Merge pull request #362 from ajsanjoaquin/master

update demo.py and darknet2pytorch.py

demo.py

@@ -17,6 +17,7 @@
 from tool.utils import *
 from tool.torch_utils import *
 from tool.darknet2pytorch import Darknet
+import torch
 import argparse
 
 """hyper parameters"""
@@ -61,7 +62,10 @@ def detect_cv2_camera(cfgfile, weightfile):
     m = Darknet(cfgfile)
 
     m.print_network()
-    m.load_weights(weightfile)
+    if args.torch:
+        m.load_state_dict(torch.load(weightfile))
+    else:
+        m.load_weights(weightfile)
     print('Loading weights from %s... Done!' % (weightfile))
 
     if use_cuda:
@@ -144,6 +148,8 @@ def get_args():
     parser.add_argument('-imgfile', type=str,
                         default='./data/mscoco2017/train2017/190109_180343_00154162.jpg',
                         help='path of your image file.', dest='imgfile')
+    parser.add_argument('-torch', type=bool, default=false,
+                        help='use torch weights')
     args = parser.parse_args()
 
     return args

tool/darknet2pytorch.py

@@ -271,10 +271,12 @@ def create_network(self, blocks):
                     model.add_module('relu{0}'.format(conv_id), nn.ReLU(inplace=True))
                 elif activation == 'mish':
                     model.add_module('mish{0}'.format(conv_id), Mish())
+                elif activation == 'linear':
+                    pass
                 elif activation == 'logistic':
                     model.add_module('sigmoid{0}'.format(conv_id), nn.Sigmoid())
                 else:
-                    print("convalution havn't activate {}".format(activation))
+                    print("No convolutional activation named {}".format(activation))
 
                 prev_filters = filters
                 out_filters.append(prev_filters)