updates
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@ -552,6 +552,15 @@ def get_yolo_layers(model):
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return [i for i, x in enumerate(bool_vec) if x] # [82, 94, 106] for yolov3
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return [i for i, x in enumerate(bool_vec) if x] # [82, 94, 106] for yolov3
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def print_model_biases(model):
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# prints the bias neurons preceding each yolo layer
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for l in model.yolo_layers: # print pretrained biases
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b = model.module_list[l - 1][0].bias.view(3, -1) # bias 3x85
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print('regression: %.2f+/-%.2f, ' % (b[:, :4].mean(), b[:, :4].std()),
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'objectness: %.2f+/-%.2f, ' % (b[:, 4].mean(), b[:, 4].std()),
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'classification: %.2f+/-%.2f' % (b[:, 5:].mean(), b[:, 5:].std()))
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def strip_optimizer_from_checkpoint(filename='weights/best.pt'):
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def strip_optimizer_from_checkpoint(filename='weights/best.pt'):
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# Strip optimizer from *.pt files for lighter files (reduced by 2/3 size)
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# Strip optimizer from *.pt files for lighter files (reduced by 2/3 size)
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a = torch.load(filename, map_location='cpu')
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a = torch.load(filename, map_location='cpu')
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