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add parser arg for hyp yaml file

pull/104/head
Alex Stoken 2020-06-16 14:53:32 -05:00
parent 8b26e89006
commit a85e6d0fc0
1 changed files with 5 additions and 1 deletions
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6
train.py
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@ -43,7 +43,9 @@ hyp = {'lr0': 0.01, # initial learning rate (SGD=1E-2, Adam=1E-3)
'translate': 0.0, # image translation (+/- fraction)
'scale': 0.5, # image scale (+/- gain)
'shear': 0.0} # image shear (+/- deg)
print(hyp)
# Don't need to be printing every time
#print(hyp)
# Overwrite hyp with hyp*.txt (optional)
f = glob.glob('hyp*.txt')
@ -382,10 +384,12 @@ if __name__ == '__main__':
parser.add_argument('--adam', action='store_true', help='use adam optimizer')
parser.add_argument('--multi-scale', action='store_true', help='vary img-size +/- 50%')
parser.add_argument('--single-cls', action='store_true', help='train as single-class dataset')
parser.add_argument('--hyp', type=str, default='', help ='path to hyp yaml file')
opt = parser.parse_args()
opt.weights = last if opt.resume else opt.weights
opt.cfg = check_file(opt.cfg) # check file
opt.data = check_file(opt.data) # check file
opt.hyp = check_file(opt.hyp) #check file
print(opt)
opt.img_size.extend([opt.img_size[-1]] * (2 - len(opt.img_size))) # extend to 2 sizes (train, test)
device = torch_utils.select_device(opt.device, apex=mixed_precision, batch_size=opt.batch_size)