| import gradio as gr |
| import torch |
| from diffusers import StableDiffusionInstructPix2PixPipeline |
| from PIL import Image |
|
|
| |
| model_id = "timbrooks/instruct-pix2pix" |
| pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained( |
| model_id, torch_dtype=torch.float32, safety_checker=None |
| ) |
| pipe.to("cpu") |
|
|
| def edit_image(input_image, instruction): |
| if input_image is None or instruction == "": |
| return None |
| |
| |
| edited_image = pipe( |
| prompt=instruction, |
| image=input_image, |
| num_inference_steps=5, |
| image_guidance_scale=1.5, |
| guidance_scale=7.5 |
| ).images[0] |
| |
| return edited_image |
|
|
| |
| with gr.Blocks() as demo: |
| gr.Markdown("## 🎨 AI Photo Editor (Prompt Based)") |
| with gr.Row(): |
| with gr.Column(): |
| img_in = gr.Image(type="pil", label="আপনার ছবি দিন") |
| prompt_in = gr.Textbox(label="কি এডিট করতে চান?", placeholder="যেমন: Make the dress red or change background to moon") |
| btn = gr.Button("এডিট করুন") |
| with gr.Column(): |
| img_out = gr.Image(type="pil", label="এডিট করা ছবি") |
|
|
| btn.click(edit_image, inputs=[img_in, prompt_in], outputs=img_out) |
|
|
| demo.launch() |
|
|
