add parser arg for hyp yaml file

train.py

@@ -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)