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| import torch | |
| from diffusers import StableDiffusionInstructPix2PixPipeline | |
| import gradio as gr | |
| from PIL import Image | |
| import random | |
| # Load the InstructPix2Pix model | |
| model_id = "timbrooks/instruct-pix2pix" | |
| pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16) | |
| pipe = pipe.to("cuda") | |
| # Initialize a random seed | |
| seed = random.randint(0, 10000) | |
| # Function to reset the seed | |
| def change_style(): | |
| global seed | |
| seed = random.randint(0, 10000) | |
| return f"Seed changed to: {seed}" | |
| # Changign the walls' color function | |
| def change_color(image,color): | |
| # Construct the furniture prompt | |
| prompt = f"paint the walls with {color} color " | |
| # Text CFG (guidance_scale) controls how strongly the model follows the prompt | |
| text_cfg = 7.5 | |
| # Image CFG: Although not explicitly part of InstructPix2Pix, you can "simulate" image preservation | |
| # by lowering the impact of the guidance. Here, we assume lower guidance impacts image preservation. | |
| image_cfg = 1.5 | |
| # Apply the edit using InstructPix2Pix, with text CFG and image CFG influencing the guidance scale | |
| edited_image = pipe( | |
| prompt=prompt, | |
| image=image, | |
| num_inference_steps=70, # Number of diffusion steps | |
| guidance_scale=text_cfg, # Text CFG for following the prompt | |
| image_guidance_scale=image_cfg, # Simulated Image CFG to preserve image content | |
| generator=torch.manual_seed(seed) # Random seed for consistency | |
| ).images[0] | |
| return edited_image | |
| # General image editing function | |
| def edit_image(image, instruction): | |
| # Text CFG (guidance_scale) controls how strongly the model follows the prompt | |
| text_cfg = 12.0 | |
| # Image CFG: Simulated value for preserving the original image content | |
| image_cfg = 1.5 | |
| # Apply the edit using InstructPix2Pix, with text CFG and simulated image CFG | |
| edited_image = pipe( | |
| prompt=instruction, | |
| image=image, | |
| num_inference_steps=70, # Number of diffusion steps | |
| guidance_scale=text_cfg, # Text CFG for following the prompt | |
| image_guidance_scale=image_cfg, # Simulated Image CFG to preserve image content | |
| generator=torch.manual_seed(seed) # Random seed for consistency | |
| ).images[0] | |
| return edited_image | |
| # Gradio interface for image editing | |
| def image_interface(): | |
| with gr.Blocks() as demo_color: | |
| gr.Markdown("## Furniture Adding App") | |
| # Image upload | |
| image_input = gr.Image(type="pil", label="Upload Room Image") | |
| # List of common painting colors | |
| common_colors = [ | |
| "Alabaster", # Off-white | |
| "Agreeable Gray", # Warm gray | |
| "Sea Salt", # Soft greenish-blue | |
| "Pure White", # Bright white | |
| "Accessible Beige", # Warm beige | |
| "Mindful Gray", # Cool gray | |
| "Peppercorn", # Dark charcoal gray | |
| "Hale Navy", # Dark navy blue | |
| "Tricorn Black", # Pure black | |
| "Pale Oak", # Soft taupe | |
| "Silver Strand", # Soft blue-gray | |
| "Rainwashed", # Light aqua | |
| "Orange Burst", # Bright orange | |
| "Sunny Yellow", # Bright yellow | |
| "Sage Green", # Muted green | |
| "Firebrick Red", # Deep red | |
| "Lavender", # Soft purple | |
| "Sky Blue", # Light blue | |
| "Coral", # Vibrant coral | |
| ] | |
| # Dropdown for wall color | |
| color_input = gr.Dropdown(common_colors, label="Choose Wall Color") | |
| # Display output image | |
| result_image = gr.Image(label="Edited Image") | |
| # Button to apply the wall color transformation | |
| submit_button = gr.Button("Paint the walls") | |
| # Define action on button click | |
| submit_button.click(fn=change_color, inputs=[image_input, color_input], outputs=result_image) | |
| return demo_color | |
| # Gradio interface for general image editing | |
| def general_editing_interface(): | |
| with gr.Blocks() as demo_general: | |
| gr.Markdown("## General Image Editing App") | |
| # Image upload | |
| image_input = gr.Image(type="pil", label="Upload an Image") | |
| # Textbox for instruction | |
| instruction_input = gr.Textbox(label="Enter the Instruction", placeholder="Describe the changes (e.g., 'Make it snowy')") | |
| # Display output image | |
| result_image = gr.Image(label="Edited Image") | |
| # Button to apply the transformation | |
| submit_button = gr.Button("Apply Edit") | |
| # Button to change the seed (style) | |
| change_style_button = gr.Button("Change the Style") | |
| # Output for seed change message | |
| seed_output = gr.Textbox(label="Seed Info", interactive=False) | |
| # Define action on button click | |
| submit_button.click(fn=edit_image, inputs=[image_input, instruction_input], outputs=result_image) | |
| change_style_button.click(fn=change_style, outputs=seed_output) | |
| return demo_general | |
| # Launch both Gradio apps | |
| color_app = image_interface() | |
| general_editing_app = general_editing_interface() | |
| with gr.Blocks() as combined_demo: | |
| gr.Markdown("## Select the Application") | |
| with gr.Tab("General Image Editing App"): | |
| general_editing_app.render() | |
| with gr.Tab("Changing The Paint App"): | |
| color_app.render() | |
| # Launch the combined Gradio app | |
| combined_demo.launch() | |