theoracle commited on
Commit
bdeeec9
·
1 Parent(s): 32fca66

Add GPU decorators and update inpainting pipeline

Browse files
__pycache__/background_edit.cpython-310.pyc CHANGED
Binary files a/__pycache__/background_edit.cpython-310.pyc and b/__pycache__/background_edit.cpython-310.pyc differ
 
__pycache__/inference.cpython-310.pyc CHANGED
Binary files a/__pycache__/inference.cpython-310.pyc and b/__pycache__/inference.cpython-310.pyc differ
 
__pycache__/utils.cpython-310.pyc CHANGED
Binary files a/__pycache__/utils.cpython-310.pyc and b/__pycache__/utils.cpython-310.pyc differ
 
background_edit.py CHANGED
@@ -37,6 +37,7 @@ inpaint_pipe = StableDiffusionXLInpaintPipeline.from_pretrained(
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  use_auth_token=os.getenv("HF_TOKEN")
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  ).to("cuda")
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  def run_background_removal_and_inpaint(image_path, prompt, negative_prompt, guidance_scale=10):
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  if not image_path or not os.path.isfile(image_path):
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  raise gr.Error("No valid image found. Please run Step 1 first.")
@@ -69,6 +70,7 @@ def run_background_removal_and_inpaint(image_path, prompt, negative_prompt, guid
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  return result
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  def run_clothing_inpaint(image, prompt, negative_prompt, guidance):
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  try:
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  print("[INFO] Step 3: Clothing segmentation and inpainting...", flush=True)
 
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  use_auth_token=os.getenv("HF_TOKEN")
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  ).to("cuda")
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+ @spaces.GPU
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  def run_background_removal_and_inpaint(image_path, prompt, negative_prompt, guidance_scale=10):
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  if not image_path or not os.path.isfile(image_path):
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  raise gr.Error("No valid image found. Please run Step 1 first.")
 
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  return result
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+ @spaces.GPU
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  def run_clothing_inpaint(image, prompt, negative_prompt, guidance):
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  try:
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  print("[INFO] Step 3: Clothing segmentation and inpainting...", flush=True)
inference.py CHANGED
@@ -18,6 +18,7 @@ pipe = AutoPipelineForImage2Image.from_pretrained(
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  pipe.load_lora_weights("theoracle/sdxl-lora-headshot")
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  def generate_with_lora(image, prompt, negative_prompt, strength, guidance_scale):
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  try:
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  if image is None:
 
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  pipe.load_lora_weights("theoracle/sdxl-lora-headshot")
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+ @spaces.GPU
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  def generate_with_lora(image, prompt, negative_prompt, strength, guidance_scale):
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  try:
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  if image is None: