Update README file

README.md

@@ -9,32 +9,32 @@ IoU metric: bbox
  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 ] = 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 ] = 0.000
  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 ] = 0.002
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.002
- Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 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 ] = 0.000
+ 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 ] = 0.000
- Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.002
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.000
 ```
 
 ## After training result
 ```
 IoU metric: bbox
- Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.015
- Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.035
- Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.010
- Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
- Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.009
- Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.018
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.080
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.183
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.201
- Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = 0.000
- Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = 0.016
- Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.225
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.004
+ Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.014
+ Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.001
+ 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 ] = 0.000
+ Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.004
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.048
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.123
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.138
+ 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 ] = 0.000
+ Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.139
 ```
 
 ## Config
@@ -46,55 +46,55 @@ IoU metric: bbox
 ## Logging
 ### Training process
 ```
-{'validation_loss': tensor(6.3440, device='cuda:0'), 'validation_loss_ce': tensor(2.0978, device='cuda:0'), 'validation_loss_bbox': tensor(0.4936, device='cuda:0'), 'validation_loss_giou': tensor(0.8890, device='cuda:0'), 'validation_cardinality_error': tensor(85.6562, device='cuda:0')}
-{'training_loss': tensor(3.1706, device='cuda:0'), 'train_loss_ce': tensor(0.5251, device='cuda:0'), 'train_loss_bbox': tensor(0.2706, device='cuda:0'), 'train_loss_giou': tensor(0.6462, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.9125, device='cuda:0'), 'validation_loss_ce': tensor(0.5056, device='cuda:0'), 'validation_loss_bbox': tensor(0.2312, device='cuda:0'), 'validation_loss_giou': tensor(0.6255, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.4987, device='cuda:0'), 'train_loss_ce': tensor(0.5532, device='cuda:0'), 'train_loss_bbox': tensor(0.1583, device='cuda:0'), 'train_loss_giou': tensor(0.5770, device='cuda:0'), 'train_cardinality_error': tensor(1.3125, device='cuda:0'), 'validation_loss': tensor(2.3335, device='cuda:0'), 'validation_loss_ce': tensor(0.4910, device='cuda:0'), 'validation_loss_bbox': tensor(0.1606, device='cuda:0'), 'validation_loss_giou': tensor(0.5197, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.5471, device='cuda:0'), 'train_loss_ce': tensor(0.4087, device='cuda:0'), 'train_loss_bbox': tensor(0.1558, device='cuda:0'), 'train_loss_giou': tensor(0.6798, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.3420, device='cuda:0'), 'validation_loss_ce': tensor(0.4825, device='cuda:0'), 'validation_loss_bbox': tensor(0.1571, device='cuda:0'), 'validation_loss_giou': tensor(0.5370, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.4962, device='cuda:0'), 'train_loss_ce': tensor(0.5160, device='cuda:0'), 'train_loss_bbox': tensor(0.1702, device='cuda:0'), 'train_loss_giou': tensor(0.5646, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.4121, device='cuda:0'), 'validation_loss_ce': tensor(0.4837, device='cuda:0'), 'validation_loss_bbox': tensor(0.1671, device='cuda:0'), 'validation_loss_giou': tensor(0.5463, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.0146, device='cuda:0'), 'train_loss_ce': tensor(0.4475, device='cuda:0'), 'train_loss_bbox': tensor(0.1417, device='cuda:0'), 'train_loss_giou': tensor(0.4294, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.4437, device='cuda:0'), 'validation_loss_ce': tensor(0.4664, device='cuda:0'), 'validation_loss_bbox': tensor(0.1689, device='cuda:0'), 'validation_loss_giou': tensor(0.5664, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.5258, device='cuda:0'), 'train_loss_ce': tensor(0.4352, device='cuda:0'), 'train_loss_bbox': tensor(0.1822, device='cuda:0'), 'train_loss_giou': tensor(0.5898, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.2827, device='cuda:0'), 'validation_loss_ce': tensor(0.4655, device='cuda:0'), 'validation_loss_bbox': tensor(0.1534, device='cuda:0'), 'validation_loss_giou': tensor(0.5252, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.5122, device='cuda:0'), 'train_loss_ce': tensor(0.4750, device='cuda:0'), 'train_loss_bbox': tensor(0.1781, device='cuda:0'), 'train_loss_giou': tensor(0.5734, device='cuda:0'), 'train_cardinality_error': tensor(1.2500, device='cuda:0'), 'validation_loss': tensor(2.3420, device='cuda:0'), 'validation_loss_ce': tensor(0.4609, device='cuda:0'), 'validation_loss_bbox': tensor(0.1545, device='cuda:0'), 'validation_loss_giou': tensor(0.5543, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.5104, device='cuda:0'), 'train_loss_ce': tensor(0.4122, device='cuda:0'), 'train_loss_bbox': tensor(0.1681, device='cuda:0'), 'train_loss_giou': tensor(0.6288, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.2988, device='cuda:0'), 'validation_loss_ce': tensor(0.4562, device='cuda:0'), 'validation_loss_bbox': tensor(0.1513, device='cuda:0'), 'validation_loss_giou': tensor(0.5432, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.5571, device='cuda:0'), 'train_loss_ce': tensor(0.5181, device='cuda:0'), 'train_loss_bbox': tensor(0.1580, device='cuda:0'), 'train_loss_giou': tensor(0.6245, device='cuda:0'), 'train_cardinality_error': tensor(1.3125, device='cuda:0'), 'validation_loss': tensor(2.3666, device='cuda:0'), 'validation_loss_ce': tensor(0.4579, device='cuda:0'), 'validation_loss_bbox': tensor(0.1604, device='cuda:0'), 'validation_loss_giou': tensor(0.5533, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.1376, device='cuda:0'), 'train_loss_ce': tensor(0.5280, device='cuda:0'), 'train_loss_bbox': tensor(0.1437, device='cuda:0'), 'train_loss_giou': tensor(0.4456, device='cuda:0'), 'train_cardinality_error': tensor(1.2500, device='cuda:0'), 'validation_loss': tensor(2.2616, device='cuda:0'), 'validation_loss_ce': tensor(0.4543, device='cuda:0'), 'validation_loss_bbox': tensor(0.1543, device='cuda:0'), 'validation_loss_giou': tensor(0.5179, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.2242, device='cuda:0'), 'train_loss_ce': tensor(0.4644, device='cuda:0'), 'train_loss_bbox': tensor(0.1293, device='cuda:0'), 'train_loss_giou': tensor(0.5567, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.2209, device='cuda:0'), 'validation_loss_ce': tensor(0.4515, device='cuda:0'), 'validation_loss_bbox': tensor(0.1492, device='cuda:0'), 'validation_loss_giou': tensor(0.5117, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.1088, device='cuda:0'), 'train_loss_ce': tensor(0.3916, device='cuda:0'), 'train_loss_bbox': tensor(0.1388, device='cuda:0'), 'train_loss_giou': tensor(0.5116, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.1887, device='cuda:0'), 'validation_loss_ce': tensor(0.4398, device='cuda:0'), 'validation_loss_bbox': tensor(0.1450, device='cuda:0'), 'validation_loss_giou': tensor(0.5119, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.1986, device='cuda:0'), 'train_loss_ce': tensor(0.4151, device='cuda:0'), 'train_loss_bbox': tensor(0.1447, device='cuda:0'), 'train_loss_giou': tensor(0.5301, device='cuda:0'), 'train_cardinality_error': tensor(1.2500, device='cuda:0'), 'validation_loss': tensor(2.1999, device='cuda:0'), 'validation_loss_ce': tensor(0.4299, device='cuda:0'), 'validation_loss_bbox': tensor(0.1486, device='cuda:0'), 'validation_loss_giou': tensor(0.5135, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.0995, device='cuda:0'), 'train_loss_ce': tensor(0.4170, device='cuda:0'), 'train_loss_bbox': tensor(0.1438, device='cuda:0'), 'train_loss_giou': tensor(0.4818, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(2.1373, device='cuda:0'), 'validation_loss_ce': tensor(0.4293, device='cuda:0'), 'validation_loss_bbox': tensor(0.1426, device='cuda:0'), 'validation_loss_giou': tensor(0.4974, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.2508, device='cuda:0'), 'train_loss_ce': tensor(0.4002, device='cuda:0'), 'train_loss_bbox': tensor(0.1417, device='cuda:0'), 'train_loss_giou': tensor(0.5711, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.1380, device='cuda:0'), 'validation_loss_ce': tensor(0.4244, device='cuda:0'), 'validation_loss_bbox': tensor(0.1417, device='cuda:0'), 'validation_loss_giou': tensor(0.5025, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.3045, device='cuda:0'), 'train_loss_ce': tensor(0.4336, device='cuda:0'), 'train_loss_bbox': tensor(0.1572, device='cuda:0'), 'train_loss_giou': tensor(0.5425, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(2.1376, device='cuda:0'), 'validation_loss_ce': tensor(0.4275, device='cuda:0'), 'validation_loss_bbox': tensor(0.1441, device='cuda:0'), 'validation_loss_giou': tensor(0.4948, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.0827, device='cuda:0'), 'train_loss_ce': tensor(0.4346, device='cuda:0'), 'train_loss_bbox': tensor(0.1247, device='cuda:0'), 'train_loss_giou': tensor(0.5122, device='cuda:0'), 'train_cardinality_error': tensor(1.2500, device='cuda:0'), 'validation_loss': tensor(2.0851, device='cuda:0'), 'validation_loss_ce': tensor(0.4186, device='cuda:0'), 'validation_loss_bbox': tensor(0.1376, device='cuda:0'), 'validation_loss_giou': tensor(0.4894, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.2029, device='cuda:0'), 'train_loss_ce': tensor(0.4592, device='cuda:0'), 'train_loss_bbox': tensor(0.1341, device='cuda:0'), 'train_loss_giou': tensor(0.5367, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.0779, device='cuda:0'), 'validation_loss_ce': tensor(0.4182, device='cuda:0'), 'validation_loss_bbox': tensor(0.1365, device='cuda:0'), 'validation_loss_giou': tensor(0.4885, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.3557, device='cuda:0'), 'train_loss_ce': tensor(0.5089, device='cuda:0'), 'train_loss_bbox': tensor(0.1324, device='cuda:0'), 'train_loss_giou': tensor(0.5923, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.1129, device='cuda:0'), 'validation_loss_ce': tensor(0.4233, device='cuda:0'), 'validation_loss_bbox': tensor(0.1375, device='cuda:0'), 'validation_loss_giou': tensor(0.5011, device='cuda:0'), 'validation_cardinality_error': tensor(1.0409, device='cuda:0')}
-{'training_loss': tensor(1.9955, device='cuda:0'), 'train_loss_ce': tensor(0.4479, device='cuda:0'), 'train_loss_bbox': tensor(0.1117, device='cuda:0'), 'train_loss_giou': tensor(0.4946, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(2.0669, device='cuda:0'), 'validation_loss_ce': tensor(0.4158, device='cuda:0'), 'validation_loss_bbox': tensor(0.1365, device='cuda:0'), 'validation_loss_giou': tensor(0.4842, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.1262, device='cuda:0'), 'train_loss_ce': tensor(0.4115, device='cuda:0'), 'train_loss_bbox': tensor(0.1496, device='cuda:0'), 'train_loss_giou': tensor(0.4833, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(2.0470, device='cuda:0'), 'validation_loss_ce': tensor(0.4140, device='cuda:0'), 'validation_loss_bbox': tensor(0.1342, device='cuda:0'), 'validation_loss_giou': tensor(0.4809, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.1451, device='cuda:0'), 'train_loss_ce': tensor(0.4341, device='cuda:0'), 'train_loss_bbox': tensor(0.1283, device='cuda:0'), 'train_loss_giou': tensor(0.5347, device='cuda:0'), 'train_cardinality_error': tensor(1.1250, device='cuda:0'), 'validation_loss': tensor(2.0579, device='cuda:0'), 'validation_loss_ce': tensor(0.4170, device='cuda:0'), 'validation_loss_bbox': tensor(0.1333, device='cuda:0'), 'validation_loss_giou': tensor(0.4873, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.1771, device='cuda:0'), 'train_loss_ce': tensor(0.4315, device='cuda:0'), 'train_loss_bbox': tensor(0.1587, device='cuda:0'), 'train_loss_giou': tensor(0.4760, device='cuda:0'), 'train_cardinality_error': tensor(1.1875, device='cuda:0'), 'validation_loss': tensor(2.0670, device='cuda:0'), 'validation_loss_ce': tensor(0.4111, device='cuda:0'), 'validation_loss_bbox': tensor(0.1353, device='cuda:0'), 'validation_loss_giou': tensor(0.4896, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(1.9001, device='cuda:0'), 'train_loss_ce': tensor(0.3586, device='cuda:0'), 'train_loss_bbox': tensor(0.1362, device='cuda:0'), 'train_loss_giou': tensor(0.4302, device='cuda:0'), 'train_cardinality_error': tensor(1.0625, device='cuda:0'), 'validation_loss': tensor(2.0867, device='cuda:0'), 'validation_loss_ce': tensor(0.4068, device='cuda:0'), 'validation_loss_bbox': tensor(0.1386, device='cuda:0'), 'validation_loss_giou': tensor(0.4934, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.2456, device='cuda:0'), 'train_loss_ce': tensor(0.4781, device='cuda:0'), 'train_loss_bbox': tensor(0.1459, device='cuda:0'), 'train_loss_giou': tensor(0.5189, device='cuda:0'), 'train_cardinality_error': tensor(1.2500, device='cuda:0'), 'validation_loss': tensor(2.0596, device='cuda:0'), 'validation_loss_ce': tensor(0.4129, device='cuda:0'), 'validation_loss_bbox': tensor(0.1373, device='cuda:0'), 'validation_loss_giou': tensor(0.4801, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(2.0215, device='cuda:0'), 'train_loss_ce': tensor(0.3352, device='cuda:0'), 'train_loss_bbox': tensor(0.1555, device='cuda:0'), 'train_loss_giou': tensor(0.4544, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.0185, device='cuda:0'), 'validation_loss_ce': tensor(0.4065, device='cuda:0'), 'validation_loss_bbox': tensor(0.1314, device='cuda:0'), 'validation_loss_giou': tensor(0.4776, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
-{'training_loss': tensor(1.6743, device='cuda:0'), 'train_loss_ce': tensor(0.3426, device='cuda:0'), 'train_loss_bbox': tensor(0.1190, device='cuda:0'), 'train_loss_giou': tensor(0.3684, device='cuda:0'), 'train_cardinality_error': tensor(1., device='cuda:0'), 'validation_loss': tensor(2.0313, device='cuda:0'), 'validation_loss_ce': tensor(0.4118, device='cuda:0'), 'validation_loss_bbox': tensor(0.1326, device='cuda:0'), 'validation_loss_giou': tensor(0.4783, device='cuda:0'), 'validation_cardinality_error': tensor(1.1205, device='cuda:0')}
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 ```