Update app.py

app.py

@@ -403,9 +403,10 @@ def infer(
 
             # #control_mode = "pose_estimation" # Режим работы ControlNet 
 
-            if control_mode.value == "pose_estimation":    
+            #if control_mode.value == "pose_estimation": 
+            if control_mode == "pose_estimation":     
 
-                print('control_mode.value = ', control_mode.value)
+                print('control_mode = ', control_mode)
 
                 # Инициализация ControlNet
                 controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-openpose", torch_dtype=torch_dtype)
@@ -488,9 +489,10 @@ def infer(
 
                 # #control_mode = "edge_detection" # Режим работы ControlNet 
 
-                if control_mode.value == "edge_detection": 
+                #if control_mode.value == "edge_detection": 
+                if control_mode == "edge_detection":     
 
-                    print('control_mode.value = ', control_mode.value)
+                    print('control_mode = ', control_mode)
 
                     controlnet = ControlNetModel.from_pretrained("lllyasviel/sd-controlnet-canny", torch_dtype=torch.float16, use_safetensors=True)
 
@@ -539,9 +541,10 @@ def infer(
 
                     # #control_mode = "depth_map" # Режим работы ControlNet 
 
-                    if control_mode.value == "depth_map": 
+                    #if control_mode.value == "depth_map": 
+                    if control_mode == "depth_map":     
 
-                        print('control_mode.value = ', control_mode.value)
+                        print('control_mode = ', control_mode)
 
                         depth_estimator = pipeline("depth-estimation")
                         depth_map = get_depth_map(control_image, depth_estimator).unsqueeze(0).half().to(device)