Train YOLOv8 on a Custom Dataset using CLI#
🛠️ Supported Hardware#
This notebook can run in a CPU or in a GPU.
✅ AMD Instinct™ Accelerators
✅ AMD Radeon™ RX/PRO Graphics Cards
✅ AMD EPYC™ Processors
✅ AMD Ryzen™ (AI) Processors
Suggested hardware: AI PC powered by AMD Ryzen™ AI Processors
⚡ Recommended Software Environment#
🎯 Goals#
Train a YOLOv8 model using a custom dataset with the Ultralytics CLI.
Perform inference on the trained model.
💡 Problem Statement#
Let us train the YOLOv8 model on a custom dataset, specifically the Aicook dataset to detect 30 common foods, such as apple, beef, bread, milk, spinach, and tomatoes in an open refrigerator effectively.
Set up the environment#
Install the necessary libraries and set up the Ultralytics package.
!pip install ultralytics
from IPython import display
display.clear_output()
import ultralytics
ultralytics.checks()
from ultralytics import YOLO
from IPython.display import display, Image
from roboflow import Roboflow
Ultralytics YOLOv8.2.89 Python-3.12.4 torch-2.4.1+cpu CPU (AMD Ryzen 9 7940HS w/ Radeon 780M Graphics)
Setup complete (16 CPUs, 29.8 GB RAM, 103.4/943.7 GB disk)
CLI Basics#
If you want to train, validate or run inference on models and do not need to make any modifications to the code, using YOLO command line interface is the easiest way to get started. Read more about CLI in Ultralytics YOLO Docs.
yolo task=detect mode=train model=yolov8n.yaml args...
classify predict yolov8n-cls.yaml args...
segment val yolov8n-seg.yaml args...
export yolov8n.pt format=onnx args...
Inference with Pre-trained COCO Model#
yolo mode=predict runs YOLOv8 inference on a variety of sources, downloading models automatically from the latest YOLOv8 release, and saving results to runs/predict.
CLI arguments to use YOLO to perform object detection on an image
‘task=detect’ specifies the detection task
‘mode=predict’ means we are using the model in prediction mode
‘model=yolov8n.pt’ specifies the YOLOv8 nano model to use
‘conf=0.25’ sets the confidence threshold for detections (only detections above 25% confidence will be shown)
‘source=’ specifies the image URL to run detection on
‘save=True’ will save the output image with detected objects
# Change the current directory to the 'datasets' folder
%cd datasets
!yolo task=detect mode=predict model=yolov8n.pt conf=0.25 source='https://media.roboflow.com/notebooks/examples/dog.jpeg' save=True
[WinError 2] The system cannot find the file specified: 'datasets'
aup-ai-tutorials\train
This is now an optional IPython functionality, using bookmarks requires you to install the `pickleshare` library.
Ultralytics YOLOv8.2.89 🚀 Python-3.12.4 torch-2.4.1+cpu CPU (AMD Ryzen 9 7940HS w/ Radeon 780M Graphics)
YOLOv8n summary (fused): 168 layers, 3,151,904 parameters, 0 gradients, 8.7 GFLOPs
Found https://media.roboflow.com/notebooks/examples/dog.jpeg locally at dog.jpeg
image 1/1 aup-ai-tutorials\train\dog.jpeg: 640x384 1 person, 1 car, 1 dog, 61.1ms
Speed: 0.0ms preprocess, 61.1ms inference, 10.1ms postprocess per image at shape (1, 3, 640, 384)
Results saved to runs\detect\predict2
💡 Learn more at https://docs.ultralytics.com/modes/predict
Prediction test#
Show the prediction, as you can see the output is the image with the bounding boxes around the detected objects.
Image(filename='./runs/detect/predict/dog.jpeg', width=200, height=200)
Download and prepare the dataset#
Obtain the Aicook dataset from Roboflow. The Aicook open-source dataset from Roboflow contains images of day-to-day items in an open refrigerator. The classes consist of 30 common foods, such as apple, beef, bread, milk, spinach, and tomatoes. The dataset has 3,050 images in total. The original set of images of the open refrigerator had 516 images and was augmented to 3,050 images through rotation, exposure, blur, salt and pepper noise and cut-outs. The source [train:validation:test] set was split into a ratio of [2896:103:51].
Note
You will need an account in Roboflow to get the API Key in order to download the dataset.
See how to get the API Key here: https://docs.roboflow.com/api-reference/authentication
Setup your Roboflow API Key
Access the specific workspace and project within Roboflow
‘workspace(“karel-cornelis-q2qqg”)’ specifies the workspace name
‘project(“aicook-lcv4d”)’ specifies the project within that workspace
Download version 4 of the dataset in YOLOv8 format
‘version(4)’ specifies the dataset version
‘download(“yolov8”)’ downloads the dataset formatted for YOLOv8
rf = Roboflow(api_key="YOUR_API_KEY")
project = rf.workspace("karel-cornelis-q2qqg").project("aicook-lcv4d")
dataset = project.version(4).download("yolov8")
loading Roboflow workspace...
loading Roboflow project...
Dependency ultralytics==8.0.196 is required but found version=8.2.89, to fix: `pip install ultralytics==8.0.196`
Downloading Dataset Version Zip in aicook-4 to yolov8:: 100%|███████████████| 386407/386407 [00:08<00:00, 45057.25it/s]
Extracting Dataset Version Zip to aicook-4 in yolov8:: 100%|██████████████████████| 6112/6112 [00:08<00:00, 701.10it/s]
Show the 30 classes of the dataset
%pycat {dataset.location}/data.yaml
names:
- apple
- banana
- beef
- blueberries
- bread
- butter
- carrot
- cheese
- chicken
- chicken_breast
- chocolate
- corn
- eggs
- flour
- goat_cheese
- green_beans
- ground_beef
- ham
- heavy_cream
- lime
- milk
- mushrooms
- onion
- potato
- shrimp
- spinach
- strawberries
- sugar
- sweet_potato
- tomato
nc: 30
roboflow:
license: MIT
project: aicook-lcv4d
url: https://universe.roboflow.com/karel-cornelis-q2qqg/aicook-lcv4d/dataset/4
version: 4
workspace: karel-cornelis-q2qqg
test: ../test/images
train: C:/Users/npurusho/Desktop/aupai/aup-ai-tutorials-main/train/aicook-4/train/images
val: C:/Users/npurusho/Desktop/aupai/aup-ai-tutorials-main/train/aicook-4/valid/images
Training using the Ultralytics CLI#
Train the YOLOv8 model on a custom dataset using the YOLO CLI command
‘task=detect’ specifies that the task is object detection
‘mode=train’ puts the model in training mode
‘model=yolov8s.pt’ specifies the YOLOv8 small model architecture (pre-trained weights) to start training from
‘data={dataset.location}/data.yaml’ sets the path to the dataset configuration file in YAML format (this file contains paths to images, labels, and class definitions)
‘epochs=3’ defines the number of training epochs (full passes through the dataset) to be 3
‘imgsz=800’ sets the input image size to 800 pixels, adjusting the model input resolution
‘plots=True’ enables plot generation to visualize training progress
‘device=cpu’ forces training to occur on the CPU (useful if no GPU is available)
!yolo task=detect mode=train model=yolov8s.pt data={dataset.location}/data.yaml epochs=3 imgsz=800 plots=True device=cpu
New https://pypi.org/project/ultralytics/8.3.27 available 😃 Update with 'pip install -U ultralytics'
Ultralytics YOLOv8.2.89 🚀 Python-3.12.4 torch-2.4.1+cpu CPU (AMD Ryzen 9 7940HS w/ Radeon 780M Graphics)
engine\trainer: task=detect, mode=train, model=yolov8s.pt, data=aup-ai-tutorials\train\aicook-4/data.yaml, epochs=3, time=None, patience=100, batch=16, imgsz=800, save=True, save_period=-1, cache=False, device=cpu, workers=8, project=None, name=train7, exist_ok=False, pretrained=True, optimizer=auto, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=None, multi_scale=False, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, embed=None, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, label_smoothing=0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, bgr=0.0, mosaic=1.0, mixup=0.0, copy_paste=0.0, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml, save_dir=runs\detect\train7
Overriding model.yaml nc=80 with nc=30
from n params module arguments
0 -1 1 928 ultralytics.nn.modules.conv.Conv [3, 32, 3, 2]
1 -1 1 18560 ultralytics.nn.modules.conv.Conv [32, 64, 3, 2]
2 -1 1 29056 ultralytics.nn.modules.block.C2f [64, 64, 1, True]
3 -1 1 73984 ultralytics.nn.modules.conv.Conv [64, 128, 3, 2]
4 -1 2 197632 ultralytics.nn.modules.block.C2f [128, 128, 2, True]
5 -1 1 295424 ultralytics.nn.modules.conv.Conv [128, 256, 3, 2]
6 -1 2 788480 ultralytics.nn.modules.block.C2f [256, 256, 2, True]
7 -1 1 1180672 ultralytics.nn.modules.conv.Conv [256, 512, 3, 2]
8 -1 1 1838080 ultralytics.nn.modules.block.C2f [512, 512, 1, True]
9 -1 1 656896 ultralytics.nn.modules.block.SPPF [512, 512, 5]
10 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
11 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1]
12 -1 1 591360 ultralytics.nn.modules.block.C2f [768, 256, 1]
13 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
14 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1]
15 -1 1 148224 ultralytics.nn.modules.block.C2f [384, 128, 1]
16 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2]
17 [-1, 12] 1 0 ultralytics.nn.modules.conv.Concat [1]
18 -1 1 493056 ultralytics.nn.modules.block.C2f [384, 256, 1]
19 -1 1 590336 ultralytics.nn.modules.conv.Conv [256, 256, 3, 2]
20 [-1, 9] 1 0 ultralytics.nn.modules.conv.Concat [1]
21 -1 1 1969152 ultralytics.nn.modules.block.C2f [768, 512, 1]
22 [15, 18, 21] 1 2127658 ultralytics.nn.modules.head.Detect [30, [128, 256, 512]]
Model summary: 225 layers, 11,147,210 parameters, 11,147,194 gradients, 28.7 GFLOPs
Transferred 349/355 items from pretrained weights
TensorBoard: Start with 'tensorboard --logdir runs\detect\train7', view at http://localhost:6006/
Freezing layer 'model.22.dfl.conv.weight'
train: New cache created: aup-ai-tutorials\train\aicook-4\train\labels.cache
val: New cache created: aup-ai-tutorials\train\aicook-4\valid\labels.cache
Plotting labels to runs\detect\train7\labels.jpg...
optimizer: 'optimizer=auto' found, ignoring 'lr0=0.01' and 'momentum=0.937' and determining best 'optimizer', 'lr0' and 'momentum' automatically...
optimizer: AdamW(lr=0.000294, momentum=0.9) with parameter groups 57 weight(decay=0.0), 64 weight(decay=0.0005), 63 bias(decay=0.0)
TensorBoard: model graph visualization added ✅
Image sizes 800 train, 800 val
Using 0 dataloader workers
Logging results to runs\detect\train7
Starting training for 3 epochs...
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
all 103 1227 0.827 0.847 0.882 0.562
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
all 103 1227 0.909 0.918 0.956 0.627
Epoch GPU_mem box_loss cls_loss dfl_loss Instances Size
all 103 1227 0.927 0.939 0.963 0.636
3 epochs completed in 1.351 hours.
Optimizer stripped from runs\detect\train7\weights\last.pt, 22.6MB
Optimizer stripped from runs\detect\train7\weights\best.pt, 22.6MB
Validating runs\detect\train7\weights\best.pt...
Ultralytics YOLOv8.2.89 🚀 Python-3.12.4 torch-2.4.1+cpu CPU (AMD Ryzen 9 7940HS w/ Radeon 780M Graphics)
Model summary (fused): 168 layers, 11,137,194 parameters, 0 gradients, 28.5 GFLOPs
all 103 1227 0.927 0.94 0.963 0.635
apple 43 44 0.827 0.976 0.977 0.742
banana 41 41 0.986 1 0.995 0.744
beef 24 24 0.864 0.53 0.759 0.28
blueberries 33 33 0.908 0.97 0.966 0.621
bread 41 41 0.904 0.951 0.966 0.654
butter 32 32 0.983 1 0.995 0.715
carrot 35 37 0.859 0.946 0.946 0.52
cheese 49 49 0.984 1 0.995 0.74
chicken 27 27 0.962 1 0.995 0.631
chicken_breast 35 35 0.553 0.886 0.673 0.237
chocolate 29 29 1 0.872 0.98 0.61
corn 48 48 1 0.997 0.995 0.672
eggs 60 60 0.996 1 0.995 0.662
flour 53 58 0.941 0.948 0.954 0.7
goat_cheese 11 11 0.928 0.909 0.988 0.716
green_beans 47 47 0.896 0.979 0.979 0.621
ground_beef 22 22 0.825 0.859 0.949 0.442
ham 7 7 0.945 1 0.995 0.522
heavy_cream 44 44 0.98 1 0.995 0.676
lime 28 28 0.961 0.888 0.976 0.716
milk 39 48 0.954 0.958 0.981 0.724
mushrooms 56 56 0.963 0.911 0.986 0.684
onion 42 42 0.903 1 0.991 0.759
potato 64 64 1 0.947 0.984 0.702
shrimp 42 42 0.944 0.796 0.955 0.549
spinach 38 38 0.944 0.891 0.973 0.67
strawberries 51 51 0.973 0.98 0.995 0.741
sugar 63 78 0.919 1 0.974 0.704
sweet_potato 30 32 0.926 1 0.993 0.714
tomato 58 59 0.992 1 0.995 0.59
Speed: 3.7ms preprocess, 171.1ms inference, 0.0ms loss, 0.6ms postprocess per image
Results saved to runs\detect\train7
💡 Learn more at https://docs.ultralytics.com/modes/train
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1/3 0G 1.817 5.234 1.609 400 800: 13%|#3 | 24/181 [03:38<22:40, 8.66s/it]
1/3 0G 1.817 5.234 1.609 400 800: 14%|#3 | 25/181 [03:38<22:33, 8.68s/it]
1/3 0G 1.812 5.206 1.606 320 800: 14%|#3 | 25/181 [03:47<22:33, 8.68s/it]
1/3 0G 1.812 5.206 1.606 320 800: 14%|#4 | 26/181 [03:47<22:27, 8.69s/it]
1/3 0G 1.806 5.176 1.6 335 800: 14%|#4 | 26/181 [03:55<22:27, 8.69s/it]
1/3 0G 1.806 5.176 1.6 335 800: 15%|#4 | 27/181 [03:55<22:17, 8.69s/it]
1/3 0G 1.801 5.147 1.598 292 800: 15%|#4 | 27/181 [04:04<22:17, 8.69s/it]
1/3 0G 1.801 5.147 1.598 292 800: 15%|#5 | 28/181 [04:04<22:03, 8.65s/it]
1/3 0G 1.792 5.121 1.594 249 800: 15%|#5 | 28/181 [04:13<22:03, 8.65s/it]
1/3 0G 1.792 5.121 1.594 249 800: 16%|#6 | 29/181 [04:13<21:57, 8.67s/it]
1/3 0G 1.79 5.093 1.593 336 800: 16%|#6 | 29/181 [04:22<21:57, 8.67s/it]
1/3 0G 1.79 5.093 1.593 336 800: 17%|#6 | 30/181 [04:22<22:00, 8.75s/it]
1/3 0G 1.787 5.065 1.591 283 800: 17%|#6 | 30/181 [04:30<22:00, 8.75s/it]
1/3 0G 1.787 5.065 1.591 283 800: 17%|#7 | 31/181 [04:30<21:47, 8.72s/it]
1/3 0G 1.783 5.042 1.589 304 800: 17%|#7 | 31/181 [04:39<21:47, 8.72s/it]
1/3 0G 1.783 5.042 1.589 304 800: 18%|#7 | 32/181 [04:39<21:33, 8.68s/it]
1/3 0G 1.778 5.014 1.586 281 800: 18%|#7 | 32/181 [04:47<21:33, 8.68s/it]
1/3 0G 1.778 5.014 1.586 281 800: 18%|#8 | 33/181 [04:47<21:24, 8.68s/it]
1/3 0G 1.775 4.988 1.583 314 800: 18%|#8 | 33/181 [04:56<21:24, 8.68s/it]
1/3 0G 1.775 4.988 1.583 314 800: 19%|#8 | 34/181 [04:56<21:15, 8.68s/it]
1/3 0G 1.768 4.961 1.577 266 800: 19%|#8 | 34/181 [05:05<21:15, 8.68s/it]
1/3 0G 1.768 4.961 1.577 266 800: 19%|#9 | 35/181 [05:05<21:07, 8.68s/it]
1/3 0G 1.763 4.932 1.574 298 800: 19%|#9 | 35/181 [05:14<21:07, 8.68s/it]
1/3 0G 1.763 4.932 1.574 298 800: 20%|#9 | 36/181 [05:14<21:00, 8.69s/it]
1/3 0G 1.76 4.907 1.572 332 800: 20%|#9 | 36/181 [05:22<21:00, 8.69s/it]
1/3 0G 1.76 4.907 1.572 332 800: 20%|## | 37/181 [05:22<20:57, 8.73s/it]
1/3 0G 1.757 4.88 1.57 270 800: 20%|## | 37/181 [05:31<20:57, 8.73s/it]
1/3 0G 1.757 4.88 1.57 270 800: 21%|## | 38/181 [05:31<20:49, 8.74s/it]
1/3 0G 1.752 4.853 1.566 331 800: 21%|## | 38/181 [05:40<20:49, 8.74s/it]
1/3 0G 1.752 4.853 1.566 331 800: 22%|##1 | 39/181 [05:40<20:43, 8.76s/it]
1/3 0G 1.747 4.828 1.562 374 800: 22%|##1 | 39/181 [05:49<20:43, 8.76s/it]
1/3 0G 1.747 4.828 1.562 374 800: 22%|##2 | 40/181 [05:49<20:34, 8.75s/it]
1/3 0G 1.741 4.798 1.558 314 800: 22%|##2 | 40/181 [05:57<20:34, 8.75s/it]
1/3 0G 1.741 4.798 1.558 314 800: 23%|##2 | 41/181 [05:57<20:20, 8.72s/it]
1/3 0G 1.736 4.771 1.554 280 800: 23%|##2 | 41/181 [06:06<20:20, 8.72s/it]
1/3 0G 1.736 4.771 1.554 280 800: 23%|##3 | 42/181 [06:06<20:08, 8.70s/it]
1/3 0G 1.73 4.743 1.549 327 800: 23%|##3 | 42/181 [06:15<20:08, 8.70s/it]
1/3 0G 1.73 4.743 1.549 327 800: 24%|##3 | 43/181 [06:15<20:06, 8.74s/it]
1/3 0G 1.726 4.716 1.547 298 800: 24%|##3 | 43/181 [06:23<20:06, 8.74s/it]
1/3 0G 1.726 4.716 1.547 298 800: 24%|##4 | 44/181 [06:23<19:56, 8.74s/it]
1/3 0G 1.722 4.687 1.543 356 800: 24%|##4 | 44/181 [06:32<19:56, 8.74s/it]
1/3 0G 1.722 4.687 1.543 356 800: 25%|##4 | 45/181 [06:32<19:52, 8.77s/it]
1/3 0G 1.717 4.66 1.54 280 800: 25%|##4 | 45/181 [06:41<19:52, 8.77s/it]
1/3 0G 1.717 4.66 1.54 280 800: 25%|##5 | 46/181 [06:41<19:42, 8.76s/it]
1/3 0G 1.715 4.634 1.538 312 800: 25%|##5 | 46/181 [06:50<19:42, 8.76s/it]
1/3 0G 1.715 4.634 1.538 312 800: 26%|##5 | 47/181 [06:50<19:35, 8.77s/it]
1/3 0G 1.711 4.607 1.535 268 800: 26%|##5 | 47/181 [06:59<19:35, 8.77s/it]
1/3 0G 1.711 4.607 1.535 268 800: 27%|##6 | 48/181 [06:59<19:24, 8.76s/it]
1/3 0G 1.708 4.58 1.533 294 800: 27%|##6 | 48/181 [07:07<19:24, 8.76s/it]
1/3 0G 1.708 4.58 1.533 294 800: 27%|##7 | 49/181 [07:07<19:12, 8.73s/it]
1/3 0G 1.705 4.551 1.53 360 800: 27%|##7 | 49/181 [07:16<19:12, 8.73s/it]
1/3 0G 1.705 4.551 1.53 360 800: 28%|##7 | 50/181 [07:16<19:01, 8.71s/it]
1/3 0G 1.699 4.523 1.526 276 800: 28%|##7 | 50/181 [07:25<19:01, 8.71s/it]
1/3 0G 1.699 4.523 1.526 276 800: 28%|##8 | 51/181 [07:25<18:51, 8.70s/it]
1/3 0G 1.694 4.493 1.523 315 800: 28%|##8 | 51/181 [07:33<18:51, 8.70s/it]
1/3 0G 1.694 4.493 1.523 315 800: 29%|##8 | 52/181 [07:33<18:42, 8.70s/it]
1/3 0G 1.692 4.467 1.521 295 800: 29%|##8 | 52/181 [07:42<18:42, 8.70s/it]
1/3 0G 1.692 4.467 1.521 295 800: 29%|##9 | 53/181 [07:42<18:33, 8.70s/it]
1/3 0G 1.691 4.441 1.519 313 800: 29%|##9 | 53/181 [07:51<18:33, 8.70s/it]
1/3 0G 1.691 4.441 1.519 313 800: 30%|##9 | 54/181 [07:51<18:26, 8.71s/it]
1/3 0G 1.688 4.416 1.518 246 800: 30%|##9 | 54/181 [07:59<18:26, 8.71s/it]
1/3 0G 1.688 4.416 1.518 246 800: 30%|### | 55/181 [07:59<18:14, 8.69s/it]
1/3 0G 1.684 4.39 1.516 236 800: 30%|### | 55/181 [08:08<18:14, 8.69s/it]
1/3 0G 1.684 4.39 1.516 236 800: 31%|### | 56/181 [08:08<18:05, 8.68s/it]
1/3 0G 1.682 4.361 1.514 301 800: 31%|### | 56/181 [08:17<18:05, 8.68s/it]
1/3 0G 1.682 4.361 1.514 301 800: 31%|###1 | 57/181 [08:17<17:54, 8.66s/it]
1/3 0G 1.679 4.334 1.513 259 800: 31%|###1 | 57/181 [08:25<17:54, 8.66s/it]
1/3 0G 1.679 4.334 1.513 259 800: 32%|###2 | 58/181 [08:25<17:47, 8.68s/it]
1/3 0G 1.674 4.305 1.51 337 800: 32%|###2 | 58/181 [08:34<17:47, 8.68s/it]
1/3 0G 1.674 4.305 1.51 337 800: 33%|###2 | 59/181 [08:34<17:42, 8.71s/it]
1/3 0G 1.671 4.277 1.507 361 800: 33%|###2 | 59/181 [08:43<17:42, 8.71s/it]
1/3 0G 1.671 4.277 1.507 361 800: 33%|###3 | 60/181 [08:43<17:34, 8.71s/it]
1/3 0G 1.668 4.25 1.505 341 800: 33%|###3 | 60/181 [08:52<17:34, 8.71s/it]
1/3 0G 1.668 4.25 1.505 341 800: 34%|###3 | 61/181 [08:52<17:31, 8.76s/it]
1/3 0G 1.664 4.226 1.501 290 800: 34%|###3 | 61/181 [09:00<17:31, 8.76s/it]
1/3 0G 1.664 4.226 1.501 290 800: 34%|###4 | 62/181 [09:00<17:22, 8.76s/it]
1/3 0G 1.66 4.201 1.498 335 800: 34%|###4 | 62/181 [09:09<17:22, 8.76s/it]
1/3 0G 1.66 4.201 1.498 335 800: 35%|###4 | 63/181 [09:09<17:14, 8.77s/it]
1/3 0G 1.659 4.178 1.498 248 800: 35%|###4 | 63/181 [09:18<17:14, 8.77s/it]
1/3 0G 1.659 4.178 1.498 248 800: 35%|###5 | 64/181 [09:18<17:02, 8.74s/it]
1/3 0G 1.656 4.156 1.495 344 800: 35%|###5 | 64/181 [09:27<17:02, 8.74s/it]
1/3 0G 1.656 4.156 1.495 344 800: 36%|###5 | 65/181 [09:27<16:52, 8.73s/it]
1/3 0G 1.652 4.13 1.492 293 800: 36%|###5 | 65/181 [09:35<16:52, 8.73s/it]
1/3 0G 1.652 4.13 1.492 293 800: 36%|###6 | 66/181 [09:35<16:44, 8.73s/it]
1/3 0G 1.65 4.104 1.49 329 800: 36%|###6 | 66/181 [09:44<16:44, 8.73s/it]
1/3 0G 1.65 4.104 1.49 329 800: 37%|###7 | 67/181 [09:44<16:38, 8.76s/it]
1/3 0G 1.646 4.08 1.488 304 800: 37%|###7 | 67/181 [09:53<16:38, 8.76s/it]
1/3 0G 1.646 4.08 1.488 304 800: 38%|###7 | 68/181 [09:53<16:27, 8.74s/it]
1/3 0G 1.642 4.054 1.485 349 800: 38%|###7 | 68/181 [10:02<16:27, 8.74s/it]
1/3 0G 1.642 4.054 1.485 349 800: 38%|###8 | 69/181 [10:02<16:21, 8.77s/it]
1/3 0G 1.64 4.03 1.484 332 800: 38%|###8 | 69/181 [10:11<16:21, 8.77s/it]
1/3 0G 1.64 4.03 1.484 332 800: 39%|###8 | 70/181 [10:11<16:14, 8.78s/it]
1/3 0G 1.637 4.007 1.483 235 800: 39%|###8 | 70/181 [10:19<16:14, 8.78s/it]
1/3 0G 1.637 4.007 1.483 235 800: 39%|###9 | 71/181 [10:19<16:05, 8.78s/it]
1/3 0G 1.634 3.984 1.481 262 800: 39%|###9 | 71/181 [10:28<16:05, 8.78s/it]
1/3 0G 1.634 3.984 1.481 262 800: 40%|###9 | 72/181 [10:28<15:55, 8.76s/it]
1/3 0G 1.63 3.959 1.478 411 800: 40%|###9 | 72/181 [10:37<15:55, 8.76s/it]
1/3 0G 1.63 3.959 1.478 411 800: 40%|#### | 73/181 [10:37<15:47, 8.78s/it]
1/3 0G 1.628 3.935 1.476 271 800: 40%|#### | 73/181 [10:46<15:47, 8.78s/it]
1/3 0G 1.628 3.935 1.476 271 800: 41%|#### | 74/181 [10:46<15:37, 8.76s/it]
1/3 0G 1.626 3.912 1.476 309 800: 41%|#### | 74/181 [10:54<15:37, 8.76s/it]
1/3 0G 1.626 3.912 1.476 309 800: 41%|####1 | 75/181 [10:54<15:30, 8.78s/it]
1/3 0G 1.623 3.89 1.473 323 800: 41%|####1 | 75/181 [11:03<15:30, 8.78s/it]
1/3 0G 1.623 3.89 1.473 323 800: 42%|####1 | 76/181 [11:03<15:21, 8.78s/it]
1/3 0G 1.621 3.867 1.472 249 800: 42%|####1 | 76/181 [11:12<15:21, 8.78s/it]
1/3 0G 1.621 3.867 1.472 249 800: 43%|####2 | 77/181 [11:12<15:14, 8.79s/it]
1/3 0G 1.618 3.845 1.47 286 800: 43%|####2 | 77/181 [11:21<15:14, 8.79s/it]
1/3 0G 1.618 3.845 1.47 286 800: 43%|####3 | 78/181 [11:21<15:03, 8.78s/it]
1/3 0G 1.615 3.824 1.468 286 800: 43%|####3 | 78/181 [11:30<15:03, 8.78s/it]
1/3 0G 1.615 3.824 1.468 286 800: 44%|####3 | 79/181 [11:30<14:56, 8.79s/it]
1/3 0G 1.612 3.801 1.466 270 800: 44%|####3 | 79/181 [11:38<14:56, 8.79s/it]
1/3 0G 1.612 3.801 1.466 270 800: 44%|####4 | 80/181 [11:38<14:46, 8.78s/it]
1/3 0G 1.61 3.78 1.464 260 800: 44%|####4 | 80/181 [11:47<14:46, 8.78s/it]
1/3 0G 1.61 3.78 1.464 260 800: 45%|####4 | 81/181 [11:47<14:35, 8.76s/it]
1/3 0G 1.607 3.758 1.462 284 800: 45%|####4 | 81/181 [11:56<14:35, 8.76s/it]
1/3 0G 1.607 3.758 1.462 284 800: 45%|####5 | 82/181 [11:56<14:28, 8.77s/it]
1/3 0G 1.604 3.736 1.46 279 800: 45%|####5 | 82/181 [12:05<14:28, 8.77s/it]
1/3 0G 1.604 3.736 1.46 279 800: 46%|####5 | 83/181 [12:05<14:19, 8.77s/it]
1/3 0G 1.6 3.714 1.457 323 800: 46%|####5 | 83/181 [12:13<14:19, 8.77s/it]
1/3 0G 1.6 3.714 1.457 323 800: 46%|####6 | 84/181 [12:13<14:09, 8.75s/it]
1/3 0G 1.597 3.694 1.455 255 800: 46%|####6 | 84/181 [12:22<14:09, 8.75s/it]
1/3 0G 1.597 3.694 1.455 255 800: 47%|####6 | 85/181 [12:22<14:01, 8.76s/it]
1/3 0G 1.594 3.673 1.453 352 800: 47%|####6 | 85/181 [12:31<14:01, 8.76s/it]
1/3 0G 1.594 3.673 1.453 352 800: 48%|####7 | 86/181 [12:31<13:55, 8.80s/it]
1/3 0G 1.592 3.652 1.451 300 800: 48%|####7 | 86/181 [12:40<13:55, 8.80s/it]
1/3 0G 1.592 3.652 1.451 300 800: 48%|####8 | 87/181 [12:40<13:49, 8.82s/it]
1/3 0G 1.588 3.631 1.449 282 800: 48%|####8 | 87/181 [12:49<13:49, 8.82s/it]
1/3 0G 1.588 3.631 1.449 282 800: 49%|####8 | 88/181 [12:49<13:41, 8.83s/it]
1/3 0G 1.587 3.612 1.447 411 800: 49%|####8 | 88/181 [12:57<13:41, 8.83s/it]
1/3 0G 1.587 3.612 1.447 411 800: 49%|####9 | 89/181 [12:57<13:30, 8.81s/it]
1/3 0G 1.584 3.593 1.446 252 800: 49%|####9 | 89/181 [13:06<13:30, 8.81s/it]
1/3 0G 1.584 3.593 1.446 252 800: 50%|####9 | 90/181 [13:06<13:19, 8.78s/it]
1/3 0G 1.583 3.576 1.446 207 800: 50%|####9 | 90/181 [13:15<13:19, 8.78s/it]
1/3 0G 1.583 3.576 1.446 207 800: 50%|##### | 91/181 [13:15<13:08, 8.76s/it]
1/3 0G 1.58 3.557 1.444 355 800: 50%|##### | 91/181 [13:24<13:08, 8.76s/it]
1/3 0G 1.58 3.557 1.444 355 800: 51%|##### | 92/181 [13:24<12:57, 8.74s/it]
1/3 0G 1.578 3.538 1.442 324 800: 51%|##### | 92/181 [13:33<12:57, 8.74s/it]
1/3 0G 1.578 3.538 1.442 324 800: 51%|#####1 | 93/181 [13:33<12:55, 8.81s/it]
1/3 0G 1.575 3.52 1.44 314 800: 51%|#####1 | 93/181 [13:41<12:55, 8.81s/it]
1/3 0G 1.575 3.52 1.44 314 800: 52%|#####1 | 94/181 [13:41<12:45, 8.80s/it]
1/3 0G 1.573 3.503 1.44 249 800: 52%|#####1 | 94/181 [13:50<12:45, 8.80s/it]
1/3 0G 1.573 3.503 1.44 249 800: 52%|#####2 | 95/181 [13:50<12:40, 8.85s/it]
1/3 0G 1.571 3.486 1.438 259 800: 52%|#####2 | 95/181 [13:59<12:40, 8.85s/it]
1/3 0G 1.571 3.486 1.438 259 800: 53%|#####3 | 96/181 [13:59<12:27, 8.79s/it]
1/3 0G 1.569 3.468 1.437 285 800: 53%|#####3 | 96/181 [14:08<12:27, 8.79s/it]
1/3 0G 1.569 3.468 1.437 285 800: 54%|#####3 | 97/181 [14:08<12:19, 8.81s/it]
1/3 0G 1.566 3.452 1.435 306 800: 54%|#####3 | 97/181 [14:16<12:19, 8.81s/it]
1/3 0G 1.566 3.452 1.435 306 800: 54%|#####4 | 98/181 [14:16<12:07, 8.77s/it]
1/3 0G 1.564 3.435 1.434 357 800: 54%|#####4 | 98/181 [14:25<12:07, 8.77s/it]
1/3 0G 1.564 3.435 1.434 357 800: 55%|#####4 | 99/181 [14:25<12:05, 8.84s/it]
1/3 0G 1.563 3.42 1.433 287 800: 55%|#####4 | 99/181 [14:34<12:05, 8.84s/it]
1/3 0G 1.563 3.42 1.433 287 800: 55%|#####5 | 100/181 [14:34<11:53, 8.81s/it]
1/3 0G 1.561 3.404 1.431 285 800: 55%|#####5 | 100/181 [14:43<11:53, 8.81s/it]
1/3 0G 1.561 3.404 1.431 285 800: 56%|#####5 | 101/181 [14:43<11:49, 8.87s/it]
1/3 0G 1.558 3.387 1.43 373 800: 56%|#####5 | 101/181 [14:52<11:49, 8.87s/it]
1/3 0G 1.558 3.387 1.43 373 800: 56%|#####6 | 102/181 [14:52<11:36, 8.82s/it]
1/3 0G 1.556 3.372 1.428 281 800: 56%|#####6 | 102/181 [15:01<11:36, 8.82s/it]
1/3 0G 1.556 3.372 1.428 281 800: 57%|#####6 | 103/181 [15:01<11:28, 8.82s/it]
1/3 0G 1.554 3.355 1.427 236 800: 57%|#####6 | 103/181 [15:09<11:28, 8.82s/it]
1/3 0G 1.554 3.355 1.427 236 800: 57%|#####7 | 104/181 [15:09<11:14, 8.76s/it]
1/3 0G 1.551 3.34 1.426 283 800: 57%|#####7 | 104/181 [15:18<11:14, 8.76s/it]
1/3 0G 1.551 3.34 1.426 283 800: 58%|#####8 | 105/181 [15:18<11:09, 8.80s/it]
1/3 0G 1.548 3.323 1.424 339 800: 58%|#####8 | 105/181 [15:27<11:09, 8.80s/it]
1/3 0G 1.548 3.323 1.424 339 800: 59%|#####8 | 106/181 [15:27<10:57, 8.77s/it]
1/3 0G 1.546 3.308 1.422 286 800: 59%|#####8 | 106/181 [15:36<10:57, 8.77s/it]
1/3 0G 1.546 3.308 1.422 286 800: 59%|#####9 | 107/181 [15:36<10:52, 8.82s/it]
1/3 0G 1.544 3.293 1.421 250 800: 59%|#####9 | 107/181 [15:45<10:52, 8.82s/it]
1/3 0G 1.544 3.293 1.421 250 800: 60%|#####9 | 108/181 [15:45<10:42, 8.80s/it]
1/3 0G 1.542 3.278 1.419 358 800: 60%|#####9 | 108/181 [15:54<10:42, 8.80s/it]
1/3 0G 1.542 3.278 1.419 358 800: 60%|###### | 109/181 [15:54<10:36, 8.84s/it]
1/3 0G 1.54 3.264 1.418 361 800: 60%|###### | 109/181 [16:02<10:36, 8.84s/it]
1/3 0G 1.54 3.264 1.418 361 800: 61%|###### | 110/181 [16:02<10:26, 8.82s/it]
1/3 0G 1.537 3.249 1.417 220 800: 61%|###### | 110/181 [16:11<10:26, 8.82s/it]
1/3 0G 1.537 3.249 1.417 220 800: 61%|######1 | 111/181 [16:11<10:18, 8.83s/it]
1/3 0G 1.535 3.234 1.415 312 800: 61%|######1 | 111/181 [16:20<10:18, 8.83s/it]
1/3 0G 1.535 3.234 1.415 312 800: 62%|######1 | 112/181 [16:20<10:05, 8.77s/it]
1/3 0G 1.533 3.222 1.415 213 800: 62%|######1 | 112/181 [16:29<10:05, 8.77s/it]
1/3 0G 1.533 3.222 1.415 213 800: 62%|######2 | 113/181 [16:29<09:59, 8.81s/it]
1/3 0G 1.531 3.208 1.413 265 800: 62%|######2 | 113/181 [16:38<09:59, 8.81s/it]
1/3 0G 1.531 3.208 1.413 265 800: 63%|######2 | 114/181 [16:38<09:57, 8.91s/it]
1/3 0G 1.529 3.195 1.412 265 800: 63%|######2 | 114/181 [16:47<09:57, 8.91s/it]
1/3 0G 1.529 3.195 1.412 265 800: 64%|######3 | 115/181 [16:47<09:50, 8.94s/it]
1/3 0G 1.527 3.182 1.411 323 800: 64%|######3 | 115/181 [16:56<09:50, 8.94s/it]
1/3 0G 1.527 3.182 1.411 323 800: 64%|######4 | 116/181 [16:56<09:36, 8.87s/it]
1/3 0G 1.526 3.169 1.41 293 800: 64%|######4 | 116/181 [17:05<09:36, 8.87s/it]
1/3 0G 1.526 3.169 1.41 293 800: 65%|######4 | 117/181 [17:05<09:28, 8.88s/it]
1/3 0G 1.524 3.155 1.409 307 800: 65%|######4 | 117/181 [17:13<09:28, 8.88s/it]
1/3 0G 1.524 3.155 1.409 307 800: 65%|######5 | 118/181 [17:13<09:16, 8.83s/it]
1/3 0G 1.523 3.141 1.407 280 800: 65%|######5 | 118/181 [17:22<09:16, 8.83s/it]
1/3 0G 1.523 3.141 1.407 280 800: 66%|######5 | 119/181 [17:22<09:09, 8.86s/it]
1/3 0G 1.52 3.13 1.406 195 800: 66%|######5 | 119/181 [17:31<09:09, 8.86s/it]
1/3 0G 1.52 3.13 1.406 195 800: 66%|######6 | 120/181 [17:31<08:56, 8.79s/it]
1/3 0G 1.518 3.117 1.405 306 800: 66%|######6 | 120/181 [17:40<08:56, 8.79s/it]
1/3 0G 1.518 3.117 1.405 306 800: 67%|######6 | 121/181 [17:40<08:49, 8.82s/it]
1/3 0G 1.516 3.104 1.404 329 800: 67%|######6 | 121/181 [17:49<08:49, 8.82s/it]
1/3 0G 1.516 3.104 1.404 329 800: 67%|######7 | 122/181 [17:49<08:41, 8.84s/it]
1/3 0G 1.514 3.092 1.402 401 800: 67%|######7 | 122/181 [17:58<08:41, 8.84s/it]
1/3 0G 1.514 3.092 1.402 401 800: 68%|######7 | 123/181 [17:58<08:37, 8.92s/it]
1/3 0G 1.513 3.079 1.401 362 800: 68%|######7 | 123/181 [18:07<08:37, 8.92s/it]
1/3 0G 1.513 3.079 1.401 362 800: 69%|######8 | 124/181 [18:07<08:28, 8.92s/it]
1/3 0G 1.511 3.066 1.399 347 800: 69%|######8 | 124/181 [18:16<08:28, 8.92s/it]
1/3 0G 1.511 3.066 1.399 347 800: 69%|######9 | 125/181 [18:16<08:22, 8.97s/it]
1/3 0G 1.509 3.053 1.398 307 800: 69%|######9 | 125/181 [18:25<08:22, 8.97s/it]
1/3 0G 1.509 3.053 1.398 307 800: 70%|######9 | 126/181 [18:25<08:13, 8.96s/it]
1/3 0G 1.507 3.041 1.397 271 800: 70%|######9 | 126/181 [18:34<08:13, 8.96s/it]
1/3 0G 1.507 3.041 1.397 271 800: 70%|####### | 127/181 [18:34<08:06, 9.01s/it]
1/3 0G 1.504 3.027 1.395 321 800: 70%|####### | 127/181 [18:43<08:06, 9.01s/it]
1/3 0G 1.504 3.027 1.395 321 800: 71%|####### | 128/181 [18:43<07:53, 8.94s/it]
1/3 0G 1.502 3.016 1.394 311 800: 71%|####### | 128/181 [18:51<07:53, 8.94s/it]
1/3 0G 1.502 3.016 1.394 311 800: 71%|#######1 | 129/181 [18:51<07:44, 8.94s/it]
1/3 0G 1.5 3.004 1.392 287 800: 71%|#######1 | 129/181 [19:00<07:44, 8.94s/it]
1/3 0G 1.5 3.004 1.392 287 800: 72%|#######1 | 130/181 [19:00<07:33, 8.88s/it]
1/3 0G 1.498 2.992 1.391 233 800: 72%|#######1 | 130/181 [19:09<07:33, 8.88s/it]
1/3 0G 1.498 2.992 1.391 233 800: 72%|#######2 | 131/181 [19:09<07:24, 8.90s/it]
1/3 0G 1.496 2.98 1.39 326 800: 72%|#######2 | 131/181 [19:18<07:24, 8.90s/it]
1/3 0G 1.496 2.98 1.39 326 800: 73%|#######2 | 132/181 [19:18<07:12, 8.84s/it]
1/3 0G 1.494 2.968 1.389 301 800: 73%|#######2 | 132/181 [19:27<07:12, 8.84s/it]
1/3 0G 1.494 2.968 1.389 301 800: 73%|#######3 | 133/181 [19:27<07:04, 8.85s/it]
1/3 0G 1.493 2.957 1.388 351 800: 73%|#######3 | 133/181 [19:36<07:04, 8.85s/it]
1/3 0G 1.493 2.957 1.388 351 800: 74%|#######4 | 134/181 [19:36<06:55, 8.83s/it]
1/3 0G 1.491 2.946 1.386 411 800: 74%|#######4 | 134/181 [19:45<06:55, 8.83s/it]
1/3 0G 1.491 2.946 1.386 411 800: 75%|#######4 | 135/181 [19:45<06:49, 8.89s/it]
1/3 0G 1.489 2.934 1.385 375 800: 75%|#######4 | 135/181 [19:53<06:49, 8.89s/it]
1/3 0G 1.489 2.934 1.385 375 800: 75%|#######5 | 136/181 [19:53<06:40, 8.89s/it]
1/3 0G 1.488 2.924 1.384 327 800: 75%|#######5 | 136/181 [20:02<06:40, 8.89s/it]
1/3 0G 1.488 2.924 1.384 327 800: 76%|#######5 | 137/181 [20:02<06:30, 8.88s/it]
1/3 0G 1.487 2.913 1.383 370 800: 76%|#######5 | 137/181 [20:11<06:30, 8.88s/it]
1/3 0G 1.487 2.913 1.383 370 800: 76%|#######6 | 138/181 [20:11<06:20, 8.84s/it]
1/3 0G 1.485 2.901 1.381 355 800: 76%|#######6 | 138/181 [20:20<06:20, 8.84s/it]
1/3 0G 1.485 2.901 1.381 355 800: 77%|#######6 | 139/181 [20:20<06:13, 8.89s/it]
1/3 0G 1.483 2.89 1.38 286 800: 77%|#######6 | 139/181 [20:29<06:13, 8.89s/it]
1/3 0G 1.483 2.89 1.38 286 800: 77%|#######7 | 140/181 [20:29<06:04, 8.88s/it]
1/3 0G 1.482 2.88 1.38 229 800: 77%|#######7 | 140/181 [20:38<06:04, 8.88s/it]
1/3 0G 1.482 2.88 1.38 229 800: 78%|#######7 | 141/181 [20:38<05:56, 8.90s/it]
1/3 0G 1.48 2.869 1.378 294 800: 78%|#######7 | 141/181 [20:47<05:56, 8.90s/it]
1/3 0G 1.48 2.869 1.378 294 800: 78%|#######8 | 142/181 [20:47<05:45, 8.86s/it]
1/3 0G 1.479 2.859 1.378 299 800: 78%|#######8 | 142/181 [20:56<05:45, 8.86s/it]
1/3 0G 1.479 2.859 1.378 299 800: 79%|#######9 | 143/181 [20:56<05:37, 8.87s/it]
1/3 0G 1.477 2.848 1.377 303 800: 79%|#######9 | 143/181 [21:04<05:37, 8.87s/it]
1/3 0G 1.477 2.848 1.377 303 800: 80%|#######9 | 144/181 [21:04<05:27, 8.86s/it]
1/3 0G 1.476 2.838 1.376 415 800: 80%|#######9 | 144/181 [21:13<05:27, 8.86s/it]
1/3 0G 1.476 2.838 1.376 415 800: 80%|######## | 145/181 [21:13<05:19, 8.88s/it]
1/3 0G 1.474 2.828 1.374 347 800: 80%|######## | 145/181 [21:22<05:19, 8.88s/it]
1/3 0G 1.474 2.828 1.374 347 800: 81%|######## | 146/181 [21:22<05:09, 8.84s/it]
1/3 0G 1.472 2.817 1.373 329 800: 81%|######## | 146/181 [21:31<05:09, 8.84s/it]
1/3 0G 1.472 2.817 1.373 329 800: 81%|########1 | 147/181 [21:31<05:01, 8.87s/it]
1/3 0G 1.471 2.807 1.372 382 800: 81%|########1 | 147/181 [21:40<05:01, 8.87s/it]
1/3 0G 1.471 2.807 1.372 382 800: 82%|########1 | 148/181 [21:40<04:52, 8.87s/it]
1/3 0G 1.469 2.797 1.37 321 800: 82%|########1 | 148/181 [21:49<04:52, 8.87s/it]
1/3 0G 1.469 2.797 1.37 321 800: 82%|########2 | 149/181 [21:49<04:43, 8.87s/it]
1/3 0G 1.467 2.787 1.369 282 800: 82%|########2 | 149/181 [21:57<04:43, 8.87s/it]
1/3 0G 1.467 2.787 1.369 282 800: 83%|########2 | 150/181 [21:57<04:33, 8.83s/it]
1/3 0G 1.465 2.777 1.368 254 800: 83%|########2 | 150/181 [22:06<04:33, 8.83s/it]
1/3 0G 1.465 2.777 1.368 254 800: 83%|########3 | 151/181 [22:06<04:25, 8.83s/it]
1/3 0G 1.463 2.767 1.367 245 800: 83%|########3 | 151/181 [22:15<04:25, 8.83s/it]
1/3 0G 1.463 2.767 1.367 245 800: 84%|########3 | 152/181 [22:15<04:14, 8.79s/it]
1/3 0G 1.462 2.757 1.366 303 800: 84%|########3 | 152/181 [22:24<04:14, 8.79s/it]
1/3 0G 1.462 2.757 1.366 303 800: 85%|########4 | 153/181 [22:24<04:07, 8.84s/it]
1/3 0G 1.46 2.747 1.365 315 800: 85%|########4 | 153/181 [22:33<04:07, 8.84s/it]
1/3 0G 1.46 2.747 1.365 315 800: 85%|########5 | 154/181 [22:33<03:57, 8.81s/it]
1/3 0G 1.458 2.738 1.364 334 800: 85%|########5 | 154/181 [22:42<03:57, 8.81s/it]
1/3 0G 1.458 2.738 1.364 334 800: 86%|########5 | 155/181 [22:42<03:50, 8.86s/it]
1/3 0G 1.457 2.728 1.363 309 800: 86%|########5 | 155/181 [22:50<03:50, 8.86s/it]
1/3 0G 1.457 2.728 1.363 309 800: 86%|########6 | 156/181 [22:50<03:41, 8.85s/it]
1/3 0G 1.456 2.72 1.363 220 800: 86%|########6 | 156/181 [22:59<03:41, 8.85s/it]
1/3 0G 1.456 2.72 1.363 220 800: 87%|########6 | 157/181 [22:59<03:32, 8.86s/it]
1/3 0G 1.454 2.712 1.362 273 800: 87%|########6 | 157/181 [23:08<03:32, 8.86s/it]
1/3 0G 1.454 2.712 1.362 273 800: 87%|########7 | 158/181 [23:08<03:23, 8.84s/it]
1/3 0G 1.452 2.702 1.36 295 800: 87%|########7 | 158/181 [23:17<03:23, 8.84s/it]
1/3 0G 1.452 2.702 1.36 295 800: 88%|########7 | 159/181 [23:17<03:15, 8.89s/it]
1/3 0G 1.451 2.693 1.359 302 800: 88%|########7 | 159/181 [23:26<03:15, 8.89s/it]
1/3 0G 1.451 2.693 1.359 302 800: 88%|########8 | 160/181 [23:26<03:05, 8.84s/it]
1/3 0G 1.449 2.685 1.358 369 800: 88%|########8 | 160/181 [23:35<03:05, 8.84s/it]
1/3 0G 1.449 2.685 1.358 369 800: 89%|########8 | 161/181 [23:35<02:57, 8.87s/it]
1/3 0G 1.448 2.677 1.357 303 800: 89%|########8 | 161/181 [23:44<02:57, 8.87s/it]
1/3 0G 1.448 2.677 1.357 303 800: 90%|########9 | 162/181 [23:44<02:48, 8.87s/it]
1/3 0G 1.447 2.668 1.356 239 800: 90%|########9 | 162/181 [23:53<02:48, 8.87s/it]
1/3 0G 1.447 2.668 1.356 239 800: 90%|######### | 163/181 [23:53<02:40, 8.89s/it]
1/3 0G 1.445 2.659 1.355 300 800: 90%|######### | 163/181 [24:01<02:40, 8.89s/it]
1/3 0G 1.445 2.659 1.355 300 800: 91%|######### | 164/181 [24:01<02:30, 8.83s/it]
1/3 0G 1.445 2.651 1.355 235 800: 91%|######### | 164/181 [24:10<02:30, 8.83s/it]
1/3 0G 1.445 2.651 1.355 235 800: 91%|#########1| 165/181 [24:10<02:21, 8.86s/it]
1/3 0G 1.443 2.642 1.354 243 800: 91%|#########1| 165/181 [24:19<02:21, 8.86s/it]
1/3 0G 1.443 2.642 1.354 243 800: 92%|#########1| 166/181 [24:19<02:11, 8.79s/it]
1/3 0G 1.442 2.634 1.353 337 800: 92%|#########1| 166/181 [24:28<02:11, 8.79s/it]
1/3 0G 1.442 2.634 1.353 337 800: 92%|#########2| 167/181 [24:28<02:03, 8.83s/it]
1/3 0G 1.44 2.625 1.352 301 800: 92%|#########2| 167/181 [24:37<02:03, 8.83s/it]
1/3 0G 1.44 2.625 1.352 301 800: 93%|#########2| 168/181 [24:37<01:54, 8.82s/it]
1/3 0G 1.439 2.617 1.351 338 800: 93%|#########2| 168/181 [24:46<01:54, 8.82s/it]
1/3 0G 1.439 2.617 1.351 338 800: 93%|#########3| 169/181 [24:46<01:46, 8.86s/it]
1/3 0G 1.438 2.61 1.35 355 800: 93%|#########3| 169/181 [24:54<01:46, 8.86s/it]
1/3 0G 1.438 2.61 1.35 355 800: 94%|#########3| 170/181 [24:54<01:37, 8.85s/it]
1/3 0G 1.436 2.601 1.349 306 800: 94%|#########3| 170/181 [25:03<01:37, 8.85s/it]
1/3 0G 1.436 2.601 1.349 306 800: 94%|#########4| 171/181 [25:03<01:28, 8.89s/it]
1/3 0G 1.435 2.593 1.348 346 800: 94%|#########4| 171/181 [25:12<01:28, 8.89s/it]
1/3 0G 1.435 2.593 1.348 346 800: 95%|#########5| 172/181 [25:12<01:19, 8.84s/it]
1/3 0G 1.434 2.585 1.347 384 800: 95%|#########5| 172/181 [25:21<01:19, 8.84s/it]
1/3 0G 1.434 2.585 1.347 384 800: 96%|#########5| 173/181 [25:21<01:11, 8.89s/it]
1/3 0G 1.432 2.578 1.347 178 800: 96%|#########5| 173/181 [25:30<01:11, 8.89s/it]
1/3 0G 1.432 2.578 1.347 178 800: 96%|#########6| 174/181 [25:30<01:01, 8.77s/it]
1/3 0G 1.431 2.57 1.346 263 800: 96%|#########6| 174/181 [25:38<01:01, 8.77s/it]
1/3 0G 1.431 2.57 1.346 263 800: 97%|#########6| 175/181 [25:38<00:52, 8.79s/it]
1/3 0G 1.43 2.562 1.345 339 800: 97%|#########6| 175/181 [25:47<00:52, 8.79s/it]
1/3 0G 1.43 2.562 1.345 339 800: 97%|#########7| 176/181 [25:47<00:43, 8.78s/it]
1/3 0G 1.428 2.554 1.344 264 800: 97%|#########7| 176/181 [25:56<00:43, 8.78s/it]
1/3 0G 1.428 2.554 1.344 264 800: 98%|#########7| 177/181 [25:56<00:35, 8.85s/it]
1/3 0G 1.427 2.546 1.343 265 800: 98%|#########7| 177/181 [26:05<00:35, 8.85s/it]
1/3 0G 1.427 2.546 1.343 265 800: 98%|#########8| 178/181 [26:05<00:26, 8.81s/it]
1/3 0G 1.425 2.538 1.343 361 800: 98%|#########8| 178/181 [26:14<00:26, 8.81s/it]
1/3 0G 1.425 2.538 1.343 361 800: 99%|#########8| 179/181 [26:14<00:17, 8.88s/it]
1/3 0G 1.424 2.531 1.342 252 800: 99%|#########8| 179/181 [26:23<00:17, 8.88s/it]
1/3 0G 1.424 2.531 1.342 252 800: 99%|#########9| 180/181 [26:23<00:08, 8.81s/it]
1/3 0G 1.423 2.524 1.341 306 800: 99%|#########9| 180/181 [26:31<00:08, 8.81s/it]
1/3 0G 1.423 2.524 1.341 306 800: 100%|##########| 181/181 [26:31<00:00, 8.81s/it]
1/3 0G 1.423 2.524 1.341 306 800: 100%|##########| 181/181 [26:31<00:00, 8.80s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 0%| | 0/4 [00:00<?, ?it/s]
Class Images Instances Box(P R mAP50 mAP50-95): 25%|##5 | 1/4 [00:07<00:23, 7.94s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 50%|##### | 2/4 [00:14<00:14, 7.37s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 75%|#######5 | 3/4 [00:22<00:07, 7.30s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 100%|##########| 4/4 [00:23<00:00, 4.99s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 100%|##########| 4/4 [00:23<00:00, 5.89s/it]
0%| | 0/181 [00:00<?, ?it/s]
2/3 0G 1.203 1.139 1.178 316 800: 0%| | 0/181 [00:08<?, ?it/s]
2/3 0G 1.203 1.139 1.178 316 800: 1%| | 1/181 [00:08<25:46, 8.59s/it]
2/3 0G 1.213 1.189 1.166 298 800: 1%| | 1/181 [00:17<25:46, 8.59s/it]
2/3 0G 1.213 1.189 1.166 298 800: 1%|1 | 2/181 [00:17<26:03, 8.73s/it]
2/3 0G 1.207 1.197 1.183 290 800: 1%|1 | 2/181 [00:26<26:03, 8.73s/it]
2/3 0G 1.207 1.197 1.183 290 800: 2%|1 | 3/181 [00:26<25:50, 8.71s/it]
2/3 0G 1.179 1.172 1.17 297 800: 2%|1 | 3/181 [00:34<25:50, 8.71s/it]
2/3 0G 1.179 1.172 1.17 297 800: 2%|2 | 4/181 [00:34<25:51, 8.77s/it]
2/3 0G 1.193 1.193 1.19 275 800: 2%|2 | 4/181 [00:43<25:51, 8.77s/it]
2/3 0G 1.193 1.193 1.19 275 800: 3%|2 | 5/181 [00:43<25:40, 8.75s/it]
2/3 0G 1.19 1.183 1.185 310 800: 3%|2 | 5/181 [00:52<25:40, 8.75s/it]
2/3 0G 1.19 1.183 1.185 310 800: 3%|3 | 6/181 [00:52<25:42, 8.81s/it]
2/3 0G 1.186 1.178 1.185 224 800: 3%|3 | 6/181 [01:01<25:42, 8.81s/it]
2/3 0G 1.186 1.178 1.185 224 800: 4%|3 | 7/181 [01:01<25:25, 8.77s/it]
2/3 0G 1.187 1.169 1.186 304 800: 4%|3 | 7/181 [01:10<25:25, 8.77s/it]
2/3 0G 1.187 1.169 1.186 304 800: 4%|4 | 8/181 [01:10<25:24, 8.81s/it]
2/3 0G 1.183 1.159 1.186 288 800: 4%|4 | 8/181 [01:19<25:24, 8.81s/it]
2/3 0G 1.183 1.159 1.186 288 800: 5%|4 | 9/181 [01:19<25:21, 8.85s/it]
2/3 0G 1.181 1.162 1.186 260 800: 5%|4 | 9/181 [01:27<25:21, 8.85s/it]
2/3 0G 1.181 1.162 1.186 260 800: 6%|5 | 10/181 [01:27<25:12, 8.85s/it]
2/3 0G 1.188 1.164 1.186 373 800: 6%|5 | 10/181 [01:36<25:12, 8.85s/it]
2/3 0G 1.188 1.164 1.186 373 800: 6%|6 | 11/181 [01:36<25:03, 8.84s/it]
2/3 0G 1.189 1.162 1.189 273 800: 6%|6 | 11/181 [01:45<25:03, 8.84s/it]
2/3 0G 1.189 1.162 1.189 273 800: 7%|6 | 12/181 [01:45<24:49, 8.81s/it]
2/3 0G 1.19 1.162 1.19 262 800: 7%|6 | 12/181 [01:54<24:49, 8.81s/it]
2/3 0G 1.19 1.162 1.19 262 800: 7%|7 | 13/181 [01:54<24:36, 8.79s/it]
2/3 0G 1.187 1.157 1.188 301 800: 7%|7 | 13/181 [02:03<24:36, 8.79s/it]
2/3 0G 1.187 1.157 1.188 301 800: 8%|7 | 14/181 [02:03<24:37, 8.85s/it]
2/3 0G 1.188 1.159 1.188 352 800: 8%|7 | 14/181 [02:12<24:37, 8.85s/it]
2/3 0G 1.188 1.159 1.188 352 800: 8%|8 | 15/181 [02:12<24:27, 8.84s/it]
2/3 0G 1.187 1.161 1.189 309 800: 8%|8 | 15/181 [02:20<24:27, 8.84s/it]
2/3 0G 1.187 1.161 1.189 309 800: 9%|8 | 16/181 [02:20<24:20, 8.85s/it]
2/3 0G 1.188 1.163 1.189 287 800: 9%|8 | 16/181 [02:29<24:20, 8.85s/it]
2/3 0G 1.188 1.163 1.189 287 800: 9%|9 | 17/181 [02:29<24:06, 8.82s/it]
2/3 0G 1.187 1.157 1.189 290 800: 9%|9 | 17/181 [02:38<24:06, 8.82s/it]
2/3 0G 1.187 1.157 1.189 290 800: 10%|9 | 18/181 [02:38<24:00, 8.84s/it]
2/3 0G 1.187 1.154 1.19 259 800: 10%|9 | 18/181 [02:47<24:00, 8.84s/it]
2/3 0G 1.187 1.154 1.19 259 800: 10%|# | 19/181 [02:47<23:44, 8.79s/it]
2/3 0G 1.187 1.153 1.188 319 800: 10%|# | 19/181 [02:56<23:44, 8.79s/it]
2/3 0G 1.187 1.153 1.188 319 800: 11%|#1 | 20/181 [02:56<23:40, 8.82s/it]
2/3 0G 1.188 1.153 1.187 388 800: 11%|#1 | 20/181 [03:04<23:40, 8.82s/it]
2/3 0G 1.188 1.153 1.187 388 800: 12%|#1 | 21/181 [03:04<23:32, 8.83s/it]
2/3 0G 1.19 1.152 1.19 270 800: 12%|#1 | 21/181 [03:13<23:32, 8.83s/it]
2/3 0G 1.19 1.152 1.19 270 800: 12%|#2 | 22/181 [03:13<23:26, 8.85s/it]
2/3 0G 1.188 1.15 1.189 316 800: 12%|#2 | 22/181 [03:22<23:26, 8.85s/it]
2/3 0G 1.188 1.15 1.189 316 800: 13%|#2 | 23/181 [03:22<23:12, 8.81s/it]
2/3 0G 1.185 1.146 1.187 272 800: 13%|#2 | 23/181 [03:31<23:12, 8.81s/it]
2/3 0G 1.185 1.146 1.187 272 800: 13%|#3 | 24/181 [03:31<23:05, 8.82s/it]
2/3 0G 1.186 1.145 1.187 272 800: 13%|#3 | 24/181 [03:40<23:05, 8.82s/it]
2/3 0G 1.186 1.145 1.187 272 800: 14%|#3 | 25/181 [03:40<22:48, 8.77s/it]
2/3 0G 1.187 1.142 1.189 249 800: 14%|#3 | 25/181 [03:49<22:48, 8.77s/it]
2/3 0G 1.187 1.142 1.189 249 800: 14%|#4 | 26/181 [03:49<22:47, 8.82s/it]
2/3 0G 1.185 1.142 1.186 343 800: 14%|#4 | 26/181 [03:57<22:47, 8.82s/it]
2/3 0G 1.185 1.142 1.186 343 800: 15%|#4 | 27/181 [03:57<22:35, 8.80s/it]
2/3 0G 1.183 1.14 1.183 320 800: 15%|#4 | 27/181 [04:06<22:35, 8.80s/it]
2/3 0G 1.183 1.14 1.183 320 800: 15%|#5 | 28/181 [04:06<22:32, 8.84s/it]
2/3 0G 1.181 1.135 1.183 302 800: 15%|#5 | 28/181 [04:15<22:32, 8.84s/it]
2/3 0G 1.181 1.135 1.183 302 800: 16%|#6 | 29/181 [04:15<22:24, 8.85s/it]
2/3 0G 1.18 1.132 1.182 289 800: 16%|#6 | 29/181 [04:24<22:24, 8.85s/it]
2/3 0G 1.18 1.132 1.182 289 800: 17%|#6 | 30/181 [04:24<22:11, 8.82s/it]
2/3 0G 1.18 1.13 1.181 266 800: 17%|#6 | 30/181 [04:33<22:11, 8.82s/it]
2/3 0G 1.18 1.13 1.181 266 800: 17%|#7 | 31/181 [04:33<21:56, 8.78s/it]
2/3 0G 1.178 1.128 1.18 340 800: 17%|#7 | 31/181 [04:41<21:56, 8.78s/it]
2/3 0G 1.178 1.128 1.18 340 800: 18%|#7 | 32/181 [04:41<21:52, 8.81s/it]
2/3 0G 1.178 1.129 1.179 250 800: 18%|#7 | 32/181 [04:50<21:52, 8.81s/it]
2/3 0G 1.178 1.129 1.179 250 800: 18%|#8 | 33/181 [04:50<21:32, 8.73s/it]
2/3 0G 1.179 1.127 1.178 329 800: 18%|#8 | 33/181 [04:59<21:32, 8.73s/it]
2/3 0G 1.179 1.127 1.178 329 800: 19%|#8 | 34/181 [04:59<21:29, 8.77s/it]
2/3 0G 1.179 1.127 1.178 261 800: 19%|#8 | 34/181 [05:08<21:29, 8.77s/it]
2/3 0G 1.179 1.127 1.178 261 800: 19%|#9 | 35/181 [05:08<21:21, 8.77s/it]
2/3 0G 1.176 1.123 1.176 326 800: 19%|#9 | 35/181 [05:17<21:21, 8.77s/it]
2/3 0G 1.176 1.123 1.176 326 800: 20%|#9 | 36/181 [05:17<21:19, 8.83s/it]
2/3 0G 1.176 1.12 1.176 294 800: 20%|#9 | 36/181 [05:25<21:19, 8.83s/it]
2/3 0G 1.176 1.12 1.176 294 800: 20%|## | 37/181 [05:25<21:14, 8.85s/it]
2/3 0G 1.175 1.118 1.175 272 800: 20%|## | 37/181 [05:35<21:14, 8.85s/it]
2/3 0G 1.175 1.118 1.175 272 800: 21%|## | 38/181 [05:35<21:13, 8.91s/it]
2/3 0G 1.174 1.115 1.174 306 800: 21%|## | 38/181 [05:43<21:13, 8.91s/it]
2/3 0G 1.174 1.115 1.174 306 800: 22%|##1 | 39/181 [05:43<21:06, 8.92s/it]
2/3 0G 1.173 1.115 1.175 241 800: 22%|##1 | 39/181 [05:53<21:06, 8.92s/it]
2/3 0G 1.173 1.115 1.175 241 800: 22%|##2 | 40/181 [05:53<21:10, 9.01s/it]
2/3 0G 1.173 1.114 1.177 199 800: 22%|##2 | 40/181 [06:02<21:10, 9.01s/it]
2/3 0G 1.173 1.114 1.177 199 800: 23%|##2 | 41/181 [06:02<20:57, 8.98s/it]
2/3 0G 1.172 1.113 1.177 232 800: 23%|##2 | 41/181 [06:11<20:57, 8.98s/it]
2/3 0G 1.172 1.113 1.177 232 800: 23%|##3 | 42/181 [06:11<20:51, 9.00s/it]
2/3 0G 1.171 1.111 1.176 289 800: 23%|##3 | 42/181 [06:20<20:51, 9.00s/it]
2/3 0G 1.171 1.111 1.176 289 800: 24%|##3 | 43/181 [06:20<20:42, 9.00s/it]
2/3 0G 1.171 1.11 1.177 259 800: 24%|##3 | 43/181 [06:29<20:42, 9.00s/it]
2/3 0G 1.171 1.11 1.177 259 800: 24%|##4 | 44/181 [06:29<20:32, 9.00s/it]
2/3 0G 1.17 1.109 1.177 220 800: 24%|##4 | 44/181 [06:37<20:32, 9.00s/it]
2/3 0G 1.17 1.109 1.177 220 800: 25%|##4 | 45/181 [06:37<20:16, 8.94s/it]
2/3 0G 1.168 1.106 1.176 282 800: 25%|##4 | 45/181 [06:46<20:16, 8.94s/it]
2/3 0G 1.168 1.106 1.176 282 800: 25%|##5 | 46/181 [06:46<20:08, 8.95s/it]
2/3 0G 1.167 1.104 1.174 319 800: 25%|##5 | 46/181 [06:55<20:08, 8.95s/it]
2/3 0G 1.167 1.104 1.174 319 800: 26%|##5 | 47/181 [06:55<20:00, 8.96s/it]
2/3 0G 1.167 1.104 1.174 297 800: 26%|##5 | 47/181 [07:04<20:00, 8.96s/it]
2/3 0G 1.167 1.104 1.174 297 800: 27%|##6 | 48/181 [07:04<19:56, 8.99s/it]
2/3 0G 1.165 1.101 1.174 290 800: 27%|##6 | 48/181 [07:13<19:56, 8.99s/it]
2/3 0G 1.165 1.101 1.174 290 800: 27%|##7 | 49/181 [07:13<19:38, 8.93s/it]
2/3 0G 1.165 1.1 1.175 249 800: 27%|##7 | 49/181 [07:22<19:38, 8.93s/it]
2/3 0G 1.165 1.1 1.175 249 800: 28%|##7 | 50/181 [07:22<19:28, 8.92s/it]
2/3 0G 1.165 1.097 1.174 336 800: 28%|##7 | 50/181 [07:31<19:28, 8.92s/it]
2/3 0G 1.165 1.097 1.174 336 800: 28%|##8 | 51/181 [07:31<19:15, 8.89s/it]
2/3 0G 1.164 1.095 1.174 257 800: 28%|##8 | 51/181 [07:40<19:15, 8.89s/it]
2/3 0G 1.164 1.095 1.174 257 800: 29%|##8 | 52/181 [07:40<19:04, 8.87s/it]
2/3 0G 1.164 1.093 1.173 387 800: 29%|##8 | 52/181 [07:49<19:04, 8.87s/it]
2/3 0G 1.164 1.093 1.173 387 800: 29%|##9 | 53/181 [07:49<18:51, 8.84s/it]
2/3 0G 1.163 1.092 1.172 308 800: 29%|##9 | 53/181 [07:57<18:51, 8.84s/it]
2/3 0G 1.163 1.092 1.172 308 800: 30%|##9 | 54/181 [07:57<18:44, 8.85s/it]
2/3 0G 1.162 1.091 1.172 213 800: 30%|##9 | 54/181 [08:06<18:44, 8.85s/it]
2/3 0G 1.162 1.091 1.172 213 800: 30%|### | 55/181 [08:06<18:27, 8.79s/it]
2/3 0G 1.161 1.09 1.172 344 800: 30%|### | 55/181 [08:15<18:27, 8.79s/it]
2/3 0G 1.161 1.09 1.172 344 800: 31%|### | 56/181 [08:15<18:23, 8.82s/it]
2/3 0G 1.162 1.089 1.172 269 800: 31%|### | 56/181 [08:24<18:23, 8.82s/it]
2/3 0G 1.162 1.089 1.172 269 800: 31%|###1 | 57/181 [08:24<18:09, 8.79s/it]
2/3 0G 1.161 1.087 1.171 271 800: 31%|###1 | 57/181 [08:33<18:09, 8.79s/it]
2/3 0G 1.161 1.087 1.171 271 800: 32%|###2 | 58/181 [08:33<18:03, 8.81s/it]
2/3 0G 1.16 1.086 1.171 243 800: 32%|###2 | 58/181 [08:42<18:03, 8.81s/it]
2/3 0G 1.16 1.086 1.171 243 800: 33%|###2 | 59/181 [08:42<18:02, 8.87s/it]
2/3 0G 1.16 1.084 1.171 327 800: 33%|###2 | 59/181 [08:50<18:02, 8.87s/it]
2/3 0G 1.16 1.084 1.171 327 800: 33%|###3 | 60/181 [08:50<17:53, 8.87s/it]
2/3 0G 1.159 1.082 1.17 289 800: 33%|###3 | 60/181 [08:59<17:53, 8.87s/it]
2/3 0G 1.159 1.082 1.17 289 800: 34%|###3 | 61/181 [08:59<17:39, 8.83s/it]
2/3 0G 1.158 1.08 1.17 255 800: 34%|###3 | 61/181 [09:08<17:39, 8.83s/it]
2/3 0G 1.158 1.08 1.17 255 800: 34%|###4 | 62/181 [09:08<17:29, 8.82s/it]
2/3 0G 1.158 1.078 1.169 335 800: 34%|###4 | 62/181 [09:17<17:29, 8.82s/it]
2/3 0G 1.158 1.078 1.169 335 800: 35%|###4 | 63/181 [09:17<17:22, 8.83s/it]
2/3 0G 1.157 1.077 1.169 278 800: 35%|###4 | 63/181 [09:26<17:22, 8.83s/it]
2/3 0G 1.157 1.077 1.169 278 800: 35%|###5 | 64/181 [09:26<17:12, 8.82s/it]
2/3 0G 1.157 1.075 1.169 307 800: 35%|###5 | 64/181 [09:34<17:12, 8.82s/it]
2/3 0G 1.157 1.075 1.169 307 800: 36%|###5 | 65/181 [09:34<17:01, 8.81s/it]
2/3 0G 1.158 1.074 1.168 341 800: 36%|###5 | 65/181 [09:43<17:01, 8.81s/it]
2/3 0G 1.158 1.074 1.168 341 800: 36%|###6 | 66/181 [09:43<16:57, 8.84s/it]
2/3 0G 1.157 1.073 1.168 339 800: 36%|###6 | 66/181 [09:52<16:57, 8.84s/it]
2/3 0G 1.157 1.073 1.168 339 800: 37%|###7 | 67/181 [09:52<16:44, 8.81s/it]
2/3 0G 1.156 1.071 1.167 334 800: 37%|###7 | 67/181 [10:01<16:44, 8.81s/it]
2/3 0G 1.156 1.071 1.167 334 800: 38%|###7 | 68/181 [10:01<16:38, 8.84s/it]
2/3 0G 1.156 1.07 1.167 322 800: 38%|###7 | 68/181 [10:10<16:38, 8.84s/it]
2/3 0G 1.156 1.07 1.167 322 800: 38%|###8 | 69/181 [10:10<16:28, 8.83s/it]
2/3 0G 1.155 1.069 1.167 253 800: 38%|###8 | 69/181 [10:19<16:28, 8.83s/it]
2/3 0G 1.155 1.069 1.167 253 800: 39%|###8 | 70/181 [10:19<16:21, 8.84s/it]
2/3 0G 1.155 1.068 1.167 275 800: 39%|###8 | 70/181 [10:27<16:21, 8.84s/it]
2/3 0G 1.155 1.068 1.167 275 800: 39%|###9 | 71/181 [10:27<16:10, 8.82s/it]
2/3 0G 1.154 1.066 1.166 329 800: 39%|###9 | 71/181 [10:36<16:10, 8.82s/it]
2/3 0G 1.154 1.066 1.166 329 800: 40%|###9 | 72/181 [10:36<16:02, 8.83s/it]
2/3 0G 1.153 1.065 1.165 299 800: 40%|###9 | 72/181 [10:45<16:02, 8.83s/it]
2/3 0G 1.153 1.065 1.165 299 800: 40%|#### | 73/181 [10:45<15:51, 8.81s/it]
2/3 0G 1.152 1.064 1.165 290 800: 40%|#### | 73/181 [10:54<15:51, 8.81s/it]
2/3 0G 1.152 1.064 1.165 290 800: 41%|#### | 74/181 [10:54<15:46, 8.85s/it]
2/3 0G 1.152 1.061 1.165 317 800: 41%|#### | 74/181 [11:03<15:46, 8.85s/it]
2/3 0G 1.152 1.061 1.165 317 800: 41%|####1 | 75/181 [11:03<15:36, 8.83s/it]
2/3 0G 1.152 1.061 1.165 277 800: 41%|####1 | 75/181 [11:12<15:36, 8.83s/it]
2/3 0G 1.152 1.061 1.165 277 800: 42%|####1 | 76/181 [11:12<15:30, 8.86s/it]
2/3 0G 1.152 1.06 1.165 297 800: 42%|####1 | 76/181 [11:20<15:30, 8.86s/it]
2/3 0G 1.152 1.06 1.165 297 800: 43%|####2 | 77/181 [11:20<15:17, 8.82s/it]
2/3 0G 1.152 1.058 1.165 323 800: 43%|####2 | 77/181 [11:29<15:17, 8.82s/it]
2/3 0G 1.152 1.058 1.165 323 800: 43%|####3 | 78/181 [11:29<15:11, 8.85s/it]
2/3 0G 1.152 1.057 1.164 327 800: 43%|####3 | 78/181 [11:38<15:11, 8.85s/it]
2/3 0G 1.152 1.057 1.164 327 800: 44%|####3 | 79/181 [11:38<14:59, 8.81s/it]
2/3 0G 1.152 1.057 1.164 434 800: 44%|####3 | 79/181 [11:47<14:59, 8.81s/it]
2/3 0G 1.152 1.057 1.164 434 800: 44%|####4 | 80/181 [11:47<14:54, 8.86s/it]
2/3 0G 1.153 1.057 1.164 288 800: 44%|####4 | 80/181 [11:56<14:54, 8.86s/it]
2/3 0G 1.153 1.057 1.164 288 800: 45%|####4 | 81/181 [11:56<14:44, 8.85s/it]
2/3 0G 1.154 1.056 1.165 282 800: 45%|####4 | 81/181 [12:05<14:44, 8.85s/it]
2/3 0G 1.154 1.056 1.165 282 800: 45%|####5 | 82/181 [12:05<14:34, 8.84s/it]
2/3 0G 1.153 1.055 1.165 286 800: 45%|####5 | 82/181 [12:13<14:34, 8.84s/it]
2/3 0G 1.153 1.055 1.165 286 800: 46%|####5 | 83/181 [12:13<14:23, 8.81s/it]
2/3 0G 1.153 1.054 1.165 239 800: 46%|####5 | 83/181 [12:22<14:23, 8.81s/it]
2/3 0G 1.153 1.054 1.165 239 800: 46%|####6 | 84/181 [12:22<14:14, 8.81s/it]
2/3 0G 1.152 1.053 1.165 268 800: 46%|####6 | 84/181 [12:31<14:14, 8.81s/it]
2/3 0G 1.152 1.053 1.165 268 800: 47%|####6 | 85/181 [12:31<14:04, 8.80s/it]
2/3 0G 1.151 1.051 1.164 321 800: 47%|####6 | 85/181 [12:40<14:04, 8.80s/it]
2/3 0G 1.151 1.051 1.164 321 800: 48%|####7 | 86/181 [12:40<13:58, 8.82s/it]
2/3 0G 1.152 1.05 1.165 247 800: 48%|####7 | 86/181 [12:49<13:58, 8.82s/it]
2/3 0G 1.152 1.05 1.165 247 800: 48%|####8 | 87/181 [12:49<13:45, 8.78s/it]
2/3 0G 1.151 1.05 1.165 180 800: 48%|####8 | 87/181 [12:57<13:45, 8.78s/it]
2/3 0G 1.151 1.05 1.165 180 800: 49%|####8 | 88/181 [12:57<13:36, 8.78s/it]
2/3 0G 1.152 1.05 1.166 267 800: 49%|####8 | 88/181 [13:06<13:36, 8.78s/it]
2/3 0G 1.152 1.05 1.166 267 800: 49%|####9 | 89/181 [13:06<13:25, 8.75s/it]
2/3 0G 1.152 1.049 1.166 360 800: 49%|####9 | 89/181 [13:15<13:25, 8.75s/it]
2/3 0G 1.152 1.049 1.166 360 800: 50%|####9 | 90/181 [13:15<13:22, 8.82s/it]
2/3 0G 1.153 1.048 1.166 322 800: 50%|####9 | 90/181 [13:24<13:22, 8.82s/it]
2/3 0G 1.153 1.048 1.166 322 800: 50%|##### | 91/181 [13:24<13:10, 8.78s/it]
2/3 0G 1.152 1.048 1.166 260 800: 50%|##### | 91/181 [13:32<13:10, 8.78s/it]
2/3 0G 1.152 1.048 1.166 260 800: 51%|##### | 92/181 [13:32<13:00, 8.77s/it]
2/3 0G 1.152 1.047 1.165 310 800: 51%|##### | 92/181 [13:41<13:00, 8.77s/it]
2/3 0G 1.152 1.047 1.165 310 800: 51%|#####1 | 93/181 [13:41<12:56, 8.82s/it]
2/3 0G 1.151 1.045 1.165 236 800: 51%|#####1 | 93/181 [13:50<12:56, 8.82s/it]
2/3 0G 1.151 1.045 1.165 236 800: 52%|#####1 | 94/181 [13:50<12:43, 8.77s/it]
2/3 0G 1.151 1.044 1.165 257 800: 52%|#####1 | 94/181 [13:59<12:43, 8.77s/it]
2/3 0G 1.151 1.044 1.165 257 800: 52%|#####2 | 95/181 [13:59<12:33, 8.76s/it]
2/3 0G 1.151 1.044 1.165 368 800: 52%|#####2 | 95/181 [14:08<12:33, 8.76s/it]
2/3 0G 1.151 1.044 1.165 368 800: 53%|#####3 | 96/181 [14:08<12:30, 8.83s/it]
2/3 0G 1.151 1.043 1.165 316 800: 53%|#####3 | 96/181 [14:17<12:30, 8.83s/it]
2/3 0G 1.151 1.043 1.165 316 800: 54%|#####3 | 97/181 [14:17<12:23, 8.85s/it]
2/3 0G 1.151 1.041 1.165 331 800: 54%|#####3 | 97/181 [14:25<12:23, 8.85s/it]
2/3 0G 1.151 1.041 1.165 331 800: 54%|#####4 | 98/181 [14:25<12:12, 8.82s/it]
2/3 0G 1.15 1.04 1.164 321 800: 54%|#####4 | 98/181 [14:34<12:12, 8.82s/it]
2/3 0G 1.15 1.04 1.164 321 800: 55%|#####4 | 99/181 [14:34<12:02, 8.81s/it]
2/3 0G 1.15 1.039 1.164 211 800: 55%|#####4 | 99/181 [14:43<12:02, 8.81s/it]
2/3 0G 1.15 1.039 1.164 211 800: 55%|#####5 | 100/181 [14:43<11:49, 8.77s/it]
2/3 0G 1.149 1.038 1.164 304 800: 55%|#####5 | 100/181 [14:52<11:49, 8.77s/it]
2/3 0G 1.149 1.038 1.164 304 800: 56%|#####5 | 101/181 [14:52<11:42, 8.78s/it]
2/3 0G 1.149 1.037 1.164 286 800: 56%|#####5 | 101/181 [15:01<11:42, 8.78s/it]
2/3 0G 1.149 1.037 1.164 286 800: 56%|#####6 | 102/181 [15:01<11:37, 8.83s/it]
2/3 0G 1.149 1.036 1.164 281 800: 56%|#####6 | 102/181 [15:09<11:37, 8.83s/it]
2/3 0G 1.149 1.036 1.164 281 800: 57%|#####6 | 103/181 [15:09<11:28, 8.83s/it]
2/3 0G 1.148 1.035 1.164 263 800: 57%|#####6 | 103/181 [15:18<11:28, 8.83s/it]
2/3 0G 1.148 1.035 1.164 263 800: 57%|#####7 | 104/181 [15:18<11:20, 8.84s/it]
2/3 0G 1.148 1.033 1.163 300 800: 57%|#####7 | 104/181 [15:27<11:20, 8.84s/it]
2/3 0G 1.148 1.033 1.163 300 800: 58%|#####8 | 105/181 [15:27<11:15, 8.88s/it]
2/3 0G 1.148 1.033 1.163 299 800: 58%|#####8 | 105/181 [15:36<11:15, 8.88s/it]
2/3 0G 1.148 1.033 1.163 299 800: 59%|#####8 | 106/181 [15:36<11:03, 8.84s/it]
2/3 0G 1.148 1.032 1.163 319 800: 59%|#####8 | 106/181 [15:45<11:03, 8.84s/it]
2/3 0G 1.148 1.032 1.163 319 800: 59%|#####9 | 107/181 [15:45<10:54, 8.85s/it]
2/3 0G 1.148 1.031 1.162 402 800: 59%|#####9 | 107/181 [15:54<10:54, 8.85s/it]
2/3 0G 1.148 1.031 1.162 402 800: 60%|#####9 | 108/181 [15:54<10:49, 8.90s/it]
2/3 0G 1.147 1.03 1.162 312 800: 60%|#####9 | 108/181 [16:03<10:49, 8.90s/it]
2/3 0G 1.147 1.03 1.162 312 800: 60%|###### | 109/181 [16:03<10:36, 8.84s/it]
2/3 0G 1.147 1.029 1.162 351 800: 60%|###### | 109/181 [16:11<10:36, 8.84s/it]
2/3 0G 1.147 1.029 1.162 351 800: 61%|###### | 110/181 [16:11<10:27, 8.83s/it]
2/3 0G 1.147 1.029 1.161 303 800: 61%|###### | 110/181 [16:21<10:27, 8.83s/it]
2/3 0G 1.147 1.029 1.161 303 800: 61%|######1 | 111/181 [16:21<10:25, 8.94s/it]
2/3 0G 1.147 1.028 1.161 283 800: 61%|######1 | 111/181 [16:29<10:25, 8.94s/it]
2/3 0G 1.147 1.028 1.161 283 800: 62%|######1 | 112/181 [16:29<10:11, 8.86s/it]
2/3 0G 1.146 1.027 1.161 296 800: 62%|######1 | 112/181 [16:38<10:11, 8.86s/it]
2/3 0G 1.146 1.027 1.161 296 800: 62%|######2 | 113/181 [16:38<09:59, 8.81s/it]
2/3 0G 1.146 1.027 1.161 262 800: 62%|######2 | 113/181 [16:47<09:59, 8.81s/it]
2/3 0G 1.146 1.027 1.161 262 800: 63%|######2 | 114/181 [16:47<09:52, 8.85s/it]
2/3 0G 1.146 1.026 1.161 321 800: 63%|######2 | 114/181 [16:56<09:52, 8.85s/it]
2/3 0G 1.146 1.026 1.161 321 800: 64%|######3 | 115/181 [16:56<09:44, 8.85s/it]
2/3 0G 1.146 1.025 1.161 328 800: 64%|######3 | 115/181 [17:05<09:44, 8.85s/it]
2/3 0G 1.146 1.025 1.161 328 800: 64%|######4 | 116/181 [17:05<09:36, 8.87s/it]
2/3 0G 1.146 1.024 1.161 259 800: 64%|######4 | 116/181 [17:14<09:36, 8.87s/it]
2/3 0G 1.146 1.024 1.161 259 800: 65%|######4 | 117/181 [17:14<09:26, 8.85s/it]
2/3 0G 1.145 1.023 1.161 327 800: 65%|######4 | 117/181 [17:22<09:26, 8.85s/it]
2/3 0G 1.145 1.023 1.161 327 800: 65%|######5 | 118/181 [17:22<09:16, 8.84s/it]
2/3 0G 1.144 1.022 1.16 279 800: 65%|######5 | 118/181 [17:31<09:16, 8.84s/it]
2/3 0G 1.144 1.022 1.16 279 800: 66%|######5 | 119/181 [17:31<09:06, 8.81s/it]
2/3 0G 1.144 1.021 1.16 319 800: 66%|######5 | 119/181 [17:40<09:06, 8.81s/it]
2/3 0G 1.144 1.021 1.16 319 800: 66%|######6 | 120/181 [17:40<08:58, 8.83s/it]
2/3 0G 1.143 1.019 1.159 337 800: 66%|######6 | 120/181 [17:49<08:58, 8.83s/it]
2/3 0G 1.143 1.019 1.159 337 800: 67%|######6 | 121/181 [17:49<08:49, 8.82s/it]
2/3 0G 1.143 1.018 1.159 312 800: 67%|######6 | 121/181 [17:58<08:49, 8.82s/it]
2/3 0G 1.143 1.018 1.159 312 800: 67%|######7 | 122/181 [17:58<08:41, 8.83s/it]
2/3 0G 1.143 1.018 1.159 319 800: 67%|######7 | 122/181 [18:07<08:41, 8.83s/it]
2/3 0G 1.143 1.018 1.159 319 800: 68%|######7 | 123/181 [18:07<08:34, 8.87s/it]
2/3 0G 1.143 1.017 1.159 275 800: 68%|######7 | 123/181 [18:15<08:34, 8.87s/it]
2/3 0G 1.143 1.017 1.159 275 800: 69%|######8 | 124/181 [18:15<08:21, 8.81s/it]
2/3 0G 1.143 1.016 1.159 303 800: 69%|######8 | 124/181 [18:24<08:21, 8.81s/it]
2/3 0G 1.143 1.016 1.159 303 800: 69%|######9 | 125/181 [18:24<08:12, 8.80s/it]
2/3 0G 1.142 1.015 1.158 300 800: 69%|######9 | 125/181 [18:33<08:12, 8.80s/it]
2/3 0G 1.142 1.015 1.158 300 800: 70%|######9 | 126/181 [18:33<08:03, 8.79s/it]
2/3 0G 1.142 1.014 1.158 258 800: 70%|######9 | 126/181 [18:42<08:03, 8.79s/it]
2/3 0G 1.142 1.014 1.158 258 800: 70%|####### | 127/181 [18:42<07:53, 8.77s/it]
2/3 0G 1.142 1.013 1.158 323 800: 70%|####### | 127/181 [18:50<07:53, 8.77s/it]
2/3 0G 1.142 1.013 1.158 323 800: 71%|####### | 128/181 [18:50<07:46, 8.80s/it]
2/3 0G 1.142 1.013 1.158 217 800: 71%|####### | 128/181 [18:59<07:46, 8.80s/it]
2/3 0G 1.142 1.013 1.158 217 800: 71%|#######1 | 129/181 [18:59<07:39, 8.83s/it]
2/3 0G 1.142 1.012 1.158 290 800: 71%|#######1 | 129/181 [19:08<07:39, 8.83s/it]
2/3 0G 1.142 1.012 1.158 290 800: 72%|#######1 | 130/181 [19:08<07:28, 8.79s/it]
2/3 0G 1.141 1.011 1.158 277 800: 72%|#######1 | 130/181 [19:17<07:28, 8.79s/it]
2/3 0G 1.141 1.011 1.158 277 800: 72%|#######2 | 131/181 [19:17<07:19, 8.79s/it]
2/3 0G 1.141 1.011 1.158 266 800: 72%|#######2 | 131/181 [19:26<07:19, 8.79s/it]
2/3 0G 1.141 1.011 1.158 266 800: 73%|#######2 | 132/181 [19:26<07:12, 8.83s/it]
2/3 0G 1.141 1.01 1.158 354 800: 73%|#######2 | 132/181 [19:35<07:12, 8.83s/it]
2/3 0G 1.141 1.01 1.158 354 800: 73%|#######3 | 133/181 [19:35<07:04, 8.84s/it]
2/3 0G 1.14 1.01 1.158 243 800: 73%|#######3 | 133/181 [19:43<07:04, 8.84s/it]
2/3 0G 1.14 1.01 1.158 243 800: 74%|#######4 | 134/181 [19:43<06:54, 8.83s/it]
2/3 0G 1.14 1.009 1.158 279 800: 74%|#######4 | 134/181 [19:52<06:54, 8.83s/it]
2/3 0G 1.14 1.009 1.158 279 800: 75%|#######4 | 135/181 [19:52<06:46, 8.85s/it]
2/3 0G 1.141 1.009 1.158 318 800: 75%|#######4 | 135/181 [20:01<06:46, 8.85s/it]
2/3 0G 1.141 1.009 1.158 318 800: 75%|#######5 | 136/181 [20:01<06:36, 8.81s/it]
2/3 0G 1.141 1.008 1.158 288 800: 75%|#######5 | 136/181 [20:10<06:36, 8.81s/it]
2/3 0G 1.141 1.008 1.158 288 800: 76%|#######5 | 137/181 [20:10<06:28, 8.82s/it]
2/3 0G 1.14 1.007 1.157 292 800: 76%|#######5 | 137/181 [20:19<06:28, 8.82s/it]
2/3 0G 1.14 1.007 1.157 292 800: 76%|#######6 | 138/181 [20:19<06:20, 8.85s/it]
2/3 0G 1.14 1.007 1.158 196 800: 76%|#######6 | 138/181 [20:27<06:20, 8.85s/it]
2/3 0G 1.14 1.007 1.158 196 800: 77%|#######6 | 139/181 [20:27<06:08, 8.77s/it]
2/3 0G 1.14 1.006 1.157 295 800: 77%|#######6 | 139/181 [20:36<06:08, 8.77s/it]
2/3 0G 1.14 1.006 1.157 295 800: 77%|#######7 | 140/181 [20:36<06:00, 8.78s/it]
2/3 0G 1.139 1.005 1.157 388 800: 77%|#######7 | 140/181 [20:45<06:00, 8.78s/it]
2/3 0G 1.139 1.005 1.157 388 800: 78%|#######7 | 141/181 [20:45<05:52, 8.82s/it]
2/3 0G 1.138 1.004 1.156 292 800: 78%|#######7 | 141/181 [20:54<05:52, 8.82s/it]
2/3 0G 1.138 1.004 1.156 292 800: 78%|#######8 | 142/181 [20:54<05:42, 8.79s/it]
2/3 0G 1.138 1.003 1.156 319 800: 78%|#######8 | 142/181 [21:03<05:42, 8.79s/it]
2/3 0G 1.138 1.003 1.156 319 800: 79%|#######9 | 143/181 [21:03<05:33, 8.78s/it]
2/3 0G 1.137 1.002 1.156 239 800: 79%|#######9 | 143/181 [21:11<05:33, 8.78s/it]
2/3 0G 1.137 1.002 1.156 239 800: 80%|#######9 | 144/181 [21:11<05:26, 8.83s/it]
2/3 0G 1.137 1.001 1.156 296 800: 80%|#######9 | 144/181 [21:20<05:26, 8.83s/it]
2/3 0G 1.137 1.001 1.156 296 800: 80%|######## | 145/181 [21:20<05:18, 8.84s/it]
2/3 0G 1.137 1.001 1.156 339 800: 80%|######## | 145/181 [21:29<05:18, 8.84s/it]
2/3 0G 1.137 1.001 1.156 339 800: 81%|######## | 146/181 [21:29<05:09, 8.84s/it]
2/3 0G 1.137 0.9998 1.156 299 800: 81%|######## | 146/181 [21:38<05:09, 8.84s/it]
2/3 0G 1.137 0.9998 1.156 299 800: 81%|########1 | 147/181 [21:38<05:00, 8.85s/it]
2/3 0G 1.137 0.9989 1.155 283 800: 81%|########1 | 147/181 [21:47<05:00, 8.85s/it]
2/3 0G 1.137 0.9989 1.155 283 800: 82%|########1 | 148/181 [21:47<04:50, 8.80s/it]
2/3 0G 1.136 0.998 1.155 259 800: 82%|########1 | 148/181 [21:56<04:50, 8.80s/it]
2/3 0G 1.136 0.998 1.155 259 800: 82%|########2 | 149/181 [21:56<04:41, 8.80s/it]
2/3 0G 1.136 0.9973 1.155 267 800: 82%|########2 | 149/181 [22:04<04:41, 8.80s/it]
2/3 0G 1.136 0.9973 1.155 267 800: 83%|########2 | 150/181 [22:04<04:32, 8.80s/it]
2/3 0G 1.135 0.9968 1.155 251 800: 83%|########2 | 150/181 [22:13<04:32, 8.80s/it]
2/3 0G 1.135 0.9968 1.155 251 800: 83%|########3 | 151/181 [22:13<04:23, 8.79s/it]
2/3 0G 1.135 0.9961 1.155 312 800: 83%|########3 | 151/181 [22:22<04:23, 8.79s/it]
2/3 0G 1.135 0.9961 1.155 312 800: 84%|########3 | 152/181 [22:22<04:15, 8.80s/it]
2/3 0G 1.135 0.9953 1.154 302 800: 84%|########3 | 152/181 [22:31<04:15, 8.80s/it]
2/3 0G 1.135 0.9953 1.154 302 800: 85%|########4 | 153/181 [22:31<04:07, 8.83s/it]
2/3 0G 1.135 0.9954 1.154 364 800: 85%|########4 | 153/181 [22:40<04:07, 8.83s/it]
2/3 0G 1.135 0.9954 1.154 364 800: 85%|########5 | 154/181 [22:40<03:57, 8.80s/it]
2/3 0G 1.134 0.9947 1.154 314 800: 85%|########5 | 154/181 [22:48<03:57, 8.80s/it]
2/3 0G 1.134 0.9947 1.154 314 800: 86%|########5 | 155/181 [22:48<03:48, 8.80s/it]
2/3 0G 1.134 0.994 1.153 322 800: 86%|########5 | 155/181 [22:57<03:48, 8.80s/it]
2/3 0G 1.134 0.994 1.153 322 800: 86%|########6 | 156/181 [22:57<03:41, 8.85s/it]
2/3 0G 1.133 0.9932 1.153 245 800: 86%|########6 | 156/181 [23:06<03:41, 8.85s/it]
2/3 0G 1.133 0.9932 1.153 245 800: 87%|########6 | 157/181 [23:06<03:31, 8.79s/it]
2/3 0G 1.133 0.9922 1.153 264 800: 87%|########6 | 157/181 [23:15<03:31, 8.79s/it]
2/3 0G 1.133 0.9922 1.153 264 800: 87%|########7 | 158/181 [23:15<03:21, 8.78s/it]
2/3 0G 1.132 0.9913 1.153 318 800: 87%|########7 | 158/181 [23:24<03:21, 8.78s/it]
2/3 0G 1.132 0.9913 1.153 318 800: 88%|########7 | 159/181 [23:24<03:14, 8.83s/it]
2/3 0G 1.132 0.9907 1.153 246 800: 88%|########7 | 159/181 [23:32<03:14, 8.83s/it]
2/3 0G 1.132 0.9907 1.153 246 800: 88%|########8 | 160/181 [23:32<03:04, 8.80s/it]
2/3 0G 1.132 0.9901 1.153 334 800: 88%|########8 | 160/181 [23:41<03:04, 8.80s/it]
2/3 0G 1.132 0.9901 1.153 334 800: 89%|########8 | 161/181 [23:41<02:56, 8.82s/it]
2/3 0G 1.132 0.9893 1.153 226 800: 89%|########8 | 161/181 [23:50<02:56, 8.82s/it]
2/3 0G 1.132 0.9893 1.153 226 800: 90%|########9 | 162/181 [23:50<02:48, 8.88s/it]
2/3 0G 1.132 0.9886 1.153 304 800: 90%|########9 | 162/181 [23:59<02:48, 8.88s/it]
2/3 0G 1.132 0.9886 1.153 304 800: 90%|######### | 163/181 [23:59<02:39, 8.86s/it]
2/3 0G 1.132 0.9878 1.153 375 800: 90%|######### | 163/181 [24:08<02:39, 8.86s/it]
2/3 0G 1.132 0.9878 1.153 375 800: 91%|######### | 164/181 [24:08<02:30, 8.87s/it]
2/3 0G 1.132 0.9873 1.152 318 800: 91%|######### | 164/181 [24:17<02:30, 8.87s/it]
2/3 0G 1.132 0.9873 1.152 318 800: 91%|#########1| 165/181 [24:17<02:21, 8.87s/it]
2/3 0G 1.132 0.9866 1.152 398 800: 91%|#########1| 165/181 [24:26<02:21, 8.87s/it]
2/3 0G 1.132 0.9866 1.152 398 800: 92%|#########1| 166/181 [24:26<02:12, 8.83s/it]
2/3 0G 1.132 0.9861 1.152 236 800: 92%|#########1| 166/181 [24:34<02:12, 8.83s/it]
2/3 0G 1.132 0.9861 1.152 236 800: 92%|#########2| 167/181 [24:34<02:03, 8.81s/it]
2/3 0G 1.132 0.9854 1.152 260 800: 92%|#########2| 167/181 [24:43<02:03, 8.81s/it]
2/3 0G 1.132 0.9854 1.152 260 800: 93%|#########2| 168/181 [24:43<01:54, 8.83s/it]
2/3 0G 1.131 0.984 1.152 279 800: 93%|#########2| 168/181 [24:52<01:54, 8.83s/it]
2/3 0G 1.131 0.984 1.152 279 800: 93%|#########3| 169/181 [24:52<01:45, 8.83s/it]
2/3 0G 1.131 0.9828 1.152 289 800: 93%|#########3| 169/181 [25:01<01:45, 8.83s/it]
2/3 0G 1.131 0.9828 1.152 289 800: 94%|#########3| 170/181 [25:01<01:37, 8.82s/it]
2/3 0G 1.131 0.9819 1.151 328 800: 94%|#########3| 170/181 [25:10<01:37, 8.82s/it]
2/3 0G 1.131 0.9819 1.151 328 800: 94%|#########4| 171/181 [25:10<01:28, 8.85s/it]
2/3 0G 1.131 0.9812 1.151 257 800: 94%|#########4| 171/181 [25:18<01:28, 8.85s/it]
2/3 0G 1.131 0.9812 1.151 257 800: 95%|#########5| 172/181 [25:18<01:19, 8.81s/it]
2/3 0G 1.13 0.9804 1.151 344 800: 95%|#########5| 172/181 [25:27<01:19, 8.81s/it]
2/3 0G 1.13 0.9804 1.151 344 800: 96%|#########5| 173/181 [25:27<01:10, 8.83s/it]
2/3 0G 1.13 0.9798 1.15 386 800: 96%|#########5| 173/181 [25:36<01:10, 8.83s/it]
2/3 0G 1.13 0.9798 1.15 386 800: 96%|#########6| 174/181 [25:36<01:02, 8.89s/it]
2/3 0G 1.13 0.979 1.15 307 800: 96%|#########6| 174/181 [25:45<01:02, 8.89s/it]
2/3 0G 1.13 0.979 1.15 307 800: 97%|#########6| 175/181 [25:45<00:53, 8.85s/it]
2/3 0G 1.129 0.9782 1.15 298 800: 97%|#########6| 175/181 [25:54<00:53, 8.85s/it]
2/3 0G 1.129 0.9782 1.15 298 800: 97%|#########7| 176/181 [25:54<00:44, 8.83s/it]
2/3 0G 1.129 0.9772 1.15 292 800: 97%|#########7| 176/181 [26:03<00:44, 8.83s/it]
2/3 0G 1.129 0.9772 1.15 292 800: 98%|#########7| 177/181 [26:03<00:35, 8.84s/it]
2/3 0G 1.129 0.9769 1.15 332 800: 98%|#########7| 177/181 [26:12<00:35, 8.84s/it]
2/3 0G 1.129 0.9769 1.15 332 800: 98%|#########8| 178/181 [26:12<00:26, 8.82s/it]
2/3 0G 1.129 0.976 1.15 298 800: 98%|#########8| 178/181 [26:20<00:26, 8.82s/it]
2/3 0G 1.129 0.976 1.15 298 800: 99%|#########8| 179/181 [26:20<00:17, 8.79s/it]
2/3 0G 1.129 0.9752 1.15 270 800: 99%|#########8| 179/181 [26:29<00:17, 8.79s/it]
2/3 0G 1.129 0.9752 1.15 270 800: 99%|#########9| 180/181 [26:29<00:08, 8.87s/it]
2/3 0G 1.128 0.974 1.149 336 800: 99%|#########9| 180/181 [26:38<00:08, 8.87s/it]
2/3 0G 1.128 0.974 1.149 336 800: 100%|##########| 181/181 [26:38<00:00, 8.82s/it]
2/3 0G 1.128 0.974 1.149 336 800: 100%|##########| 181/181 [26:38<00:00, 8.83s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 0%| | 0/4 [00:00<?, ?it/s]
Class Images Instances Box(P R mAP50 mAP50-95): 25%|##5 | 1/4 [00:06<00:20, 6.91s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 50%|##### | 2/4 [00:13<00:13, 6.87s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 75%|#######5 | 3/4 [00:20<00:06, 6.87s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 100%|##########| 4/4 [00:21<00:00, 4.68s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 100%|##########| 4/4 [00:21<00:00, 5.49s/it]
0%| | 0/181 [00:00<?, ?it/s]
3/3 0G 1.071 0.8168 1.087 309 800: 0%| | 0/181 [00:08<?, ?it/s]
3/3 0G 1.071 0.8168 1.087 309 800: 1%| | 1/181 [00:08<26:06, 8.70s/it]
3/3 0G 1.125 0.8645 1.14 283 800: 1%| | 1/181 [00:17<26:06, 8.70s/it]
3/3 0G 1.125 0.8645 1.14 283 800: 1%|1 | 2/181 [00:17<26:33, 8.90s/it]
3/3 0G 1.129 0.8709 1.138 310 800: 1%|1 | 2/181 [00:26<26:33, 8.90s/it]
3/3 0G 1.129 0.8709 1.138 310 800: 2%|1 | 3/181 [00:26<26:13, 8.84s/it]
3/3 0G 1.121 0.8523 1.135 262 800: 2%|1 | 3/181 [00:35<26:13, 8.84s/it]
3/3 0G 1.121 0.8523 1.135 262 800: 2%|2 | 4/181 [00:35<26:01, 8.82s/it]
3/3 0G 1.128 0.8558 1.14 281 800: 2%|2 | 4/181 [00:44<26:01, 8.82s/it]
3/3 0G 1.128 0.8558 1.14 281 800: 3%|2 | 5/181 [00:44<26:01, 8.87s/it]
3/3 0G 1.107 0.8455 1.135 232 800: 3%|2 | 5/181 [00:52<26:01, 8.87s/it]
3/3 0G 1.107 0.8455 1.135 232 800: 3%|3 | 6/181 [00:52<25:41, 8.81s/it]
3/3 0G 1.104 0.8418 1.132 336 800: 3%|3 | 6/181 [01:01<25:41, 8.81s/it]
3/3 0G 1.104 0.8418 1.132 336 800: 4%|3 | 7/181 [01:01<25:33, 8.81s/it]
3/3 0G 1.106 0.8387 1.133 244 800: 4%|3 | 7/181 [01:10<25:33, 8.81s/it]
3/3 0G 1.106 0.8387 1.133 244 800: 4%|4 | 8/181 [01:10<25:34, 8.87s/it]
3/3 0G 1.097 0.8267 1.131 296 800: 4%|4 | 8/181 [01:19<25:34, 8.87s/it]
3/3 0G 1.097 0.8267 1.131 296 800: 5%|4 | 9/181 [01:19<25:19, 8.83s/it]
3/3 0G 1.095 0.8291 1.127 263 800: 5%|4 | 9/181 [01:28<25:19, 8.83s/it]
3/3 0G 1.095 0.8291 1.127 263 800: 6%|5 | 10/181 [01:28<25:14, 8.86s/it]
3/3 0G 1.093 0.827 1.124 337 800: 6%|5 | 10/181 [01:37<25:14, 8.86s/it]
3/3 0G 1.093 0.827 1.124 337 800: 6%|6 | 11/181 [01:37<25:08, 8.88s/it]
3/3 0G 1.094 0.8285 1.123 271 800: 6%|6 | 11/181 [01:46<25:08, 8.88s/it]
3/3 0G 1.094 0.8285 1.123 271 800: 7%|6 | 12/181 [01:46<24:55, 8.85s/it]
3/3 0G 1.092 0.8302 1.123 312 800: 7%|6 | 12/181 [01:54<24:55, 8.85s/it]
3/3 0G 1.092 0.8302 1.123 312 800: 7%|7 | 13/181 [01:54<24:46, 8.85s/it]
3/3 0G 1.097 0.8345 1.129 260 800: 7%|7 | 13/181 [02:03<24:46, 8.85s/it]
3/3 0G 1.097 0.8345 1.129 260 800: 8%|7 | 14/181 [02:03<24:36, 8.84s/it]
3/3 0G 1.094 0.8303 1.127 313 800: 8%|7 | 14/181 [02:12<24:36, 8.84s/it]
3/3 0G 1.094 0.8303 1.127 313 800: 8%|8 | 15/181 [02:12<24:23, 8.82s/it]
3/3 0G 1.09 0.8264 1.126 281 800: 8%|8 | 15/181 [02:21<24:23, 8.82s/it]
3/3 0G 1.09 0.8264 1.126 281 800: 9%|8 | 16/181 [02:21<24:19, 8.84s/it]
3/3 0G 1.089 0.8286 1.123 436 800: 9%|8 | 16/181 [02:30<24:19, 8.84s/it]
3/3 0G 1.089 0.8286 1.123 436 800: 9%|9 | 17/181 [02:30<24:15, 8.87s/it]
3/3 0G 1.091 0.8286 1.124 376 800: 9%|9 | 17/181 [02:39<24:15, 8.87s/it]
3/3 0G 1.091 0.8286 1.124 376 800: 10%|9 | 18/181 [02:39<24:04, 8.86s/it]
3/3 0G 1.089 0.8265 1.125 249 800: 10%|9 | 18/181 [02:48<24:04, 8.86s/it]
3/3 0G 1.089 0.8265 1.125 249 800: 10%|# | 19/181 [02:48<23:52, 8.84s/it]
3/3 0G 1.088 0.8229 1.124 257 800: 10%|# | 19/181 [02:57<23:52, 8.84s/it]
3/3 0G 1.088 0.8229 1.124 257 800: 11%|#1 | 20/181 [02:57<23:53, 8.90s/it]
3/3 0G 1.088 0.8228 1.124 299 800: 11%|#1 | 20/181 [03:05<23:53, 8.90s/it]
3/3 0G 1.088 0.8228 1.124 299 800: 12%|#1 | 21/181 [03:05<23:42, 8.89s/it]
3/3 0G 1.088 0.8242 1.126 267 800: 12%|#1 | 21/181 [03:14<23:42, 8.89s/it]
3/3 0G 1.088 0.8242 1.126 267 800: 12%|#2 | 22/181 [03:14<23:26, 8.85s/it]
3/3 0G 1.086 0.8234 1.127 244 800: 12%|#2 | 22/181 [03:23<23:26, 8.85s/it]
3/3 0G 1.086 0.8234 1.127 244 800: 13%|#2 | 23/181 [03:23<23:19, 8.86s/it]
3/3 0G 1.085 0.8223 1.127 286 800: 13%|#2 | 23/181 [03:32<23:19, 8.86s/it]
3/3 0G 1.085 0.8223 1.127 286 800: 13%|#3 | 24/181 [03:32<23:09, 8.85s/it]
3/3 0G 1.084 0.8207 1.126 321 800: 13%|#3 | 24/181 [03:41<23:09, 8.85s/it]
3/3 0G 1.084 0.8207 1.126 321 800: 14%|#3 | 25/181 [03:41<23:00, 8.85s/it]
3/3 0G 1.083 0.8218 1.125 316 800: 14%|#3 | 25/181 [03:50<23:00, 8.85s/it]
3/3 0G 1.083 0.8218 1.125 316 800: 14%|#4 | 26/181 [03:50<22:57, 8.89s/it]
3/3 0G 1.082 0.823 1.125 281 800: 14%|#4 | 26/181 [03:58<22:57, 8.89s/it]
3/3 0G 1.082 0.823 1.125 281 800: 15%|#4 | 27/181 [03:58<22:40, 8.84s/it]
3/3 0G 1.079 0.8208 1.124 235 800: 15%|#4 | 27/181 [04:07<22:40, 8.84s/it]
3/3 0G 1.079 0.8208 1.124 235 800: 15%|#5 | 28/181 [04:07<22:35, 8.86s/it]
3/3 0G 1.081 0.8214 1.124 322 800: 15%|#5 | 28/181 [04:16<22:35, 8.86s/it]
3/3 0G 1.081 0.8214 1.124 322 800: 16%|#6 | 29/181 [04:16<22:27, 8.86s/it]
3/3 0G 1.079 0.8195 1.122 307 800: 16%|#6 | 29/181 [04:25<22:27, 8.86s/it]
3/3 0G 1.079 0.8195 1.122 307 800: 17%|#6 | 30/181 [04:25<22:13, 8.83s/it]
3/3 0G 1.079 0.8193 1.123 274 800: 17%|#6 | 30/181 [04:34<22:13, 8.83s/it]
3/3 0G 1.079 0.8193 1.123 274 800: 17%|#7 | 31/181 [04:34<22:02, 8.81s/it]
3/3 0G 1.079 0.8204 1.124 205 800: 17%|#7 | 31/181 [04:43<22:02, 8.81s/it]
3/3 0G 1.079 0.8204 1.124 205 800: 18%|#7 | 32/181 [04:43<21:58, 8.85s/it]
3/3 0G 1.077 0.8198 1.123 194 800: 18%|#7 | 32/181 [04:51<21:58, 8.85s/it]
3/3 0G 1.077 0.8198 1.123 194 800: 18%|#8 | 33/181 [04:51<21:40, 8.79s/it]
3/3 0G 1.076 0.8184 1.122 322 800: 18%|#8 | 33/181 [05:00<21:40, 8.79s/it]
3/3 0G 1.076 0.8184 1.122 322 800: 19%|#8 | 34/181 [05:00<21:29, 8.77s/it]
3/3 0G 1.076 0.8176 1.123 262 800: 19%|#8 | 34/181 [05:09<21:29, 8.77s/it]
3/3 0G 1.076 0.8176 1.123 262 800: 19%|#9 | 35/181 [05:09<21:21, 8.78s/it]
3/3 0G 1.077 0.8166 1.122 375 800: 19%|#9 | 35/181 [05:18<21:21, 8.78s/it]
3/3 0G 1.077 0.8166 1.122 375 800: 20%|#9 | 36/181 [05:18<21:10, 8.76s/it]
3/3 0G 1.076 0.8179 1.123 264 800: 20%|#9 | 36/181 [05:26<21:10, 8.76s/it]
3/3 0G 1.076 0.8179 1.123 264 800: 20%|## | 37/181 [05:26<21:06, 8.80s/it]
3/3 0G 1.076 0.8175 1.124 223 800: 20%|## | 37/181 [05:35<21:06, 8.80s/it]
3/3 0G 1.076 0.8175 1.124 223 800: 21%|## | 38/181 [05:35<21:02, 8.83s/it]
3/3 0G 1.076 0.8177 1.124 275 800: 21%|## | 38/181 [05:44<21:02, 8.83s/it]
3/3 0G 1.076 0.8177 1.124 275 800: 22%|##1 | 39/181 [05:44<20:48, 8.80s/it]
3/3 0G 1.078 0.8179 1.125 324 800: 22%|##1 | 39/181 [05:53<20:48, 8.80s/it]
3/3 0G 1.078 0.8179 1.125 324 800: 22%|##2 | 40/181 [05:53<20:41, 8.81s/it]
3/3 0G 1.077 0.8163 1.125 318 800: 22%|##2 | 40/181 [06:02<20:41, 8.81s/it]
3/3 0G 1.077 0.8163 1.125 318 800: 23%|##2 | 41/181 [06:02<20:34, 8.82s/it]
3/3 0G 1.077 0.8145 1.124 310 800: 23%|##2 | 41/181 [06:11<20:34, 8.82s/it]
3/3 0G 1.077 0.8145 1.124 310 800: 23%|##3 | 42/181 [06:11<20:21, 8.79s/it]
3/3 0G 1.076 0.8132 1.123 318 800: 23%|##3 | 42/181 [06:19<20:21, 8.79s/it]
3/3 0G 1.076 0.8132 1.123 318 800: 24%|##3 | 43/181 [06:19<20:11, 8.78s/it]
3/3 0G 1.076 0.8141 1.123 322 800: 24%|##3 | 43/181 [06:28<20:11, 8.78s/it]
3/3 0G 1.076 0.8141 1.123 322 800: 24%|##4 | 44/181 [06:28<20:09, 8.83s/it]
3/3 0G 1.076 0.8134 1.123 287 800: 24%|##4 | 44/181 [06:37<20:09, 8.83s/it]
3/3 0G 1.076 0.8134 1.123 287 800: 25%|##4 | 45/181 [06:37<20:03, 8.85s/it]
3/3 0G 1.076 0.8134 1.122 326 800: 25%|##4 | 45/181 [06:46<20:03, 8.85s/it]
3/3 0G 1.076 0.8134 1.122 326 800: 25%|##5 | 46/181 [06:46<19:58, 8.88s/it]
3/3 0G 1.075 0.8136 1.122 304 800: 25%|##5 | 46/181 [06:55<19:58, 8.88s/it]
3/3 0G 1.075 0.8136 1.122 304 800: 26%|##5 | 47/181 [06:55<19:49, 8.87s/it]
3/3 0G 1.074 0.8128 1.121 295 800: 26%|##5 | 47/181 [07:04<19:49, 8.87s/it]
3/3 0G 1.074 0.8128 1.121 295 800: 27%|##6 | 48/181 [07:04<19:32, 8.82s/it]
3/3 0G 1.072 0.8107 1.121 253 800: 27%|##6 | 48/181 [07:12<19:32, 8.82s/it]
3/3 0G 1.072 0.8107 1.121 253 800: 27%|##7 | 49/181 [07:12<19:21, 8.80s/it]
3/3 0G 1.071 0.8088 1.12 331 800: 27%|##7 | 49/181 [07:21<19:21, 8.80s/it]
3/3 0G 1.071 0.8088 1.12 331 800: 28%|##7 | 50/181 [07:21<19:16, 8.83s/it]
3/3 0G 1.07 0.8081 1.12 256 800: 28%|##7 | 50/181 [07:30<19:16, 8.83s/it]
3/3 0G 1.07 0.8081 1.12 256 800: 28%|##8 | 51/181 [07:30<19:08, 8.83s/it]
3/3 0G 1.069 0.8088 1.12 345 800: 28%|##8 | 51/181 [07:39<19:08, 8.83s/it]
3/3 0G 1.069 0.8088 1.12 345 800: 29%|##8 | 52/181 [07:39<18:57, 8.82s/it]
3/3 0G 1.069 0.8078 1.12 207 800: 29%|##8 | 52/181 [07:48<18:57, 8.82s/it]
3/3 0G 1.069 0.8078 1.12 207 800: 29%|##9 | 53/181 [07:48<18:47, 8.81s/it]
3/3 0G 1.068 0.8072 1.12 339 800: 29%|##9 | 53/181 [07:56<18:47, 8.81s/it]
3/3 0G 1.068 0.8072 1.12 339 800: 30%|##9 | 54/181 [07:56<18:35, 8.78s/it]
3/3 0G 1.068 0.8065 1.12 309 800: 30%|##9 | 54/181 [08:05<18:35, 8.78s/it]
3/3 0G 1.068 0.8065 1.12 309 800: 30%|### | 55/181 [08:05<18:27, 8.79s/it]
3/3 0G 1.068 0.8057 1.119 317 800: 30%|### | 55/181 [08:14<18:27, 8.79s/it]
3/3 0G 1.068 0.8057 1.119 317 800: 31%|### | 56/181 [08:14<18:24, 8.84s/it]
3/3 0G 1.067 0.8055 1.119 244 800: 31%|### | 56/181 [08:23<18:24, 8.84s/it]
3/3 0G 1.067 0.8055 1.119 244 800: 31%|###1 | 57/181 [08:23<18:13, 8.82s/it]
3/3 0G 1.067 0.8045 1.119 301 800: 31%|###1 | 57/181 [08:32<18:13, 8.82s/it]
3/3 0G 1.067 0.8045 1.119 301 800: 32%|###2 | 58/181 [08:32<18:03, 8.81s/it]
3/3 0G 1.067 0.8042 1.118 331 800: 32%|###2 | 58/181 [08:41<18:03, 8.81s/it]
3/3 0G 1.067 0.8042 1.118 331 800: 33%|###2 | 59/181 [08:41<18:00, 8.86s/it]
3/3 0G 1.065 0.8033 1.117 359 800: 33%|###2 | 59/181 [08:49<18:00, 8.86s/it]
3/3 0G 1.065 0.8033 1.117 359 800: 33%|###3 | 60/181 [08:49<17:46, 8.81s/it]
3/3 0G 1.064 0.8049 1.118 250 800: 33%|###3 | 60/181 [08:58<17:46, 8.81s/it]
3/3 0G 1.064 0.8049 1.118 250 800: 34%|###3 | 61/181 [08:58<17:35, 8.80s/it]
3/3 0G 1.065 0.8054 1.117 325 800: 34%|###3 | 61/181 [09:07<17:35, 8.80s/it]
3/3 0G 1.065 0.8054 1.117 325 800: 34%|###4 | 62/181 [09:07<17:32, 8.85s/it]
3/3 0G 1.065 0.8047 1.117 292 800: 34%|###4 | 62/181 [09:16<17:32, 8.85s/it]
3/3 0G 1.065 0.8047 1.117 292 800: 35%|###4 | 63/181 [09:16<17:24, 8.85s/it]
3/3 0G 1.064 0.8049 1.117 250 800: 35%|###4 | 63/181 [09:25<17:24, 8.85s/it]
3/3 0G 1.064 0.8049 1.117 250 800: 35%|###5 | 64/181 [09:25<17:13, 8.83s/it]
3/3 0G 1.064 0.8046 1.117 238 800: 35%|###5 | 64/181 [09:34<17:13, 8.83s/it]
3/3 0G 1.064 0.8046 1.117 238 800: 36%|###5 | 65/181 [09:34<17:01, 8.81s/it]
3/3 0G 1.063 0.8039 1.117 298 800: 36%|###5 | 65/181 [09:42<17:01, 8.81s/it]
3/3 0G 1.063 0.8039 1.117 298 800: 36%|###6 | 66/181 [09:42<16:50, 8.78s/it]
3/3 0G 1.063 0.8036 1.117 254 800: 36%|###6 | 66/181 [09:51<16:50, 8.78s/it]
3/3 0G 1.063 0.8036 1.117 254 800: 37%|###7 | 67/181 [09:51<16:37, 8.75s/it]
3/3 0G 1.064 0.8038 1.117 340 800: 37%|###7 | 67/181 [10:00<16:37, 8.75s/it]
3/3 0G 1.064 0.8038 1.117 340 800: 38%|###7 | 68/181 [10:00<16:37, 8.83s/it]
3/3 0G 1.063 0.8029 1.117 267 800: 38%|###7 | 68/181 [10:09<16:37, 8.83s/it]
3/3 0G 1.063 0.8029 1.117 267 800: 38%|###8 | 69/181 [10:09<16:28, 8.83s/it]
3/3 0G 1.063 0.8026 1.116 410 800: 38%|###8 | 69/181 [10:18<16:28, 8.83s/it]
3/3 0G 1.063 0.8026 1.116 410 800: 39%|###8 | 70/181 [10:18<16:21, 8.84s/it]
3/3 0G 1.063 0.8022 1.115 312 800: 39%|###8 | 70/181 [10:26<16:21, 8.84s/it]
3/3 0G 1.063 0.8022 1.115 312 800: 39%|###9 | 71/181 [10:26<16:12, 8.84s/it]
3/3 0G 1.063 0.8023 1.116 240 800: 39%|###9 | 71/181 [10:35<16:12, 8.84s/it]
3/3 0G 1.063 0.8023 1.116 240 800: 40%|###9 | 72/181 [10:35<16:01, 8.82s/it]
3/3 0G 1.063 0.8022 1.117 296 800: 40%|###9 | 72/181 [10:44<16:01, 8.82s/it]
3/3 0G 1.063 0.8022 1.117 296 800: 40%|#### | 73/181 [10:44<15:51, 8.81s/it]
3/3 0G 1.063 0.8015 1.116 353 800: 40%|#### | 73/181 [10:53<15:51, 8.81s/it]
3/3 0G 1.063 0.8015 1.116 353 800: 41%|#### | 74/181 [10:53<15:51, 8.89s/it]
3/3 0G 1.062 0.8014 1.116 324 800: 41%|#### | 74/181 [11:02<15:51, 8.89s/it]
3/3 0G 1.062 0.8014 1.116 324 800: 41%|####1 | 75/181 [11:02<15:38, 8.86s/it]
3/3 0G 1.062 0.8011 1.116 323 800: 41%|####1 | 75/181 [11:11<15:38, 8.86s/it]
3/3 0G 1.062 0.8011 1.116 323 800: 42%|####1 | 76/181 [11:11<15:30, 8.86s/it]
3/3 0G 1.061 0.8 1.115 348 800: 42%|####1 | 76/181 [11:20<15:30, 8.86s/it]
3/3 0G 1.061 0.8 1.115 348 800: 43%|####2 | 77/181 [11:20<15:21, 8.86s/it]
3/3 0G 1.062 0.7999 1.115 344 800: 43%|####2 | 77/181 [11:28<15:21, 8.86s/it]
3/3 0G 1.062 0.7999 1.115 344 800: 43%|####3 | 78/181 [11:28<15:09, 8.83s/it]
3/3 0G 1.062 0.7998 1.115 266 800: 43%|####3 | 78/181 [11:37<15:09, 8.83s/it]
3/3 0G 1.062 0.7998 1.115 266 800: 44%|####3 | 79/181 [11:37<14:57, 8.80s/it]
3/3 0G 1.062 0.7993 1.115 347 800: 44%|####3 | 79/181 [11:46<14:57, 8.80s/it]
3/3 0G 1.062 0.7993 1.115 347 800: 44%|####4 | 80/181 [11:46<14:59, 8.90s/it]
3/3 0G 1.063 0.7993 1.115 301 800: 44%|####4 | 80/181 [11:55<14:59, 8.90s/it]
3/3 0G 1.063 0.7993 1.115 301 800: 45%|####4 | 81/181 [11:55<14:51, 8.92s/it]
3/3 0G 1.062 0.7995 1.116 262 800: 45%|####4 | 81/181 [12:04<14:51, 8.92s/it]
3/3 0G 1.062 0.7995 1.116 262 800: 45%|####5 | 82/181 [12:04<14:41, 8.91s/it]
3/3 0G 1.062 0.7985 1.115 317 800: 45%|####5 | 82/181 [12:13<14:41, 8.91s/it]
3/3 0G 1.062 0.7985 1.115 317 800: 46%|####5 | 83/181 [12:13<14:31, 8.90s/it]
3/3 0G 1.062 0.7984 1.115 239 800: 46%|####5 | 83/181 [12:22<14:31, 8.90s/it]
3/3 0G 1.062 0.7984 1.115 239 800: 46%|####6 | 84/181 [12:22<14:16, 8.83s/it]
3/3 0G 1.061 0.7983 1.116 183 800: 46%|####6 | 84/181 [12:30<14:16, 8.83s/it]
3/3 0G 1.061 0.7983 1.116 183 800: 47%|####6 | 85/181 [12:30<14:04, 8.80s/it]
3/3 0G 1.062 0.7985 1.116 259 800: 47%|####6 | 85/181 [12:39<14:04, 8.80s/it]
3/3 0G 1.062 0.7985 1.116 259 800: 48%|####7 | 86/181 [12:39<13:58, 8.83s/it]
3/3 0G 1.061 0.7976 1.115 296 800: 48%|####7 | 86/181 [12:48<13:58, 8.83s/it]
3/3 0G 1.061 0.7976 1.115 296 800: 48%|####8 | 87/181 [12:48<13:49, 8.83s/it]
3/3 0G 1.059 0.7966 1.114 356 800: 48%|####8 | 87/181 [12:57<13:49, 8.83s/it]
3/3 0G 1.059 0.7966 1.114 356 800: 49%|####8 | 88/181 [12:57<13:42, 8.85s/it]
3/3 0G 1.059 0.7964 1.114 307 800: 49%|####8 | 88/181 [13:06<13:42, 8.85s/it]
3/3 0G 1.059 0.7964 1.114 307 800: 49%|####9 | 89/181 [13:06<13:32, 8.83s/it]
3/3 0G 1.058 0.7964 1.113 247 800: 49%|####9 | 89/181 [13:15<13:32, 8.83s/it]
3/3 0G 1.058 0.7964 1.113 247 800: 50%|####9 | 90/181 [13:15<13:21, 8.81s/it]
3/3 0G 1.058 0.7954 1.113 303 800: 50%|####9 | 90/181 [13:23<13:21, 8.81s/it]
3/3 0G 1.058 0.7954 1.113 303 800: 50%|##### | 91/181 [13:23<13:13, 8.82s/it]
3/3 0G 1.058 0.7951 1.113 337 800: 50%|##### | 91/181 [13:32<13:13, 8.82s/it]
3/3 0G 1.058 0.7951 1.113 337 800: 51%|##### | 92/181 [13:32<13:11, 8.89s/it]
3/3 0G 1.058 0.7949 1.113 280 800: 51%|##### | 92/181 [13:41<13:11, 8.89s/it]
3/3 0G 1.058 0.7949 1.113 280 800: 51%|#####1 | 93/181 [13:41<12:59, 8.86s/it]
3/3 0G 1.058 0.7945 1.113 312 800: 51%|#####1 | 93/181 [13:50<12:59, 8.86s/it]
3/3 0G 1.058 0.7945 1.113 312 800: 52%|#####1 | 94/181 [13:50<12:48, 8.83s/it]
3/3 0G 1.057 0.7943 1.113 300 800: 52%|#####1 | 94/181 [13:59<12:48, 8.83s/it]
3/3 0G 1.057 0.7943 1.113 300 800: 52%|#####2 | 95/181 [13:59<12:40, 8.84s/it]
3/3 0G 1.058 0.7949 1.113 216 800: 52%|#####2 | 95/181 [14:08<12:40, 8.84s/it]
3/3 0G 1.058 0.7949 1.113 216 800: 53%|#####3 | 96/181 [14:08<12:30, 8.82s/it]
3/3 0G 1.057 0.7941 1.113 312 800: 53%|#####3 | 96/181 [14:17<12:30, 8.82s/it]
3/3 0G 1.057 0.7941 1.113 312 800: 54%|#####3 | 97/181 [14:17<12:23, 8.85s/it]
3/3 0G 1.058 0.7941 1.113 253 800: 54%|#####3 | 97/181 [14:25<12:23, 8.85s/it]
3/3 0G 1.058 0.7941 1.113 253 800: 54%|#####4 | 98/181 [14:25<12:13, 8.83s/it]
3/3 0G 1.058 0.7937 1.113 321 800: 54%|#####4 | 98/181 [14:34<12:13, 8.83s/it]
3/3 0G 1.058 0.7937 1.113 321 800: 55%|#####4 | 99/181 [14:34<12:04, 8.84s/it]
3/3 0G 1.058 0.7934 1.113 374 800: 55%|#####4 | 99/181 [14:43<12:04, 8.84s/it]
3/3 0G 1.058 0.7934 1.113 374 800: 55%|#####5 | 100/181 [14:43<12:00, 8.89s/it]
3/3 0G 1.058 0.7931 1.113 286 800: 55%|#####5 | 100/181 [14:52<12:00, 8.89s/it]
3/3 0G 1.058 0.7931 1.113 286 800: 56%|#####5 | 101/181 [14:52<11:52, 8.90s/it]
3/3 0G 1.058 0.7934 1.114 221 800: 56%|#####5 | 101/181 [15:01<11:52, 8.90s/it]
3/3 0G 1.058 0.7934 1.114 221 800: 56%|#####6 | 102/181 [15:01<11:39, 8.85s/it]
3/3 0G 1.058 0.7932 1.114 328 800: 56%|#####6 | 102/181 [15:10<11:39, 8.85s/it]
3/3 0G 1.058 0.7932 1.114 328 800: 57%|#####6 | 103/181 [15:10<11:28, 8.83s/it]
3/3 0G 1.058 0.7927 1.114 279 800: 57%|#####6 | 103/181 [15:18<11:28, 8.83s/it]
3/3 0G 1.058 0.7927 1.114 279 800: 57%|#####7 | 104/181 [15:18<11:20, 8.83s/it]
3/3 0G 1.058 0.7931 1.114 247 800: 57%|#####7 | 104/181 [15:27<11:20, 8.83s/it]
3/3 0G 1.058 0.7931 1.114 247 800: 58%|#####8 | 105/181 [15:27<11:12, 8.85s/it]
3/3 0G 1.058 0.7931 1.114 384 800: 58%|#####8 | 105/181 [15:36<11:12, 8.85s/it]
3/3 0G 1.058 0.7931 1.114 384 800: 59%|#####8 | 106/181 [15:36<10:59, 8.80s/it]
3/3 0G 1.058 0.7928 1.114 265 800: 59%|#####8 | 106/181 [15:45<10:59, 8.80s/it]
3/3 0G 1.058 0.7928 1.114 265 800: 59%|#####9 | 107/181 [15:45<10:53, 8.84s/it]
3/3 0G 1.058 0.7929 1.114 387 800: 59%|#####9 | 107/181 [15:54<10:53, 8.84s/it]
3/3 0G 1.058 0.7929 1.114 387 800: 60%|#####9 | 108/181 [15:54<10:49, 8.90s/it]
3/3 0G 1.058 0.7926 1.114 276 800: 60%|#####9 | 108/181 [16:03<10:49, 8.90s/it]
3/3 0G 1.058 0.7926 1.114 276 800: 60%|###### | 109/181 [16:03<10:40, 8.89s/it]
3/3 0G 1.058 0.7928 1.113 347 800: 60%|###### | 109/181 [16:12<10:40, 8.89s/it]
3/3 0G 1.058 0.7928 1.113 347 800: 61%|###### | 110/181 [16:12<10:28, 8.86s/it]
3/3 0G 1.058 0.7926 1.113 281 800: 61%|###### | 110/181 [16:21<10:28, 8.86s/it]
3/3 0G 1.058 0.7926 1.113 281 800: 61%|######1 | 111/181 [16:21<10:19, 8.85s/it]
3/3 0G 1.059 0.7928 1.114 282 800: 61%|######1 | 111/181 [16:29<10:19, 8.85s/it]
3/3 0G 1.059 0.7928 1.114 282 800: 62%|######1 | 112/181 [16:29<10:11, 8.87s/it]
3/3 0G 1.059 0.7923 1.114 283 800: 62%|######1 | 112/181 [16:38<10:11, 8.87s/it]
3/3 0G 1.059 0.7923 1.114 283 800: 62%|######2 | 113/181 [16:38<10:05, 8.91s/it]
3/3 0G 1.059 0.7921 1.114 234 800: 62%|######2 | 113/181 [16:47<10:05, 8.91s/it]
3/3 0G 1.059 0.7921 1.114 234 800: 63%|######2 | 114/181 [16:47<09:53, 8.86s/it]
3/3 0G 1.058 0.7916 1.114 227 800: 63%|######2 | 114/181 [16:56<09:53, 8.86s/it]
3/3 0G 1.058 0.7916 1.114 227 800: 64%|######3 | 115/181 [16:56<09:43, 8.84s/it]
3/3 0G 1.059 0.7912 1.115 263 800: 64%|######3 | 115/181 [17:05<09:43, 8.84s/it]
3/3 0G 1.059 0.7912 1.115 263 800: 64%|######4 | 116/181 [17:05<09:37, 8.88s/it]
3/3 0G 1.058 0.7905 1.114 358 800: 64%|######4 | 116/181 [17:14<09:37, 8.88s/it]
3/3 0G 1.058 0.7905 1.114 358 800: 65%|######4 | 117/181 [17:14<09:28, 8.89s/it]
3/3 0G 1.059 0.7909 1.115 261 800: 65%|######4 | 117/181 [17:23<09:28, 8.89s/it]
3/3 0G 1.059 0.7909 1.115 261 800: 65%|######5 | 118/181 [17:23<09:15, 8.82s/it]
3/3 0G 1.058 0.7906 1.114 272 800: 65%|######5 | 118/181 [17:31<09:15, 8.82s/it]
3/3 0G 1.058 0.7906 1.114 272 800: 66%|######5 | 119/181 [17:31<09:05, 8.80s/it]
3/3 0G 1.059 0.7908 1.115 279 800: 66%|######5 | 119/181 [17:40<09:05, 8.80s/it]
3/3 0G 1.059 0.7908 1.115 279 800: 66%|######6 | 120/181 [17:40<08:58, 8.84s/it]
3/3 0G 1.058 0.7906 1.114 312 800: 66%|######6 | 120/181 [17:49<08:58, 8.84s/it]
3/3 0G 1.058 0.7906 1.114 312 800: 67%|######6 | 121/181 [17:49<08:52, 8.87s/it]
3/3 0G 1.059 0.7907 1.114 339 800: 67%|######6 | 121/181 [17:58<08:52, 8.87s/it]
3/3 0G 1.059 0.7907 1.114 339 800: 67%|######7 | 122/181 [17:58<08:41, 8.85s/it]
3/3 0G 1.058 0.79 1.114 316 800: 67%|######7 | 122/181 [18:07<08:41, 8.85s/it]
3/3 0G 1.058 0.79 1.114 316 800: 68%|######7 | 123/181 [18:07<08:31, 8.81s/it]
3/3 0G 1.057 0.7894 1.114 216 800: 68%|######7 | 123/181 [18:16<08:31, 8.81s/it]
3/3 0G 1.057 0.7894 1.114 216 800: 69%|######8 | 124/181 [18:16<08:23, 8.84s/it]
3/3 0G 1.057 0.7888 1.113 286 800: 69%|######8 | 124/181 [18:24<08:23, 8.84s/it]
3/3 0G 1.057 0.7888 1.113 286 800: 69%|######9 | 125/181 [18:24<08:15, 8.85s/it]
3/3 0G 1.058 0.7888 1.113 261 800: 69%|######9 | 125/181 [18:33<08:15, 8.85s/it]
3/3 0G 1.058 0.7888 1.113 261 800: 70%|######9 | 126/181 [18:33<08:05, 8.82s/it]
3/3 0G 1.057 0.7881 1.113 315 800: 70%|######9 | 126/181 [18:42<08:05, 8.82s/it]
3/3 0G 1.057 0.7881 1.113 315 800: 70%|####### | 127/181 [18:42<08:00, 8.91s/it]
3/3 0G 1.057 0.7875 1.113 322 800: 70%|####### | 127/181 [18:51<08:00, 8.91s/it]
3/3 0G 1.057 0.7875 1.113 322 800: 71%|####### | 128/181 [18:51<07:51, 8.89s/it]
3/3 0G 1.057 0.7872 1.113 235 800: 71%|####### | 128/181 [19:00<07:51, 8.89s/it]
3/3 0G 1.057 0.7872 1.113 235 800: 71%|#######1 | 129/181 [19:00<07:41, 8.87s/it]
3/3 0G 1.056 0.7866 1.113 272 800: 71%|#######1 | 129/181 [19:09<07:41, 8.87s/it]
3/3 0G 1.056 0.7866 1.113 272 800: 72%|#######1 | 130/181 [19:09<07:29, 8.82s/it]
3/3 0G 1.056 0.7862 1.114 214 800: 72%|#######1 | 130/181 [19:17<07:29, 8.82s/it]
3/3 0G 1.056 0.7862 1.114 214 800: 72%|#######2 | 131/181 [19:17<07:19, 8.79s/it]
3/3 0G 1.056 0.7858 1.113 278 800: 72%|#######2 | 131/181 [19:26<07:19, 8.79s/it]
3/3 0G 1.056 0.7858 1.113 278 800: 73%|#######2 | 132/181 [19:26<07:12, 8.82s/it]
3/3 0G 1.056 0.7854 1.113 322 800: 73%|#######2 | 132/181 [19:35<07:12, 8.82s/it]
3/3 0G 1.056 0.7854 1.113 322 800: 73%|#######3 | 133/181 [19:35<07:05, 8.87s/it]
3/3 0G 1.056 0.7853 1.113 330 800: 73%|#######3 | 133/181 [19:44<07:05, 8.87s/it]
3/3 0G 1.056 0.7853 1.113 330 800: 74%|#######4 | 134/181 [19:44<06:57, 8.88s/it]
3/3 0G 1.056 0.7851 1.113 234 800: 74%|#######4 | 134/181 [19:53<06:57, 8.88s/it]
3/3 0G 1.056 0.7851 1.113 234 800: 75%|#######4 | 135/181 [19:53<06:47, 8.85s/it]
3/3 0G 1.056 0.7848 1.113 297 800: 75%|#######4 | 135/181 [20:02<06:47, 8.85s/it]
3/3 0G 1.056 0.7848 1.113 297 800: 75%|#######5 | 136/181 [20:02<06:39, 8.87s/it]
3/3 0G 1.056 0.7845 1.113 233 800: 75%|#######5 | 136/181 [20:11<06:39, 8.87s/it]
3/3 0G 1.056 0.7845 1.113 233 800: 76%|#######5 | 137/181 [20:11<06:29, 8.86s/it]
3/3 0G 1.056 0.784 1.113 320 800: 76%|#######5 | 137/181 [20:19<06:29, 8.86s/it]
3/3 0G 1.056 0.784 1.113 320 800: 76%|#######6 | 138/181 [20:19<06:19, 8.82s/it]
3/3 0G 1.056 0.7836 1.113 290 800: 76%|#######6 | 138/181 [20:28<06:19, 8.82s/it]
3/3 0G 1.056 0.7836 1.113 290 800: 77%|#######6 | 139/181 [20:28<06:11, 8.85s/it]
3/3 0G 1.056 0.7836 1.113 196 800: 77%|#######6 | 139/181 [20:37<06:11, 8.85s/it]
3/3 0G 1.056 0.7836 1.113 196 800: 77%|#######7 | 140/181 [20:37<06:01, 8.83s/it]
3/3 0G 1.056 0.7835 1.113 230 800: 77%|#######7 | 140/181 [20:46<06:01, 8.83s/it]
3/3 0G 1.056 0.7835 1.113 230 800: 78%|#######7 | 141/181 [20:46<05:54, 8.85s/it]
3/3 0G 1.056 0.7834 1.113 346 800: 78%|#######7 | 141/181 [20:55<05:54, 8.85s/it]
3/3 0G 1.056 0.7834 1.113 346 800: 78%|#######8 | 142/181 [20:55<05:44, 8.83s/it]
3/3 0G 1.056 0.783 1.113 382 800: 78%|#######8 | 142/181 [21:04<05:44, 8.83s/it]
3/3 0G 1.056 0.783 1.113 382 800: 79%|#######9 | 143/181 [21:04<05:34, 8.81s/it]
3/3 0G 1.056 0.7825 1.113 252 800: 79%|#######9 | 143/181 [21:13<05:34, 8.81s/it]
3/3 0G 1.056 0.7825 1.113 252 800: 80%|#######9 | 144/181 [21:13<05:27, 8.85s/it]
3/3 0G 1.055 0.7819 1.113 213 800: 80%|#######9 | 144/181 [21:21<05:27, 8.85s/it]
3/3 0G 1.055 0.7819 1.113 213 800: 80%|######## | 145/181 [21:21<05:19, 8.86s/it]
3/3 0G 1.056 0.7814 1.113 279 800: 80%|######## | 145/181 [21:30<05:19, 8.86s/it]
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3/3 0G 1.056 0.7809 1.113 260 800: 81%|######## | 146/181 [21:39<05:08, 8.81s/it]
3/3 0G 1.056 0.7809 1.113 260 800: 81%|########1 | 147/181 [21:39<04:59, 8.80s/it]
3/3 0G 1.055 0.7802 1.113 272 800: 81%|########1 | 147/181 [21:48<04:59, 8.80s/it]
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3/3 0G 1.055 0.7801 1.113 351 800: 82%|########1 | 148/181 [21:57<04:50, 8.80s/it]
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3/3 0G 1.056 0.7801 1.114 219 800: 82%|########2 | 149/181 [22:05<04:43, 8.87s/it]
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3/3 0G 1.055 0.7798 1.113 325 800: 83%|########2 | 150/181 [22:14<04:32, 8.80s/it]
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3/3 0G 1.055 0.7795 1.113 314 800: 83%|########3 | 151/181 [22:23<04:23, 8.79s/it]
3/3 0G 1.055 0.7795 1.113 314 800: 84%|########3 | 152/181 [22:23<04:16, 8.86s/it]
3/3 0G 1.055 0.7791 1.113 312 800: 84%|########3 | 152/181 [22:32<04:16, 8.86s/it]
3/3 0G 1.055 0.7791 1.113 312 800: 85%|########4 | 153/181 [22:32<04:08, 8.88s/it]
3/3 0G 1.055 0.7788 1.113 260 800: 85%|########4 | 153/181 [22:41<04:08, 8.88s/it]
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3/3 0G 1.054 0.7785 1.113 255 800: 85%|########5 | 154/181 [22:50<03:57, 8.81s/it]
3/3 0G 1.054 0.7785 1.113 255 800: 86%|########5 | 155/181 [22:50<03:49, 8.82s/it]
3/3 0G 1.054 0.7777 1.112 307 800: 86%|########5 | 155/181 [22:59<03:49, 8.82s/it]
3/3 0G 1.054 0.7777 1.112 307 800: 86%|########6 | 156/181 [22:59<03:42, 8.88s/it]
3/3 0G 1.053 0.7775 1.112 247 800: 86%|########6 | 156/181 [23:08<03:42, 8.88s/it]
3/3 0G 1.053 0.7775 1.112 247 800: 87%|########6 | 157/181 [23:08<03:33, 8.90s/it]
3/3 0G 1.054 0.7773 1.112 378 800: 87%|########6 | 157/181 [23:16<03:33, 8.90s/it]
3/3 0G 1.054 0.7773 1.112 378 800: 87%|########7 | 158/181 [23:16<03:23, 8.87s/it]
3/3 0G 1.054 0.7773 1.112 210 800: 87%|########7 | 158/181 [23:25<03:23, 8.87s/it]
3/3 0G 1.054 0.7773 1.112 210 800: 88%|########7 | 159/181 [23:25<03:14, 8.83s/it]
3/3 0G 1.054 0.7774 1.112 245 800: 88%|########7 | 159/181 [23:34<03:14, 8.83s/it]
3/3 0G 1.054 0.7774 1.112 245 800: 88%|########8 | 160/181 [23:34<03:05, 8.84s/it]
3/3 0G 1.054 0.7772 1.112 367 800: 88%|########8 | 160/181 [23:43<03:05, 8.84s/it]
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3/3 0G 1.054 0.7771 1.112 294 800: 89%|########8 | 161/181 [23:51<02:57, 8.85s/it]
3/3 0G 1.054 0.7771 1.112 294 800: 90%|########9 | 162/181 [23:51<02:47, 8.81s/it]
3/3 0G 1.053 0.7768 1.112 294 800: 90%|########9 | 162/181 [24:00<02:47, 8.81s/it]
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3/3 0G 1.053 0.7767 1.112 299 800: 91%|######### | 164/181 [24:18<02:29, 8.81s/it]
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3/3 0G 1.053 0.7766 1.111 244 800: 92%|#########1| 166/181 [24:36<02:12, 8.83s/it]
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3/3 0G 1.053 0.7761 1.111 270 800: 92%|#########2| 167/181 [24:45<02:04, 8.88s/it]
3/3 0G 1.053 0.7761 1.111 270 800: 93%|#########2| 168/181 [24:45<01:55, 8.90s/it]
3/3 0G 1.053 0.776 1.111 284 800: 93%|#########2| 168/181 [24:54<01:55, 8.90s/it]
3/3 0G 1.053 0.776 1.111 284 800: 93%|#########3| 169/181 [24:54<01:47, 8.94s/it]
3/3 0G 1.053 0.7757 1.111 328 800: 93%|#########3| 169/181 [25:03<01:47, 8.94s/it]
3/3 0G 1.053 0.7757 1.111 328 800: 94%|#########3| 170/181 [25:03<01:38, 8.95s/it]
3/3 0G 1.053 0.7757 1.111 320 800: 94%|#########3| 170/181 [25:12<01:38, 8.95s/it]
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3/3 0G 1.053 0.7755 1.111 268 800: 94%|#########4| 171/181 [25:21<01:29, 8.94s/it]
3/3 0G 1.053 0.7755 1.111 268 800: 95%|#########5| 172/181 [25:21<01:20, 8.94s/it]
3/3 0G 1.053 0.7754 1.111 316 800: 95%|#########5| 172/181 [25:30<01:20, 8.94s/it]
3/3 0G 1.053 0.7754 1.111 316 800: 96%|#########5| 173/181 [25:30<01:11, 8.96s/it]
3/3 0G 1.052 0.7752 1.111 290 800: 96%|#########5| 173/181 [25:38<01:11, 8.96s/it]
3/3 0G 1.052 0.7752 1.111 290 800: 96%|#########6| 174/181 [25:38<01:02, 8.89s/it]
3/3 0G 1.053 0.7751 1.111 328 800: 96%|#########6| 174/181 [25:47<01:02, 8.89s/it]
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3/3 0G 1.053 0.7753 1.111 250 800: 97%|#########6| 175/181 [25:56<00:53, 8.93s/it]
3/3 0G 1.053 0.7753 1.111 250 800: 97%|#########7| 176/181 [25:56<00:44, 8.89s/it]
3/3 0G 1.053 0.775 1.111 360 800: 97%|#########7| 176/181 [26:05<00:44, 8.89s/it]
3/3 0G 1.053 0.775 1.111 360 800: 98%|#########7| 177/181 [26:05<00:35, 8.90s/it]
3/3 0G 1.052 0.7747 1.11 346 800: 98%|#########7| 177/181 [26:14<00:35, 8.90s/it]
3/3 0G 1.052 0.7747 1.11 346 800: 98%|#########8| 178/181 [26:14<00:26, 8.84s/it]
3/3 0G 1.052 0.7743 1.11 300 800: 98%|#########8| 178/181 [26:23<00:26, 8.84s/it]
3/3 0G 1.052 0.7743 1.11 300 800: 99%|#########8| 179/181 [26:23<00:17, 8.82s/it]
3/3 0G 1.052 0.7744 1.11 328 800: 99%|#########8| 179/181 [26:32<00:17, 8.82s/it]
3/3 0G 1.052 0.7744 1.11 328 800: 99%|#########9| 180/181 [26:32<00:08, 8.87s/it]
3/3 0G 1.052 0.7744 1.11 303 800: 99%|#########9| 180/181 [26:40<00:08, 8.87s/it]
3/3 0G 1.052 0.7744 1.11 303 800: 100%|##########| 181/181 [26:40<00:00, 8.87s/it]
3/3 0G 1.052 0.7744 1.11 303 800: 100%|##########| 181/181 [26:40<00:00, 8.84s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 0%| | 0/4 [00:00<?, ?it/s]
Class Images Instances Box(P R mAP50 mAP50-95): 25%|##5 | 1/4 [00:06<00:20, 6.81s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 50%|##### | 2/4 [00:13<00:13, 6.92s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 75%|#######5 | 3/4 [00:20<00:06, 6.95s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 100%|##########| 4/4 [00:22<00:00, 4.73s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 100%|##########| 4/4 [00:22<00:00, 5.53s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 0%| | 0/4 [00:00<?, ?it/s]
Class Images Instances Box(P R mAP50 mAP50-95): 25%|##5 | 1/4 [00:05<00:17, 5.72s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 50%|##### | 2/4 [00:11<00:11, 5.92s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 75%|#######5 | 3/4 [00:17<00:05, 5.97s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 100%|##########| 4/4 [00:19<00:00, 4.13s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 100%|##########| 4/4 [00:19<00:00, 4.78s/it]
Evaluate the trained model#
Assess the performance of the trained model.
Confusion matrix#
The X-axis represents the predicted class and the Y-axis represents the actual class.
The diagonal cells show true positives, they show how many instances of each class were correctly predicted by the model. The off-diagonal cells show instances where the predicted class did not match the actual class.
from IPython.display import Image
Image(filename=f'runs/detect/train7/confusion_matrix.png', width=600)
Loss and Accuracy plots#
The plot below shows the loss and accuracy plot for YOLOv8 when fine-tuned on the ai-cook data set. The model performed well with a high precision and recall rate of 0.94 or higher. The mean-average-precision for an IoU > 0.5 (a good prediction) for YOLOv8 was 0.97.
Image(filename=f'runs/detect/train7/results.png', width=600)
Image(filename=f'runs/detect/train7/val_batch0_pred.jpg', width=600)
Validate Custom Model#
Run the model on validation images and display the results.
Validate the YOLOv8 model on the validation dataset using the YOLO CLI command
‘task=detect’ specifies that the task is object detection
‘mode=val’ puts the model in validation mode, which assesses performance on a validation set
‘model=runs/detect/train7/weights/best.pt’ specifies the path to the trained model weights (the best weights from training)
‘data={dataset.location}/data.yaml’ provides the path to the dataset configuration file, which includes validation data paths
!yolo task=detect mode=val model=runs/detect/train7/weights/best.pt data={dataset.location}/data.yaml
Ultralytics YOLOv8.2.89 🚀 Python-3.12.4 torch-2.4.1+cpu CPU (AMD Ryzen 9 7940HS w/ Radeon 780M Graphics)
Model summary (fused): 168 layers, 11,137,194 parameters, 0 gradients, 28.5 GFLOPs
all 103 1227 0.927 0.94 0.963 0.635
apple 43 44 0.827 0.976 0.977 0.742
banana 41 41 0.986 1 0.995 0.744
beef 24 24 0.864 0.53 0.759 0.28
blueberries 33 33 0.908 0.97 0.966 0.621
bread 41 41 0.904 0.951 0.966 0.654
butter 32 32 0.983 1 0.995 0.715
carrot 35 37 0.859 0.946 0.946 0.52
cheese 49 49 0.984 1 0.995 0.74
chicken 27 27 0.962 1 0.995 0.631
chicken_breast 35 35 0.553 0.886 0.673 0.237
chocolate 29 29 1 0.872 0.98 0.61
corn 48 48 1 0.997 0.995 0.672
eggs 60 60 0.996 1 0.995 0.662
flour 53 58 0.941 0.948 0.954 0.7
goat_cheese 11 11 0.928 0.909 0.988 0.716
green_beans 47 47 0.896 0.979 0.979 0.621
ground_beef 22 22 0.825 0.859 0.949 0.442
ham 7 7 0.945 1 0.995 0.522
heavy_cream 44 44 0.98 1 0.995 0.676
lime 28 28 0.961 0.888 0.976 0.716
milk 39 48 0.954 0.958 0.981 0.724
mushrooms 56 56 0.963 0.911 0.986 0.684
onion 42 42 0.903 1 0.991 0.759
potato 64 64 1 0.947 0.984 0.702
shrimp 42 42 0.944 0.796 0.955 0.549
spinach 38 38 0.944 0.891 0.973 0.67
strawberries 51 51 0.973 0.98 0.995 0.741
sugar 63 78 0.919 1 0.974 0.704
sweet_potato 30 32 0.926 1 0.993 0.714
tomato 58 59 0.992 1 0.995 0.59
Speed: 1.2ms preprocess, 137.4ms inference, 0.0ms loss, 0.6ms postprocess per image
Results saved to runs\detect\val
💡 Learn more at https://docs.ultralytics.com/modes/val
val: Scanning aup-ai-tutorials\train\aicook-4\valid\labels.cache... 103 images, 0 backgrounds, 0 corrupt: 100%|##########| 103/103 [00:00<?, ?it/s]
val: Scanning aup-ai-tutorials\train\aicook-4\valid\labels.cache... 103 images, 0 backgrounds, 0 corrupt: 100%|##########| 103/103 [00:00<?, ?it/s]
Class Images Instances Box(P R mAP50 mAP50-95): 0%| | 0/7 [00:00<?, ?it/s]
Class Images Instances Box(P R mAP50 mAP50-95): 14%|#4 | 1/7 [00:02<00:14, 2.41s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 29%|##8 | 2/7 [00:04<00:12, 2.47s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 43%|####2 | 3/7 [00:07<00:09, 2.48s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 57%|#####7 | 4/7 [00:09<00:07, 2.47s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 71%|#######1 | 5/7 [00:12<00:04, 2.42s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 86%|########5 | 6/7 [00:14<00:02, 2.38s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 100%|##########| 7/7 [00:15<00:00, 1.92s/it]
Class Images Instances Box(P R mAP50 mAP50-95): 100%|##########| 7/7 [00:15<00:00, 2.21s/it]
Display a batch of images
Image(filename=f'runs/detect/val/val_batch0_pred.jpg', width=600)
Inference with Custom Model#
Test the model on new images and display the results.
Use the YOLOv8 model to make predictions on test images with the YOLO CLI command
‘task=detect’ specifies that the task is object detection
‘mode=predict’ sets the model to prediction mode, which performs inference on input images
‘model=./runs/detect/train7/weights/best.pt’ specifies the path to the trained model weights (using the best weights from training)
‘conf=0.25’ sets the confidence threshold for detections (only predictions with a confidence score above 25% will be displayed)
‘source={dataset.location}/test/images’ defines the source directory of the test images for inference
‘save=True’ enables saving the output images with detected objects to a directory
!yolo task=detect mode=predict model=./runs/detect/train7/weights/best.pt conf=0.25 source={dataset.location}/test/images save=True
Ultralytics YOLOv8.2.89 🚀 Python-3.12.4 torch-2.4.1+cpu CPU (AMD Ryzen 9 7940HS w/ Radeon 780M Graphics)
Model summary (fused): 168 layers, 11,137,194 parameters, 0 gradients, 28.5 GFLOPs
image 1/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_5941_JPG_jpg.rf.7f34ef03affd2f952f6519e8506d8cdc.jpg: 800x800 1 apple, 1 bread, 1 carrot, 1 chocolate, 1 flour, 1 green_beans, 1 ground_beef, 1 lime, 1 strawberries, 2 sugars, 1 tomato, 140.8ms
image 2/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_5945_JPG_jpg.rf.15457f9c7c97e17d20684976193e6e8f.jpg: 800x800 1 apple, 2 beefs, 1 bread, 1 carrot, 1 chicken, 1 chicken_breast, 1 ground_beef, 1 lime, 1 spinach, 1 strawberries, 1 sugar, 1 tomato, 117.7ms
image 3/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_5959_JPG_jpg.rf.9fc416d1349e2e3c26a0a0d2a15a7976.jpg: 800x800 1 bread, 1 butter, 1 cheese, 1 eggs, 1 green_beans, 1 ground_beef, 1 heavy_cream, 1 mushrooms, 1 onion, 1 spinach, 1 strawberries, 3 sweet_potatos, 114.3ms
image 4/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_5966_JPG_jpg.rf.5d1394ae07842ba768ef443a1f11100e.jpg: 800x800 1 apple, 1 blueberries, 1 bread, 1 chicken_breast, 1 chocolate, 1 eggs, 2 onions, 1 spinach, 1 strawberries, 1 sugar, 1 sweet_potato, 1 tomato, 110.2ms
image 5/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_5968_JPG_jpg.rf.5eb40ebc6ac76249dfc35ddacc0a3aee.jpg: 800x800 1 apple, 1 bread, 1 cheese, 1 chicken_breast, 1 chocolate, 1 eggs, 1 potato, 2 strawberriess, 1 sugar, 1 sweet_potato, 106.0ms
image 6/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_5994_JPG_jpg.rf.e59df6997260d8a4811dea2ac9fd906b.jpg: 800x800 1 banana, 1 blueberries, 1 bread, 1 chicken, 1 chicken_breast, 1 eggs, 1 flour, 1 green_beans, 1 potato, 1 shrimp, 1 sugar, 114.0ms
image 7/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6021_JPG_jpg.rf.624152252b749f6789ed901524aa61fd.jpg: 800x800 1 banana, 1 cheese, 1 chicken_breast, 1 chocolate, 1 corn, 1 eggs, 1 heavy_cream, 1 milk, 1 mushrooms, 1 potato, 1 tomato, 118.3ms
image 8/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6054_JPG_jpg.rf.6f7baadc273b8df793ef0372f9a9be39.jpg: 800x800 1 apple, 1 bread, 1 butter, 1 cheese, 2 chicken_breasts, 1 corn, 1 eggs, 1 flour, 1 green_beans, 1 ground_beef, 1 milk, 1 strawberries, 2 sweet_potatos, 103.2ms
image 9/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6059_JPG_jpg.rf.6d01b8d48241048bb9456081492861ca.jpg: 800x800 1 banana, 1 bread, 1 cheese, 1 eggs, 1 flour, 1 green_beans, 1 milk, 1 mushrooms, 1 onion, 1 strawberries, 1 sugar, 113.0ms
image 10/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6060_JPG_jpg.rf.aaadd1e2af83511440f289f21abf4099.jpg: 800x800 1 banana, 1 bread, 1 cheese, 1 chicken_breast, 1 eggs, 1 flour, 1 green_beans, 1 milk, 1 mushrooms, 1 onion, 1 strawberries, 1 sugar, 113.8ms
image 11/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6065_JPG_jpg.rf.564df77ab0cd26ddebf9a40aa5a331d5.jpg: 800x800 1 banana, 1 bread, 1 cheese, 1 chicken_breast, 1 chocolate, 1 eggs, 1 flour, 1 green_beans, 2 milks, 1 mushrooms, 1 onion, 1 shrimp, 117.2ms
image 12/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6067_JPG_jpg.rf.d1098c3269fb5a8b884c44ad9a8e679c.jpg: 800x800 1 banana, 1 bread, 1 butter, 1 cheese, 1 eggs, 1 flour, 1 green_beans, 1 mushrooms, 1 onion, 1 shrimp, 118.2ms
image 13/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6069_JPG_jpg.rf.84034956163d2654b1ea41786d3b6189.jpg: 800x800 1 apple, 2 breads, 1 butter, 1 cheese, 1 chicken_breast, 1 chocolate, 1 eggs, 1 flour, 1 green_beans, 1 mushrooms, 1 onion, 1 shrimp, 114.0ms
image 14/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6072_JPG_jpg.rf.5873ad8da06b887c08a768c5655f320b.jpg: 800x800 1 apple, 1 bread, 1 butter, 1 cheese, 1 chicken_breast, 1 eggs, 1 flour, 1 green_beans, 1 onion, 1 shrimp, 116.1ms
image 15/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6073_JPG_jpg.rf.6fce287076b0a40cd67889aab85418a7.jpg: 800x800 1 apple, 1 beef, 1 bread, 1 cheese, 1 eggs, 1 flour, 1 green_beans, 1 onion, 1 potato, 1 shrimp, 112.4ms
image 16/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6074_JPG_jpg.rf.f88f78a1872d7cf3f5834d7bbbad65cc.jpg: 800x800 1 apple, 1 beef, 1 bread, 1 cheese, 1 chicken_breast, 1 eggs, 1 flour, 1 green_beans, 1 lime, 1 onion, 1 potato, 1 shrimp, 113.7ms
image 17/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6076_JPG_jpg.rf.7e91bf702c848a342ca9f27e720eb698.jpg: 800x800 1 apple, 1 beef, 1 blueberries, 1 cheese, 1 chicken_breast, 1 eggs, 1 flour, 2 green_beanss, 2 limes, 1 onion, 1 potato, 1 spinach, 117.0ms
image 18/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6077_JPG_jpg.rf.288867a7b9a9a2e7c70751cfabc2a1db.jpg: 800x800 1 apple, 1 beef, 1 blueberries, 1 cheese, 1 eggs, 1 green_beans, 1 lime, 1 onion, 2 potatos, 1 spinach, 113.4ms
image 19/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6078_JPG_jpg.rf.fc893aec75fed3ce0858b6e463a6f3a8.jpg: 800x800 1 apple, 1 beef, 1 blueberries, 1 cheese, 1 chicken_breast, 1 eggs, 1 flour, 1 green_beans, 1 onion, 1 potato, 2 spinachs, 113.3ms
image 20/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6079_JPG_jpg.rf.cfa6235726a16182fee204865c7ec52d.jpg: 800x800 1 apple, 1 beef, 1 blueberries, 1 cheese, 2 chicken_breasts, 1 eggs, 1 flour, 1 green_beans, 1 lime, 1 onion, 1 potato, 1 spinach, 115.7ms
image 21/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6080_JPG_jpg.rf.dd18c6ec8d9f3c84689d4ee527a43cff.jpg: 800x800 1 blueberries, 1 cheese, 1 chicken, 2 chicken_breasts, 1 eggs, 1 flour, 1 lime, 1 onion, 1 potato, 113.9ms
image 22/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6082_JPG_jpg.rf.5826a63def4bcc615717da331d38e901.jpg: 800x800 1 apple, 1 beef, 1 blueberries, 1 chicken, 2 chicken_breasts, 1 corn, 1 eggs, 1 flour, 1 ground_beef, 1 milk, 1 potato, 1 tomato, 114.3ms
image 23/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6083_JPG_jpg.rf.c6e66a02ab7dada63a83a7463190e8c3.jpg: 800x800 1 beef, 1 blueberries, 1 chicken, 2 chicken_breasts, 1 corn, 1 eggs, 1 flour, 1 milk, 1 potato, 1 tomato, 117.0ms
image 24/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6084_JPG_jpg.rf.f7deac2397b83ba9075619a979cc5613.jpg: 800x800 1 beef, 1 blueberries, 1 butter, 1 chicken, 2 chicken_breasts, 1 corn, 1 eggs, 1 flour, 1 milk, 1 potato, 114.7ms
image 25/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6085_JPG_jpg.rf.1d156d69a4a4348e1274b71a9ff91f0d.jpg: 800x800 1 blueberries, 1 butter, 1 chicken, 2 chicken_breasts, 1 corn, 1 eggs, 1 flour, 1 mushrooms, 1 potato, 1 strawberries, 1 sugar, 115.9ms
image 26/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6089_JPG_jpg.rf.fa37d8ef13cb74d0b20cbe3a5331789a.jpg: 800x800 1 beef, 2 blueberriess, 1 chicken, 1 chicken_breast, 1 corn, 1 eggs, 1 flour, 1 heavy_cream, 1 potato, 1 strawberries, 1 sugar, 116.4ms
image 27/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6090_JPG_jpg.rf.c5fd03c031efa773a79bbd0f40025ae9.jpg: 800x800 1 beef, 1 blueberries, 1 cheese, 1 chicken, 1 chicken_breast, 1 corn, 1 eggs, 1 flour, 1 milk, 1 potato, 1 strawberries, 1 sugar, 120.4ms
image 28/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6091_JPG_jpg.rf.d9493f73a3360959aa1ecc64176e67c6.jpg: 800x800 1 beef, 1 blueberries, 1 cheese, 1 chicken, 1 chicken_breast, 1 chocolate, 1 corn, 1 eggs, 1 flour, 1 milk, 1 potato, 1 strawberries, 115.9ms
image 29/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6092_JPG_jpg.rf.05eb9a1289d9aa88e05b6403b6a4bfc2.jpg: 800x800 1 beef, 1 blueberries, 1 cheese, 1 chicken, 1 chicken_breast, 1 chocolate, 1 corn, 1 eggs, 1 flour, 2 milks, 2 potatos, 1 strawberries, 1 sugar, 115.3ms
image 30/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6093_JPG_jpg.rf.1ce230d6d529e44c6644c672e05e2957.jpg: 800x800 1 apple, 1 beef, 1 blueberries, 1 cheese, 1 chicken, 1 chocolate, 1 corn, 1 eggs, 1 flour, 2 limes, 2 milks, 1 potato, 1 strawberries, 115.8ms
image 31/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6095_JPG_jpg.rf.f2a7d4dce16f81a68e5ff5abcce2b5fc.jpg: 800x800 1 apple, 1 beef, 1 blueberries, 1 carrot, 1 chicken, 1 chicken_breast, 2 corns, 1 eggs, 2 milks, 1 onion, 1 strawberries, 1 sugar, 113.3ms
image 32/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6096_JPG_jpg.rf.9a8bd1abb671636f1571e8f6b35edeba.jpg: 800x800 1 apple, 1 beef, 2 blueberriess, 1 carrot, 1 chicken, 1 corn, 1 eggs, 1 flour, 1 ground_beef, 2 milks, 1 strawberries, 113.5ms
image 33/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6097_JPG_jpg.rf.f19732a3986e212e490be477045c14de.jpg: 800x800 1 apple, 1 blueberries, 2 carrots, 1 chicken, 2 chicken_breasts, 1 corn, 1 eggs, 1 flour, 1 ground_beef, 1 milk, 1 strawberries, 115.3ms
image 34/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6098_JPG_jpg.rf.bbcafc7e8d30934d085fb4861f858c19.jpg: 800x800 1 apple, 1 beef, 1 blueberries, 1 carrot, 1 chicken, 1 chicken_breast, 1 corn, 1 eggs, 1 flour, 1 ground_beef, 1 milk, 1 strawberries, 1 sugar, 112.9ms
image 35/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6099_JPG_jpg.rf.3039514604f0ad81210a752a39882524.jpg: 800x800 1 apple, 1 blueberries, 1 bread, 1 carrot, 1 chicken, 2 chicken_breasts, 1 corn, 1 eggs, 1 flour, 1 ground_beef, 1 milk, 1 sugar, 113.5ms
image 36/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6100_JPG_jpg.rf.7120b7220cd97f99aa583effd1abf327.jpg: 800x800 3 apples, 1 beef, 1 bread, 1 carrot, 1 chicken, 2 chicken_breasts, 1 corn, 1 eggs, 1 flour, 1 ground_beef, 1 milk, 1 sugar, 111.7ms
image 37/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6104_JPG_jpg.rf.e15e409dc36be42b274c64ef99005173.jpg: 800x800 1 apple, 1 beef, 1 bread, 1 carrot, 1 chicken, 1 chicken_breast, 1 eggs, 1 flour, 2 milks, 1 sugar, 113.0ms
image 38/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6105_JPG_jpg.rf.ff0a91dcb57df0748309bc56f19afd21.jpg: 800x800 1 apple, 1 beef, 1 bread, 1 carrot, 1 cheese, 1 chicken, 1 chicken_breast, 1 eggs, 1 flour, 1 lime, 3 milks, 1 sugar, 114.5ms
image 39/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6106_JPG_jpg.rf.acbbcdb96e5ac7389d43925a6af23102.jpg: 800x800 1 apple, 1 beef, 1 bread, 1 carrot, 1 cheese, 1 chicken, 2 chicken_breasts, 1 eggs, 1 flour, 1 lime, 2 milks, 1 shrimp, 1 sugar, 110.9ms
image 40/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6107_JPG_jpg.rf.2bb5660c99f5942f8b6dcca5c7ba9a16.jpg: 800x800 1 apple, 1 beef, 1 bread, 1 butter, 1 carrot, 1 cheese, 1 chicken, 2 chicken_breasts, 1 eggs, 1 flour, 1 lime, 3 milks, 1 shrimp, 1 sugar, 116.3ms
image 41/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6108_JPG_jpg.rf.38cc9fcc1ddf0fc0c8f80ffaeb52488a.jpg: 800x800 1 apple, 1 beef, 1 butter, 1 carrot, 1 cheese, 1 chicken, 2 chicken_breasts, 1 eggs, 1 lime, 1 milk, 2 shrimps, 1 sugar, 113.3ms
image 42/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6110_JPG_jpg.rf.f13fb135d157fd365b2241c4a2d7fe02.jpg: 800x800 1 apple, 1 bread, 1 butter, 1 chicken, 2 chicken_breasts, 1 eggs, 2 flours, 1 green_beans, 1 ground_beef, 1 milk, 1 shrimp, 1 sweet_potato, 113.4ms
image 43/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6111_JPG_jpg.rf.d1bd597e751651dcb4352eae69d689ef.jpg: 800x800 1 apple, 1 beef, 1 bread, 1 butter, 1 chicken, 2 chicken_breasts, 1 eggs, 2 flours, 1 green_beans, 1 ground_beef, 1 milk, 1 shrimp, 1 sweet_potato, 109.5ms
image 44/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6112_JPG_jpg.rf.7adc4e1f67cd111a7aebd2d3af0d264b.jpg: 800x800 1 apple, 1 bread, 1 butter, 1 cheese, 1 chicken, 1 chicken_breast, 1 eggs, 1 flour, 1 green_beans, 1 ground_beef, 1 shrimp, 1 strawberries, 1 sweet_potato, 110.8ms
image 45/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6113_JPG_jpg.rf.9a7c1f6ada4508c5b4b9b518e1252dfc.jpg: 800x800 1 apple, 1 bread, 1 cheese, 1 chicken, 1 eggs, 1 flour, 1 green_beans, 1 ground_beef, 1 milk, 1 mushrooms, 1 onion, 1 shrimp, 1 sweet_potato, 110.9ms
image 46/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6115_JPG_jpg.rf.47488bf353646497486a31e6a0a5e43e.jpg: 800x800 1 bread, 1 carrot, 1 cheese, 1 chicken, 1 flour, 1 green_beans, 1 ground_beef, 1 lime, 1 milk, 1 onion, 1 strawberries, 1 sweet_potato, 1 tomato, 116.1ms
image 47/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6116_JPG_jpg.rf.fbf038d25af223dd2e9fdd55b262a062.jpg: 800x800 1 carrot, 1 cheese, 1 chicken, 1 corn, 1 flour, 1 heavy_cream, 1 lime, 1 milk, 1 mushrooms, 1 onion, 1 strawberries, 1 sweet_potato, 1 tomato, 110.2ms
image 48/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6118_JPG_jpg.rf.59a322b5925c268682d8f3049d37db7e.jpg: 800x800 1 bread, 1 chicken, 1 chicken_breast, 1 eggs, 1 flour, 1 green_beans, 1 heavy_cream, 1 milk, 1 mushrooms, 1 onion, 1 spinach, 1 strawberries, 1 tomato, 112.4ms
image 49/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6119_JPG_jpg.rf.66f55ef8c2f07e811b33307ee130cdbc.jpg: 800x800 1 bread, 1 chicken, 1 chicken_breast, 1 eggs, 1 flour, 1 green_beans, 1 heavy_cream, 1 milk, 1 mushrooms, 1 onion, 4 spinachs, 1 strawberries, 1 tomato, 116.1ms
image 50/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6120_JPG_jpg.rf.c22d6d6e7c23ea5ed6729a4362b2d20f.jpg: 800x800 1 chicken, 2 chicken_breasts, 1 eggs, 1 flour, 1 green_beans, 1 ground_beef, 1 milk, 1 mushrooms, 1 onion, 1 potato, 2 spinachs, 1 strawberries, 1 tomato, 121.8ms
image 51/51 aup-ai-tutorials\train\aicook-4\test\images\DSC_6121_JPG_jpg.rf.46804f374a0f5f83ea880d6eb02d3364.jpg: 800x800 1 bread, 2 cheeses, 1 chicken, 2 chicken_breasts, 1 eggs, 1 flour, 1 green_beans, 1 ground_beef, 2 milks, 1 mushrooms, 1 potato, 1 shrimp, 1 spinach, 1 tomato, 111.4ms
Speed: 3.0ms preprocess, 114.6ms inference, 0.6ms postprocess per image at shape (1, 3, 800, 800)
Results saved to runs\detect\predict3
💡 Learn more at https://docs.ultralytics.com/modes/predict
Display a few predictions#
import matplotlib.pyplot as plt
import glob
from IPython.display import display, Image
# Set up the 3x3 grid
fig, axes = plt.subplots(3, 3, figsize=(12, 12))
# Get the first 9 images from the specified folder
image_paths = glob.glob(f'runs/detect/predict3/*.jpg')[:9]
# Display each image in the grid
for i, ax in enumerate(axes.flat):
if i < len(image_paths):
img = plt.imread(image_paths[i])
ax.imshow(img)
ax.axis('off') # Hide axes for a cleaner look
else:
ax.axis('off') # Hide any extra subplots
# Show the 3x3 grid of images
plt.tight_layout()
plt.show()
Copyright (C) 2025 Advanced Micro Devices, Inc. All rights reserved.
SPDX-License-Identifier: MIT