Update training_metrics.log

training_metrics.log

@@ -3,22 +3,6 @@ epoch: 0
 class_names: ('empty', 'car', 'bicycle', 'motorcycle', 'truck', 'other-vehicle', 'person', 'bicyclist', 'motorcyclist', 'road', 'parking', 'sidewalk', 'other-ground', 'building', 'fence', 'vegetation', 'trunk', 'terrain', 'pole', 'traffic-sign')
 iou_per_class: ['0.00', '0.29', '0.08', '0.00', '0.00', '0.00', '0.02', '0.01', '0.00', '1.36', '0.00', '0.78', '0.00', '1.67', '0.00', '0.47', '0.49', '0.00', '0.00', '0.00']
 epoch: 0
-{'test/Precision': tensor(0.6153, device='cuda:3'), 'test/Recall': tensor(0.6188, device='cuda:3'), 'test/IoU': tensor(0.4462, device='cuda:3'), 'test/mIoU': tensor(0.1639, device='cuda:3')}
-class_names: ('empty', 'car', 'bicycle', 'motorcycle', 'truck', 'other-vehicle', 'person', 'bicyclist', 'motorcyclist', 'road', 'parking', 'sidewalk', 'other-ground', 'building', 'fence', 'vegetation', 'trunk', 'terrain', 'pole', 'traffic-sign')
-iou_per_class: ['93.64', '32.16', '1.41', '4.93', '19.90', '15.74', '3.42', '2.48', '0.00', '59.85', '22.83', '29.91', '1.17', '24.33', '10.81', '27.35', '6.10', '35.11', '9.01', '4.86']
-epoch: 0
-{'test/Precision': tensor(0.6153, device='cuda:1'), 'test/Recall': tensor(0.6188, device='cuda:1'), 'test/IoU': tensor(0.4462, device='cuda:1'), 'test/mIoU': tensor(0.1639, device='cuda:1')}
-class_names: ('empty', 'car', 'bicycle', 'motorcycle', 'truck', 'other-vehicle', 'person', 'bicyclist', 'motorcyclist', 'road', 'parking', 'sidewalk', 'other-ground', 'building', 'fence', 'vegetation', 'trunk', 'terrain', 'pole', 'traffic-sign')
-iou_per_class: ['93.64', '32.16', '1.41', '4.93', '19.90', '15.74', '3.42', '2.48', '0.00', '59.85', '22.83', '29.91', '1.17', '24.33', '10.81', '27.35', '6.10', '35.11', '9.01', '4.86']
-epoch: 0
-{'test/Precision': tensor(0.6153, device='cuda:2'), 'test/Recall': tensor(0.6188, device='cuda:2'), 'test/IoU': tensor(0.4462, device='cuda:2'), 'test/mIoU': tensor(0.1639, device='cuda:2')}
-class_names: ('empty', 'car', 'bicycle', 'motorcycle', 'truck', 'other-vehicle', 'person', 'bicyclist', 'motorcyclist', 'road', 'parking', 'sidewalk', 'other-ground', 'building', 'fence', 'vegetation', 'trunk', 'terrain', 'pole', 'traffic-sign')
-iou_per_class: ['93.64', '32.16', '1.41', '4.93', '19.90', '15.74', '3.42', '2.48', '0.00', '59.85', '22.83', '29.91', '1.17', '24.33', '10.81', '27.35', '6.10', '35.11', '9.01', '4.86']
-epoch: 0
-{'test/Precision': tensor(0.6153, device='cuda:0'), 'test/Recall': tensor(0.6188, device='cuda:0'), 'test/IoU': tensor(0.4462, device='cuda:0'), 'test/mIoU': tensor(0.1639, device='cuda:0')}
-class_names: ('empty', 'car', 'bicycle', 'motorcycle', 'truck', 'other-vehicle', 'person', 'bicyclist', 'motorcyclist', 'road', 'parking', 'sidewalk', 'other-ground', 'building', 'fence', 'vegetation', 'trunk', 'terrain', 'pole', 'traffic-sign')
-iou_per_class: ['93.64', '32.16', '1.41', '4.93', '19.90', '15.74', '3.42', '2.48', '0.00', '59.85', '22.83', '29.91', '1.17', '24.33', '10.81', '27.35', '6.10', '35.11', '9.01', '4.86']
-epoch: 0
 {'val/Precision': tensor(0.4890, device='cuda:0'), 'val/Recall': tensor(0.6651, device='cuda:0'), 'val/IoU': tensor(0.3924, device='cuda:0'), 'val/mIoU': tensor(0.1035, device='cuda:0')}
 class_names: ('empty', 'car', 'bicycle', 'motorcycle', 'truck', 'other-vehicle', 'person', 'bicyclist', 'motorcyclist', 'road', 'parking', 'sidewalk', 'other-ground', 'building', 'fence', 'vegetation', 'trunk', 'terrain', 'pole', 'traffic-sign')
 iou_per_class: ['91.44', '24.85', '0.16', '0.10', '1.25', '2.21', '0.94', '0.26', '0.00', '51.27', '7.64', '25.71', '0.34', '15.82', '4.69', '21.43', '3.96', '28.74', '5.02', '2.33']