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3432643
1
Parent(s):
e55ec3c
Update app.py
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app.py
CHANGED
@@ -1,25 +1,29 @@
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import gradio as gr
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from PIL import Image
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from diffusers import DiffusionPipeline
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# Load model and scheduler
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ldm = DiffusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256")
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def generate_image(prompt, negative_prompt="Low quality", width=512, height=512):
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# Run pipeline in inference (sample random noise and denoise)
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images = ldm([prompt], num_inference_steps=50, eta=0.3, guidance_scale=6, negative_prompts=[negative_prompt]).images
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# Resize image to desired width and height
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resized_images = [image.resize((int(width), int(height))) for image in images]
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# Save images
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for idx, image in enumerate(resized_images):
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image.save(f"squirrel-{idx}.png")
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# Define the interface
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iface = gr.Interface(
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fn=generate_image,
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inputs=["text", "text", "number", "number"],
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outputs="
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layout="vertical",
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title="Image Generation",
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description="Generate images based on prompts.",
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import gradio as gr
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from PIL import Image
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from diffusers import DiffusionPipeline
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import time
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# Load model and scheduler
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ldm = DiffusionPipeline.from_pretrained("CompVis/ldm-text2im-large-256")
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def generate_image(prompt, negative_prompt="Low quality", width=512, height=512):
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# Run pipeline in inference (sample random noise and denoise)
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start_time = time.time()
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images = ldm([prompt], num_inference_steps=50, eta=0.3, guidance_scale=6, negative_prompts=[negative_prompt]).images
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# Resize image to desired width and height
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resized_images = [image.resize((int(width), int(height))) for image in images]
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# Save images
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for idx, image in enumerate(resized_images):
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image.save(f"squirrel-{idx}.png")
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end_time = time.time()
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elapsed_time = round(end_time - start_time, 2)
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return f"Images generated successfully! (Elapsed Time: {elapsed_time} seconds)"
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# Define the interface
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iface = gr.Interface(
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fn=generate_image,
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inputs=["text", "text", "number", "number"],
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outputs=gr.outputs.Image(label="Generated Image"),
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layout="vertical",
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title="Image Generation",
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description="Generate images based on prompts.",
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