Update app.py
Browse files
app.py
CHANGED
@@ -4,42 +4,43 @@ from PIL import Image
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import gradio as gr
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import os
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#
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payload = {
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"inputs": prompt,
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"parameters": {
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"width": width,
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"height": height,
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"guidance_scale": guidance_scale,
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"num_inference_steps": num_inference_steps,
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},
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}
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# Include negative prompt in the payload if provided
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if negative_prompt:
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payload["parameters"]["negative_prompt"] = negative_prompt
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response = requests.post(API_URL, headers=headers, json=payload)
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image_bytes = response.content
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image = Image.open(io.BytesIO(image_bytes))
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return image
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# Define Gradio interface components
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iface = gr.Interface(
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fn=generate_image,
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inputs=[
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gr.Textbox(label="Prompt", placeholder="Enter your prompt here..."),
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gr.Textbox(label="Negative Prompt", placeholder="Enter a negative prompt here (optional)..."),
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gr.Slider(label="Guidance Scale", minimum=1, maximum=20, step=0.1,
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gr.Slider(label="Width", minimum=768, maximum=1024, step=1,
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gr.Slider(label="Height", minimum=768, maximum=1024, step=1,
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gr.Slider(label="Number of Inference Steps", minimum=20, maximum=50, step=1,
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],
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outputs=gr.Image(type="pil"),
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title="Stable Diffusion XL Image Generator",
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description="Generate images with Stable Diffusion XL. Provide a prompt, optionally specify a negative prompt, and adjust other parameters as desired."
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)
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# Launch the Gradio app
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iface.launch()
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import gradio as gr
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import os
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# Replace "YOUR_HUGGING_FACE_API_TOKEN" with your actual Hugging Face API token
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API_TOKEN = os.getenv("HF_API_TOKEN")
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if not API_TOKEN:
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raise ValueError("Hugging Face API token not found. Please set the HF_API_TOKEN environment variable.")
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API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0"
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headers = {"Authorization": f"Bearer {API_TOKEN}"}
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def generate_image(prompt, negative_prompt, guidance_scale, width, height, num_inference_steps):
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payload = {
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"inputs": prompt,
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"parameters": {
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"negative_prompt": negative_prompt,
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"guidance_scale": guidance_scale,
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"width": width,
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"height": height,
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"num_inference_steps": num_inference_steps,
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},
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}
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response = requests.post(API_URL, headers=headers, json=payload)
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image_bytes = response.content
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image = Image.open(io.BytesIO(image_bytes))
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return image
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iface = gr.Interface(
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fn=generate_image,
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inputs=[
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gr.Textbox(label="Prompt", placeholder="Enter your prompt here..."),
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gr.Textbox(label="Negative Prompt", placeholder="Enter a negative prompt here (optional)...", optional=True),
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gr.Slider(label="Guidance Scale", minimum=1, maximum=20, step=0.1, value=7.5),
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gr.Slider(label="Width", minimum=768, maximum=1024, step=1, value=1024),
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gr.Slider(label="Height", minimum=768, maximum=1024, step=1, value=768),
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gr.Slider(label="Number of Inference Steps", minimum=20, maximum=50, step=1, value=30)
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],
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outputs=gr.Image(type="pil"),
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title="Stable Diffusion XL Image Generator",
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description="Generate images with Stable Diffusion XL. Provide a prompt, optionally specify a negative prompt, and adjust other parameters as desired."
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)
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iface.launch()
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