fix bug

demo/model.py

@@ -135,8 +135,8 @@ class Model_all:
 
         # sketch part
         self.model_sketch = Adapter(channels=[320, 640, 1280, 1280][:4], nums_rb=2, ksize=1, sk=True,
-                                    use_conv=False)#.to(device)
-        # self.model_sketch.load_state_dict(torch.load("models/t2iadapter_sketch_sd14v1.pth", map_location=device))
+                                    use_conv=False).to(device)
+        self.model_sketch.load_state_dict(torch.load("models/t2iadapter_sketch_sd14v1.pth", map_location=device))
         self.model_edge = pidinet().to(device)
         self.model_edge.load_state_dict({k.replace('module.', ''): v for k, v in torch.load('models/table5_pidinet.pth', map_location=device)['state_dict'].items()})
 
@@ -144,8 +144,8 @@ class Model_all:
         self.model_seger = seger().to(device)
         self.model_seger.eval()
         self.coler = Colorize(n=182)
-        self.model_seg = Adapter(cin=int(3*64), channels=[320, 640, 1280, 1280][:4], nums_rb=2, ksize=1, sk=True, use_conv=False)#.to(device)
-        # self.model_seg.load_state_dict(torch.load("models/t2iadapter_seg_sd14v1.pth", map_location=device))
+        self.model_seg = Adapter(cin=int(3*64), channels=[320, 640, 1280, 1280][:4], nums_rb=2, ksize=1, sk=True, use_conv=False).to(device)
+        self.model_seg.load_state_dict(torch.load("models/t2iadapter_seg_sd14v1.pth", map_location=device))
         self.depth_model = MiDaSInference(model_type='dpt_hybrid').to(device)
 
         # depth part