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@@ -12,17 +12,17 @@ Not provided
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  ```
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  IoU metric: bbox
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  Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.006
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- Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.012
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- Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.006
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  Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
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  Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000
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  Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.006
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.037
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.064
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.072
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  Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
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  Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000
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- Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.074
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  ```
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  ## Config
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  ## Logging
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  ### Training process
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  ```
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- {'validation_loss': tensor(8.3678, device='cuda:0'), 'validation_loss_ce': tensor(3.2526, device='cuda:0'), 'validation_loss_bbox': tensor(0.5756, device='cuda:0'), 'validation_loss_giou': tensor(1.1184, device='cuda:0'), 'validation_cardinality_error': tensor(99.5938, device='cuda:0')}
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- {'training_loss': tensor(1.3440, device='cuda:0'), 'train_loss_ce': tensor(0.2790, device='cuda:0'), 'train_loss_bbox': tensor(0.0702, device='cuda:0'), 'train_loss_giou': tensor(0.3571, device='cuda:0'), 'train_cardinality_error': tensor(0.6471, device='cuda:0'), 'validation_loss': tensor(1.6742, device='cuda:0'), 'validation_loss_ce': tensor(0.2339, device='cuda:0'), 'validation_loss_bbox': tensor(0.0976, device='cuda:0'), 'validation_loss_giou': tensor(0.4762, device='cuda:0'), 'validation_cardinality_error': tensor(0.5294, device='cuda:0')}
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  ```
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  ## Examples
 
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  ```
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  IoU metric: bbox
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  Average Precision (AP) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.006
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+ Average Precision (AP) @[ IoU=0.50 | area= all | maxDets=100 ] = 0.016
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+ Average Precision (AP) @[ IoU=0.75 | area= all | maxDets=100 ] = 0.004
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  Average Precision (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
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  Average Precision (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000
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  Average Precision (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.006
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 1 ] = 0.041
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets= 10 ] = 0.077
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area= all | maxDets=100 ] = 0.083
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  Average Recall (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
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  Average Recall (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.000
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+ Average Recall (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.085
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  ```
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  ## Config
 
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  ## Logging
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  ### Training process
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  ```
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+ {'validation_loss': tensor(7.8284, device='cuda:1'), 'validation_loss_ce': tensor(2.7671, device='cuda:1'), 'validation_loss_bbox': tensor(0.5730, device='cuda:1'), 'validation_loss_giou': tensor(1.0983, device='cuda:1'), 'validation_cardinality_error': tensor(98.8125, device='cuda:1')}
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+ {'training_loss': tensor(1.3821, device='cuda:1'), 'train_loss_ce': tensor(0.1972, device='cuda:1'), 'train_loss_bbox': tensor(0.0681, device='cuda:1'), 'train_loss_giou': tensor(0.4223, device='cuda:1'), 'train_cardinality_error': tensor(0.4118, device='cuda:1'), 'validation_loss': tensor(1.6166, device='cuda:1'), 'validation_loss_ce': tensor(0.2388, device='cuda:1'), 'validation_loss_bbox': tensor(0.0936, device='cuda:1'), 'validation_loss_giou': tensor(0.4548, device='cuda:1'), 'validation_cardinality_error': tensor(0.5118, device='cuda:1')}
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  ```
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  ## Examples