Fix hyp file read in and dict update.

new_hyp.yaml

@@ -0,0 +1,18 @@
+anchor_t: 10.0
+cls: 0.58
+cls_pw: 1.0
+degrees: 20.0
+fl_gamma: 1.0
+giou: 0.15
+hsv_h: 0.014
+hsv_s: 0.68
+hsv_v: 0.36
+iou_t: 0.2
+lr0: 0.001
+momentum: 0.900
+obj: 1.0
+obj_pw: 1.0
+scale: 0.5
+shear: 0.0
+translate: 0.0
+weight_decay: 0.000625

train.py

@@ -408,6 +408,7 @@ if __name__ == '__main__':
     opt.cfg = check_file(opt.cfg)  # check file
     opt.data = check_file(opt.data)  # check file
     opt.hyp = check_file(opt.hyp) if opt.hyp else '' #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)
@@ -419,7 +420,10 @@ if __name__ == '__main__':
         tb_writer = SummaryWriter(comment=opt.name)
         
         #updates hyp defaults from hyp.yaml
-        if opt.hyp: hyp.update(opt.hyp)
+        if opt.hyp:
+            with open(opt.hyp) as f:
+                updated_hyp = yaml.load(f, Loader=yaml.FullLoader)
+                hyp.update(updated_hyp)
 
         # Print focal loss if gamma > 0
         if hyp['fl_gamma']: