Update app.py

app.py

@@ -84,22 +84,12 @@ def preprocess_image(image, target_width, target_height, resize_to_224=False):
     image = torch.from_numpy(image).to(device)
     return image
 
-# def get_depth_map(image, depth_estimator):
-#     image = depth_estimator(image)["depth"]
-#     image = np.array(image)
-#     image = image[:, :, None]
-#     image = np.concatenate([image, image, image], axis=2)
-#     detected_map = torch.from_numpy(image).float() / 255.0
-#     depth_map = detected_map.permute(2, 0, 1)
-#     return depth_map
-
 def get_depth_map(image, depth_estimator):
     # Преобразуем изображение в PIL, если это необходимо
     if isinstance(image, np.ndarray):
         image = Image.fromarray(image)
     elif isinstance(image, torch.Tensor):
         image = Image.fromarray(image.cpu().numpy())
-    
     # Получаем карту глубины
     depth_map = depth_estimator(image)["depth"]
     depth_map = np.array(depth_map)
@@ -411,7 +401,7 @@ def infer(
                     pipe_controlnet = StableDiffusionControlNetPipeline.from_pretrained(
                         "stable-diffusion-v1-5/stable-diffusion-v1-5", 
                         controlnet=controlnet, 
-                        torch_dtype=torch.float16, 
+                        torch_dtype=torch_dtype, 
                         use_safetensors=True
                     ).to(device)
 
@@ -440,10 +430,6 @@ def infer(
 
                         print('control_mode = ', control_mode)
 
-                        # # Преобразуем изображения
-                        # cn_source_image = preprocess_image(cn_source_image, width, height)
-                        # control_image = preprocess_image(control_image, width, height)
-
                         depth_estimator = pipeline("depth-estimation")
                         depth_map = get_depth_map(control_image, depth_estimator).unsqueeze(0).half().to(device)
 
@@ -455,7 +441,7 @@ def infer(
                         pipe_controlnet = StableDiffusionControlNetImg2ImgPipeline.from_pretrained(
                             "stable-diffusion-v1-5/stable-diffusion-v1-5",
                             controlnet=controlnet,
-                            torch_dtype=torch.float16,
+                            torch_dtype=torch_dtype,
                             use_safetensors=True
                         ).to(device)