Update README file

README.md

@@ -6,18 +6,18 @@ tags: []
 ## Original result
 ```
 IoU metric: bbox
- Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.002
- Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.009
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.000
+ Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.000
  Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.000
  Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000
  Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000
- Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.002
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000
  Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.000
  Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.000
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.100
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.000
  Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000
  Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000
- Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.100
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000
 ```
 
 ## After training result
@@ -49,11 +49,11 @@ IoU metric: bbox
 ## Logging
 ### Training process
 ```
-{'validation_loss': tensor(4.1854, device='cuda:0'), 'validation_loss_ce': tensor(1.6290, device='cuda:0'), 'validation_loss_bbox': tensor(0.2323, device='cuda:0'), 'validation_loss_giou': tensor(0.6976, device='cuda:0'), 'validation_cardinality_error': tensor(7., device='cuda:0')}
-{'training_loss': tensor(4.1854, device='cuda:0'), 'train_loss_ce': tensor(1.6290, device='cuda:0'), 'train_loss_bbox': tensor(0.2323, device='cuda:0'), 'train_loss_giou': tensor(0.6976, device='cuda:0'), 'train_cardinality_error': tensor(7., device='cuda:0'), 'validation_loss': tensor(5.7900, device='cuda:0'), 'validation_loss_ce': tensor(1.4416, device='cuda:0'), 'validation_loss_bbox': tensor(0.5520, device='cuda:0'), 'validation_loss_giou': tensor(0.7942, device='cuda:0'), 'validation_cardinality_error': tensor(1., device='cuda:0')}
+{'validation_loss': tensor(5.3133, device='cuda:0'), 'validation_loss_ce': tensor(1.9971, device='cuda:0'), 'validation_loss_bbox': tensor(0.4005, device='cuda:0'), 'validation_loss_giou': tensor(0.6569, device='cuda:0'), 'validation_cardinality_error': tensor(94., device='cuda:0')}
+{'training_loss': tensor(5.3133, device='cuda:0'), 'train_loss_ce': tensor(1.9971, device='cuda:0'), 'train_loss_bbox': tensor(0.4005, device='cuda:0'), 'train_loss_giou': tensor(0.6569, device='cuda:0'), 'train_cardinality_error': tensor(94., device='cuda:0'), 'validation_loss': tensor(5.8451, device='cuda:0'), 'validation_loss_ce': tensor(1.8095, device='cuda:0'), 'validation_loss_bbox': tensor(0.3824, device='cuda:0'), 'validation_loss_giou': tensor(1.0617, device='cuda:0'), 'validation_cardinality_error': tensor(53., device='cuda:0')}
 ```
 
 ## Examples
-{'size': tensor([800, 800]), 'image_id': tensor([543]), 'class_labels': tensor([2]), 'boxes': tensor([[0.7222, 0.5302, 0.3101, 0.3513]]), 'area': tensor([69714.3281]), 'iscrowd': tensor([0]), 'orig_size': tensor([1024, 1024])}
+{'size': tensor([800, 800]), 'image_id': tensor([40]), 'class_labels': tensor([4]), 'boxes': tensor([[0.6817, 0.5681, 0.3008, 0.1822]]), 'area': tensor([35081.8711]), 'iscrowd': tensor([0]), 'orig_size': tensor([1024, 1024])}
 
 ![Example](./example.png)