| import sys |
| from transformers.models.mt5 import tokenization_mt5 |
| import transformers |
|
|
| |
| transformers.MT5Tokenizer = tokenization_mt5.MT5Tokenizer |
| import gradio as gr |
| import torch |
| from diffusers import AutoPipelineForInpainting |
| from PIL import Image |
|
|
| |
| device = "mps" if torch.backends.mps.is_available() else "cpu" |
| model_id = "diffusers/stable-diffusion-xl-1.0-inpainting-0.1" |
|
|
| pipe = AutoPipelineForInpainting.from_pretrained( |
| model_id, |
| torch_dtype=torch.float16, |
| variant="fp16" |
| ).to(device) |
|
|
| def extend_photo(image_data, prompt): |
| |
| image = image_data["background"].convert("RGB") |
| mask = image_data["layers"][0].convert("RGB") |
| |
| |
| output = pipe( |
| prompt=prompt, |
| image=image, |
| mask_image=mask, |
| num_inference_steps=30 |
| ).images[0] |
| |
| return output |
|
|
| |
| with gr.Blocks() as demo: |
| gr.Markdown("## SDXL Photo Extender (Mac Local)") |
| with gr.Row(): |
| input_img = gr.ImageMask(label="ပုံထည့်ပြီး Extend လုပ်မည့်နေရာကို ခြစ်ပါ", type="pil") |
| output_img = gr.Image(label="ရလဒ်") |
| prompt_text = gr.Textbox(label="ဘာပုံ ဆက်ဆွဲရမလဲဆိုတာ ရေးပါ (ဥပမာ- beautiful forest background)") |
| run_btn = gr.Button("Extend Photo") |
| |
| run_btn.click(fn=extend_photo, inputs=[input_img, prompt_text], outputs=output_img) |
|
|
| |
| |
| demo.launch(share=True) |
