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Browse files- check_app.py +16 -2
check_app.py
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@@ -15,7 +15,9 @@ from diffusers import (
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import gradio as gr
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from diffusers.pipelines.pipeline_utils import DiffusionPipeline
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-
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MAX_SEED = np.iinfo(np.int32).max
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MAX_IMAGE_SIZE = 1024
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@@ -163,7 +165,8 @@ def generate_image_with_progress(model_name,pipe, prompt, num_steps, guidance_sc
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# Generate image
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image = pipe(**common_args).images[0]
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return seed, image
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@spaces.GPU(duration=170)
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@@ -264,6 +267,17 @@ def main():
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app.launch()
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if __name__ == "__main__":
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main()
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)
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import gradio as gr
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from diffusers.pipelines.pipeline_utils import DiffusionPipeline
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from pathlib import Path
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import time
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from datetime import datetime
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MAX_SEED = np.iinfo(np.int32).max
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MAX_IMAGE_SIZE = 1024
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# Generate image
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image = pipe(**common_args).images[0]
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filepath = save_generated_image(image, model_name, prompt)
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print(f"Saved image to: {filepath}")
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return seed, image
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@spaces.GPU(duration=170)
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app.launch()
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def save_generated_image(image, model_name, prompt):
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"""Save generated image with timestamp and model name"""
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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# Create sanitized filename from prompt (first 30 chars)
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prompt_part = "".join(c for c in prompt[:30] if c.isalnum() or c in (' ', '-', '_')).strip()
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filename = f"{timestamp}_{model_name}_{prompt_part}.png"
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path = Path(model_name)
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path.mkdir(parents=True, exist_ok=True)
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filepath = os.path.join(model_name, filename)
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image.save(filepath)
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return filepath
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if __name__ == "__main__":
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main()
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