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Runtime error
Update app.py
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app.py
CHANGED
@@ -179,9 +179,15 @@ global pipeline
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global MultiResNetModel
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global causal_dit
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global controlnet
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@spaces.GPU
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def load_ckpt():
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weight_dtype = torch.float16
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block_out_channels = [128, 128, 256, 512, 512]
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@@ -292,11 +298,14 @@ def load_ckpt():
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print('loaded pipeline')
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load_ckpt()
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-
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global cur_style
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cur_style = 'line + shadow'
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@spaces.GPU
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def change_ckpt(style):
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weight_dtype = torch.float16
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if style == 'line':
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@@ -348,6 +357,11 @@ def process_multi_images(files):
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@spaces.GPU
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def extract_lines(image):
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src = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2GRAY)
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rows = int(np.ceil(src.shape[0] / 16)) * 16
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@@ -373,6 +387,11 @@ def extract_lines(image):
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@spaces.GPU
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def extract_line_image(query_image_, resolution):
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tar_width, tar_height = resolution
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query_image = query_image_.resize((tar_width, tar_height))
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query_image = query_image.convert('L').convert('RGB')
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@@ -418,6 +437,11 @@ def extract_sketch_line_image(query_image_, input_style):
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@spaces.GPU(duration=120)
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def colorize_image(extracted_line, reference_images, resolution, seed, num_inference_steps, top_k, hint_mask=None, hint_color=None, query_image_origin=None, extracted_image_ori=None):
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if extracted_line is None:
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gr.Info("Please preprocess the image first")
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raise ValueError("Please preprocess the image first")
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global MultiResNetModel
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global causal_dit
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global controlnet
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global cur_style
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@spaces.GPU
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def load_ckpt():
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global pipeline
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global MultiResNetModel
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global causal_dit
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global controlnet
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global cur_style
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weight_dtype = torch.float16
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block_out_channels = [128, 128, 256, 512, 512]
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print('loaded pipeline')
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load_ckpt()
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cur_style = 'line + shadow'
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@spaces.GPU
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def change_ckpt(style):
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global pipeline
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global MultiResNetModel
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global causal_dit
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global controlnet
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global cur_style
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weight_dtype = torch.float16
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if style == 'line':
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@spaces.GPU
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def extract_lines(image):
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global pipeline
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global MultiResNetModel
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global causal_dit
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global controlnet
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global cur_style
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src = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2GRAY)
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rows = int(np.ceil(src.shape[0] / 16)) * 16
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@spaces.GPU
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def extract_line_image(query_image_, resolution):
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global pipeline
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global MultiResNetModel
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global causal_dit
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global controlnet
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global cur_style
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tar_width, tar_height = resolution
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query_image = query_image_.resize((tar_width, tar_height))
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query_image = query_image.convert('L').convert('RGB')
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@spaces.GPU(duration=120)
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def colorize_image(extracted_line, reference_images, resolution, seed, num_inference_steps, top_k, hint_mask=None, hint_color=None, query_image_origin=None, extracted_image_ori=None):
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global pipeline
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global MultiResNetModel
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global causal_dit
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global controlnet
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global cur_style
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if extracted_line is None:
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gr.Info("Please preprocess the image first")
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raise ValueError("Please preprocess the image first")
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