updates
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6
train.py
6
train.py
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@ -37,10 +37,10 @@ except:
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hyp = {'giou': 1.582, # giou loss gain
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'xy': 4.688, # xy loss gain
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'wh': 0.1857, # wh loss gain
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'cls': 27.76, # cls loss gain (CE=~1.0, uCE=~20, uBCE=~200,~30)
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'cls': 27.76, # cls loss gain (CE=~1.0, uCE=~20)
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'cls_pw': 1.446, # cls BCELoss positive_weight
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'obj': 21.35, # obj loss gain
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'obj_pw': 3.941, # obj BCELoss positive_weight
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'obj_pw': 3.941, # obj BCELoss positive_weight (*=80 for uBCE with 80 classes)
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'iou_t': 0.2635, # iou training threshold
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'lr0': 0.002324, # initial learning rate
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'lrf': -4., # final LambdaLR learning rate = lr0 * (10 ** lrf)
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@ -362,7 +362,7 @@ if __name__ == '__main__':
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parser.add_argument('--batch-size', type=int, default=32, help='batch size')
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parser.add_argument('--accumulate', type=int, default=2, help='number of 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('--data', type=str, default='data/coco.data', help='coco.data file path')
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parser.add_argument('--data', type=str, default='../out/data.data', help='coco.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('--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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