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| import gradio as gr | |
| import numpy as np | |
| from PIL import Image | |
| import io | |
| from huggingface_hub import InferenceClient | |
| # Initialize client | |
| client = InferenceClient() | |
| def segment_and_edit(image, prompt): | |
| """ | |
| Fast interior design editor using Hugging Face Inference API | |
| """ | |
| try: | |
| # Convert PIL to bytes | |
| img_byte_arr = io.BytesIO() | |
| image.save(img_byte_arr, format='PNG') | |
| img_byte_arr = img_byte_arr.getvalue() | |
| # Use a free, public model for image-to-image | |
| edited_image = client.image_to_image( | |
| image=img_byte_arr, | |
| prompt=f"interior design photo, {prompt}, professional photography, high quality, detailed, realistic", | |
| negative_prompt="blurry, distorted, low quality, watermark, text, cartoon, sketch", | |
| model="black-forest-labs/FLUX.1-schnell", # Fast, public model | |
| ) | |
| return edited_image | |
| except Exception as e: | |
| # Fallback to text-to-image if image-to-image fails | |
| try: | |
| generated = client.text_to_image( | |
| prompt=f"interior room design, {prompt}, professional photography, 4k, realistic", | |
| model="black-forest-labs/FLUX.1-schnell" | |
| ) | |
| return generated | |
| except Exception as e2: | |
| return None, f"Error: {str(e2)}" | |
| def process_room(image, edit_prompt): | |
| """Main processing function""" | |
| if image is None: | |
| return None, "Please upload an image" | |
| if not edit_prompt.strip(): | |
| return None, "Please provide editing instructions" | |
| # Process the image | |
| result = segment_and_edit(image, edit_prompt) | |
| if isinstance(result, tuple): | |
| return result | |
| return result, "✅ Edit complete!" | |
| # Gradio Interface | |
| with gr.Blocks(theme=gr.themes.Soft()) as demo: | |
| gr.Markdown(""" | |
| # 🏠 AI Interior Designer Assistant | |
| Upload a room photo and describe your desired changes. Uses AI to redesign your space. | |
| **Example prompts:** | |
| - "Change the sofa to mid-century modern, deep blue velvet" | |
| - "Replace with white minimalist furniture and add plants" | |
| - "Make it Scandinavian style with light wood" | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| input_image = gr.Image(type="pil", label="Upload Room Photo") | |
| edit_prompt = gr.Textbox( | |
| label="Describe Your Changes", | |
| placeholder="E.g., change the sofa to modern gray fabric and add a floor lamp", | |
| lines=3 | |
| ) | |
| submit_btn = gr.Button("Transform Room 🎨", variant="primary") | |
| with gr.Column(): | |
| output_image = gr.Image(label="Redesigned Room") | |
| status_text = gr.Textbox(label="Status", interactive=False) | |
| # Examples | |
| gr.Examples( | |
| examples=[ | |
| ["Change to modern minimalist with white furniture", None], | |
| ["Replace with bohemian style, add colorful cushions and plants", None], | |
| ["Make it industrial loft style with exposed brick aesthetic", None], | |
| ], | |
| inputs=[edit_prompt, input_image], | |
| ) | |
| submit_btn.click( | |
| fn=process_room, | |
| inputs=[input_image, edit_prompt], | |
| outputs=[output_image, status_text] | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |