Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -117,7 +117,7 @@ def get_random_hex():
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random_hex = random_bytes.hex()
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return random_hex
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-
@spaces.GPU(duration=
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def run_full(image: str, seed: int = 0, num_inference_steps: int = 50, guidance_scale: float = 7.5, simplify: bool = True, target_face_num: int = DEFAULT_FACE_NUMBER, req=None):
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try:
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image_seg = prepare_image(image, bg_color=np.array([1.0, 1.0, 1.0]), rmbg_net=rmbg_net)
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@@ -337,7 +337,7 @@ def run_segmentation(image):
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logger.error(f"Error in run_segmentation: {str(e)}")
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raise
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-
@spaces.GPU(duration=
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@torch.no_grad()
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def image_to_3d(
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image, # Changed to accept FileData dict or PIL Image
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@@ -391,7 +391,7 @@ def image_to_3d(
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logger.error(f"Error in image_to_3d: {str(e)}")
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raise
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-
@spaces.GPU(duration=
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@torch.no_grad()
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def run_texture(image: Image, mesh_path: str, seed: int, req: gr.Request):
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try:
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@@ -485,7 +485,7 @@ def run_texture(image: Image, mesh_path: str, seed: int, req: gr.Request):
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logger.error(f"Error in run_texture: {str(e)}")
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raise
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-
@spaces.GPU(duration=
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@torch.no_grad()
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def run_full_api(image, seed: int = 0, num_inference_steps: int = 50, guidance_scale: float = 7.5, simplify: bool = True, target_face_num: int = DEFAULT_FACE_NUMBER, req: gr.Request = None):
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try:
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random_hex = random_bytes.hex()
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return random_hex
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+
@spaces.GPU(duration=3)
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def run_full(image: str, seed: int = 0, num_inference_steps: int = 50, guidance_scale: float = 7.5, simplify: bool = True, target_face_num: int = DEFAULT_FACE_NUMBER, req=None):
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try:
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image_seg = prepare_image(image, bg_color=np.array([1.0, 1.0, 1.0]), rmbg_net=rmbg_net)
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logger.error(f"Error in run_segmentation: {str(e)}")
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raise
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+
@spaces.GPU(duration=3)
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@torch.no_grad()
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def image_to_3d(
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image, # Changed to accept FileData dict or PIL Image
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logger.error(f"Error in image_to_3d: {str(e)}")
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raise
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+
@spaces.GPU(duration=3)
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@torch.no_grad()
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def run_texture(image: Image, mesh_path: str, seed: int, req: gr.Request):
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try:
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logger.error(f"Error in run_texture: {str(e)}")
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raise
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+
@spaces.GPU(duration=3)
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@torch.no_grad()
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def run_full_api(image, seed: int = 0, num_inference_steps: int = 50, guidance_scale: float = 7.5, simplify: bool = True, target_face_num: int = DEFAULT_FACE_NUMBER, req: gr.Request = None):
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try:
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