| import spaces |
| import gradio as gr |
| import torch |
| import uuid |
| import os |
|
|
| from PIL import Image |
| from enhance_utils import enhance_image |
|
|
| DEFAULT_SRC_PROMPT = "a woman, photo" |
| DEFAULT_EDIT_PROMPT = "a beautiful woman, photo, hollywood style face, 8k, high quality" |
|
|
| device = "cuda" if torch.cuda.is_available() else "cpu" |
|
|
| def create_demo() -> gr.Blocks: |
| from inversion_run_base import run as base_run |
|
|
| @spaces.GPU(duration=10) |
| def image_to_image( |
| input_image_path: str, |
| input_image_prompt: str, |
| edit_prompt: str, |
| seed: int, |
| w1: float, |
| num_steps: int, |
| start_step: int, |
| guidance_scale: float, |
| enhance_face: bool = True, |
| ): |
| w2 = 1.0 |
|
|
| input_image = Image.open(input_image_path) |
| icc_profile = input_image.info.get("icc_profile") |
|
|
| run_model = base_run |
| res_image = run_model( |
| input_image, |
| input_image_prompt, |
| edit_prompt, |
| seed, |
| w1, |
| w2, |
| num_steps, |
| start_step, |
| guidance_scale, |
| ) |
| enhanced_image = enhance_image(res_image, enhance_face) |
|
|
| tmpPrefix = "/tmp/gradio/" |
|
|
| extension = 'png' |
| if enhanced_image.mode == 'RGBA': |
| extension = 'png' |
| else: |
| extension = 'jpg' |
|
|
| targetDir = f"{tmpPrefix}output/" |
| if not os.path.exists(targetDir): |
| os.makedirs(targetDir) |
|
|
| enhanced_path = f"{targetDir}{uuid.uuid4()}.{extension}" |
| enhanced_image.save(enhanced_path, quality=100, icc_profile=icc_profile) |
|
|
| return enhanced_path |
|
|
| with gr.Blocks() as demo: |
| with gr.Row(): |
| with gr.Column(): |
| input_image_path = gr.File(label="Input Image") |
| with gr.Column(): |
| generated_image_path = gr.File(label="Download the segment image", interactive=False) |
| with gr.Row(): |
| with gr.Column(): |
| input_image_prompt = gr.Textbox(lines=1, label="Input Image Prompt", value=DEFAULT_SRC_PROMPT) |
| edit_prompt = gr.Textbox(lines=1, label="Edit Prompt", value=DEFAULT_EDIT_PROMPT) |
| with gr.Accordion("Advanced Options", open=False): |
| guidance_scale = gr.Slider(minimum=0, maximum=20, value=0, step=0.5, label="Guidance Scale") |
| enhance_face = gr.Checkbox(label="Enhance Face", value=False) |
| seed = gr.Number(label="Seed", value=8) |
| with gr.Column(): |
| num_steps = gr.Slider(minimum=1, maximum=100, value=20, step=1, label="Num Steps") |
| start_step = gr.Slider(minimum=1, maximum=100, value=15, step=1, label="Start Step") |
| w1 = gr.Number(label="W1", value=2) |
| g_btn = gr.Button("Edit Image") |
| |
| |
| g_btn.click( |
| fn=image_to_image, |
| inputs=[input_image_path, input_image_prompt, edit_prompt,seed,w1, num_steps, start_step, guidance_scale, enhance_face], |
| outputs=[generated_image_path], |
| ) |
|
|
| return demo |