Spaces:
Running
on
A100
Running
on
A100
upda
Browse files
app.py
CHANGED
@@ -50,12 +50,14 @@ except ImportError as e:
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BASE_DIR = os.environ.get('HUNYUANIMAGE_V2_1_MODEL_ROOT', './ckpts')
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class CheckpointDownloader:
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"""Handles downloading of all required checkpoints for HunyuanImage."""
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def __init__(self, base_dir: str = BASE_DIR):
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self.base_dir = Path(base_dir)
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self.base_dir.mkdir(exist_ok=True)
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# Define all required checkpoints
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self.checkpoints = {
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@@ -215,6 +217,7 @@ class HunyuanImageApp:
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) -> Tuple[Optional[Image.Image], str]:
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"""Generate an image using the HunyuanImage pipeline."""
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try:
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if self.pipeline is None:
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return None, "Pipeline not loaded. Please try again."
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@@ -252,6 +255,8 @@ class HunyuanImageApp:
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) -> Tuple[str, str]:
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"""Enhance a prompt using the reprompt model."""
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try:
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# Load pipeline if needed
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if self.pipeline is None:
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return prompt, "Pipeline not loaded. Please try again."
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@@ -284,7 +289,9 @@ class HunyuanImageApp:
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try:
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if image is None:
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return None, "Please upload an image to refine."
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-
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# Resize image to target dimensions if needed
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if image.size != (width, height):
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image = image.resize((width, height), Image.Resampling.LANCZOS)
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@@ -631,7 +638,7 @@ if __name__ == "__main__":
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demo.launch(
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server_name=args.host,
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-
server_port=args.port,
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share=False,
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show_error=True,
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quiet=False,
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BASE_DIR = os.environ.get('HUNYUANIMAGE_V2_1_MODEL_ROOT', './ckpts')
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+
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class CheckpointDownloader:
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"""Handles downloading of all required checkpoints for HunyuanImage."""
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def __init__(self, base_dir: str = BASE_DIR):
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self.base_dir = Path(base_dir)
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self.base_dir.mkdir(exist_ok=True)
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print(f'Downloading checkpoints to: {self.base_dir}')
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# Define all required checkpoints
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self.checkpoints = {
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) -> Tuple[Optional[Image.Image], str]:
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"""Generate an image using the HunyuanImage pipeline."""
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try:
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torch.cuda.empty_cache()
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if self.pipeline is None:
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return None, "Pipeline not loaded. Please try again."
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) -> Tuple[str, str]:
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"""Enhance a prompt using the reprompt model."""
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try:
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torch.cuda.empty_cache()
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# Load pipeline if needed
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if self.pipeline is None:
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return prompt, "Pipeline not loaded. Please try again."
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try:
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if image is None:
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return None, "Please upload an image to refine."
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+
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torch.cuda.empty_cache()
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# Resize image to target dimensions if needed
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if image.size != (width, height):
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image = image.resize((width, height), Image.Resampling.LANCZOS)
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demo.launch(
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server_name=args.host,
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# server_port=args.port,
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share=False,
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show_error=True,
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quiet=False,
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