Merge remote-tracking branch 'origin/master'
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commit
c7f8dfcb87
@ -106,6 +106,9 @@ def create_modules(module_defs, img_size, cfg):
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# Initialize preceding Conv2d() bias (https://arxiv.org/pdf/1708.02002.pdf section 3.3)
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try:
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j = layers[yolo_index] if 'from' in mdef else -1
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# If previous layer is a dropout layer, get the one before
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if module_list[j].__class__.__name__ == 'Dropout':
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j -= 1
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bias_ = module_list[j][0].bias # shape(255,)
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bias = bias_[:modules.no * modules.na].view(modules.na, -1) # shape(3,85)
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bias[:, 4] += -4.5 # obj
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@ -114,6 +117,9 @@ def create_modules(module_defs, img_size, cfg):
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except:
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print('WARNING: smart bias initialization failure.')
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elif mdef['type'] == 'dropout':
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perc = float(mdef['probability'])
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modules = nn.Dropout(p=perc)
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else:
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print('Warning: Unrecognized Layer Type: ' + mdef['type'])
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@ -31,6 +31,7 @@ def parse_model_cfg(path):
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mdefs[-1][key] = [int(x) for x in val.split(',')]
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else:
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val = val.strip()
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# TODO: .isnumeric() actually fails to get the float case
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if val.isnumeric(): # return int or float
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mdefs[-1][key] = int(val) if (int(val) - float(val)) == 0 else float(val)
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else:
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@ -40,7 +41,7 @@ def parse_model_cfg(path):
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supported = ['type', 'batch_normalize', 'filters', 'size', 'stride', 'pad', 'activation', 'layers', 'groups',
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'from', 'mask', 'anchors', 'classes', 'num', 'jitter', 'ignore_thresh', 'truth_thresh', 'random',
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'stride_x', 'stride_y', 'weights_type', 'weights_normalization', 'scale_x_y', 'beta_nms', 'nms_kind',
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'iou_loss', 'iou_normalizer', 'cls_normalizer', 'iou_thresh']
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'iou_loss', 'iou_normalizer', 'cls_normalizer', 'iou_thresh', 'probability']
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f = [] # fields
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for x in mdefs[1:]:
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