Bienqq
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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-06-18 16:32:37 +02:00
parent 6efb2c935f
commit 4fb2567aa5
1 changed files with 2 additions and 2 deletions
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train.py
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@ -313,7 +313,7 @@ if __name__ == '__main__':
parser.add_argument('--batch-size', type=int, default=8, help='batch size') parser.add_argument('--batch-size', type=int, default=8, help='batch size')
parser.add_argument('--accumulate', type=int, default=8, help='number of batches to accumulate before optimizing') parser.add_argument('--accumulate', type=int, default=8, help='number of batches to accumulate before optimizing')
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-cfg', type=str, default='data/coco_64img.data', help='coco.data file path') parser.add_argument('--data-cfg', type=str, default='../supermarket2/supermarket2.data', help='coco.data file path')
parser.add_argument('--single-scale', action='store_true', help='train at fixed size (no multi-scale)') parser.add_argument('--single-scale', action='store_true', help='train at fixed size (no multi-scale)')
parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)') parser.add_argument('--img-size', type=int, default=416, help='inference size (pixels)')
parser.add_argument('--resume', action='store_true', help='resume training flag') parser.add_argument('--resume', action='store_true', help='resume training flag')
@ -360,7 +360,7 @@ if __name__ == '__main__':
# Mutate hyperparameters # Mutate hyperparameters
old_hyp = hyp.copy() old_hyp = hyp.copy()
init_seeds(seed=int(time.time())) init_seeds(seed=int(time.time()))
s = [0.5, .5, .5, .5, .5, .5, .5, .5, .05, .5] # xy, wh, cls, conf, iou_t, lr0, lrf, momentum, weight_decay s = [.5, .5, .5, .5, .5, .5, .5, .5, .05, .5] # xy, wh, cls, conf, iou_t, lr0, lrf, momentum, weight_decay
for i, k in enumerate(hyp.keys()): for i, k in enumerate(hyp.keys()):
x = (np.random.randn(1) * s[i] + 1) ** 1.1 # plt.hist(x.ravel(), 100) x = (np.random.randn(1) * s[i] + 1) ** 1.1 # plt.hist(x.ravel(), 100)
hyp[k] = hyp[k] * float(x) # vary by about 30% 1sigma hyp[k] = hyp[k] * float(x) # vary by about 30% 1sigma