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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-08-06 14:35:18 +02:00
parent 68a5f8e207
commit bd2d3cc5d1
1 changed files with 2 additions and 2 deletions
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train.py
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@ -205,7 +205,7 @@ def train(cfg,
model_info(model, report='summary') # 'full' or 'summary' model_info(model, report='summary') # 'full' or 'summary'
nb = len(dataloader) nb = len(dataloader)
maps = np.zeros(nc) # mAP per class maps = np.zeros(nc) # mAP per class
results = (0, 0, 0, 0, 0) # P, R, mAP, F1, test_loss results = (0, 0, 0, 0, 0, 0, 0) # P, R, mAP, F1, test_loss
# n_burnin = min(round(nb / 5 + 1), 1000) # burn-in batches # n_burnin = min(round(nb / 5 + 1), 1000) # burn-in batches
t0 = time.time() t0 = time.time()
for epoch in range(start_epoch, epochs): for epoch in range(start_epoch, epochs):
@ -341,7 +341,7 @@ if __name__ == '__main__':
parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path') parser.add_argument('--cfg', type=str, default='cfg/yolov3-spp.cfg', help='cfg file path')
parser.add_argument('--data', type=str, default='data/coco.data', help='coco.data file path') parser.add_argument('--data', type=str, default='data/coco.data', help='coco.data file path')
parser.add_argument('--multi-scale', action='store_true', help='train at (1/1.5)x - 1.5x sizes') parser.add_argument('--multi-scale', action='store_true', help='train at (1/1.5)x - 1.5x sizes')
parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)') parser.add_argument('--img-size', type=int, default=320, help='inference size (pixels)')
parser.add_argument('--rect', action='store_true', help='rectangular training') parser.add_argument('--rect', action='store_true', help='rectangular training')
parser.add_argument('--resume', action='store_true', help='resume training flag') parser.add_argument('--resume', action='store_true', help='resume training flag')
parser.add_argument('--transfer', action='store_true', help='transfer learning flag') parser.add_argument('--transfer', action='store_true', help='transfer learning flag')