updates
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fd653eca8a
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8
train.py
8
train.py
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@ -250,7 +250,7 @@ def train():
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imgs = F.interpolate(imgs, size=ns, mode='bilinear', align_corners=False)
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imgs = F.interpolate(imgs, size=ns, mode='bilinear', align_corners=False)
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# Plot images with bounding boxes
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# Plot images with bounding boxes
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if epoch == 0 and i == 0:
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if ni == 0:
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fname = 'train_batch%g.jpg' % i
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fname = 'train_batch%g.jpg' % i
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plot_images(imgs=imgs, targets=targets, paths=paths, fname=fname)
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plot_images(imgs=imgs, targets=targets, paths=paths, fname=fname)
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if tb_writer:
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if tb_writer:
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@ -284,7 +284,7 @@ def train():
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loss.backward()
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loss.backward()
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# Accumulate gradient for x batches before optimizing
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# Accumulate gradient for x batches before optimizing
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if (i + 1) % accumulate == 0 or (i + 1) == nb:
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if ni % accumulate == 0:
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optimizer.step()
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optimizer.step()
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optimizer.zero_grad()
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optimizer.zero_grad()
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@ -305,7 +305,7 @@ def train():
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img_size=opt.img_size,
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img_size=opt.img_size,
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model=model,
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model=model,
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conf_thres=0.001 if final_epoch and epoch > 0 else 0.1, # 0.1 for speed
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conf_thres=0.001 if final_epoch and epoch > 0 else 0.1, # 0.1 for speed
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save_json=final_epoch and 'coco.data' in data)
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save_json=final_epoch and epoch > 0 and 'coco.data' in data)
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# Write epoch results
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# Write epoch results
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with open('results.txt', 'a') as file:
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with open('results.txt', 'a') as file:
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@ -366,7 +366,7 @@ if __name__ == '__main__':
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parser.add_argument('--accumulate', type=int, default=2, help='batches to accumulate before optimizing')
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parser.add_argument('--accumulate', type=int, default=2, help='batches to accumulate before optimizing')
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parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
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parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
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parser.add_argument('--data', type=str, default='data/coco.data', help='*.data file path')
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parser.add_argument('--data', type=str, default='data/coco.data', help='*.data file path')
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parser.add_argument('--multi-scale', action='store_true', help='train at (1/1.5)x - 1.5x sizes')
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parser.add_argument('--multi-scale', action='store_true', help='adjust (67% - 150%) img_size every 10 batches')
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parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
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parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
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parser.add_argument('--rect', action='store_true', help='rectangular training')
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parser.add_argument('--rect', action='store_true', help='rectangular training')
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parser.add_argument('--resume', action='store_true', help='resume training from last.pt')
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parser.add_argument('--resume', action='store_true', help='resume training from last.pt')
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