| import gradio as gr | |
| from io import BytesIO | |
| import requests | |
| import PIL | |
| from PIL import Image | |
| import numpy as np | |
| import os | |
| import uuid | |
| import torch | |
| from torch import autocast | |
| import cv2 | |
| from matplotlib import pyplot as plt | |
| from torchvision import transforms | |
| from diffusers import DiffusionPipeline | |
| from diffusers.utils import torch_device | |
| pipe = DiffusionPipeline.from_pretrained( | |
| "Fantasy-Studio/Paint-by-Example", | |
| torch_dtype=torch.float16, | |
| ) | |
| pipe = pipe.to("cuda") | |
| from share_btn import community_icon_html, loading_icon_html, share_js | |
| def read_content(file_path: str) -> str: | |
| """read the content of target file | |
| """ | |
| with open(file_path, 'r', encoding='utf-8') as f: | |
| content = f.read() | |
| return content | |
| def predict(dict, reference, scale, seed, step): | |
| width,height=dict["image"].size | |
| if width<height: | |
| factor=width/512.0 | |
| width=512 | |
| height=int((height/factor)/8.0)*8 | |
| else: | |
| factor=height/512.0 | |
| height=512 | |
| width=int((width/factor)/8.0)*8 | |
| init_image = dict["image"].convert("RGB").resize((width,height)) | |
| mask = dict["mask"].convert("RGB").resize((width,height)) | |
| generator = torch.Generator('cuda').manual_seed(seed) if seed != 0 else None | |
| output = pipe( | |
| image=init_image, | |
| mask_image=mask, | |
| example_image=reference, | |
| generator=generator, | |
| guidance_scale=scale, | |
| num_inference_steps=step, | |
| ).images[0] | |
| return output, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True) | |
| css = ''' | |
| .container {max-width: 1150px;margin: auto;padding-top: 1.5rem} | |
| #image_upload{min-height:400px} | |
| #image_upload [data-testid="image"], #image_upload [data-testid="image"] > div{min-height: 400px} | |
| #mask_radio .gr-form{background:transparent; border: none} | |
| #word_mask{margin-top: .75em !important} | |
| #word_mask textarea:disabled{opacity: 0.3} | |
| .footer {margin-bottom: 45px;margin-top: 35px;text-align: center;border-bottom: 1px solid #e5e5e5} | |
| .footer>p {font-size: .8rem; display: inline-block; padding: 0 10px;transform: translateY(10px);background: white} | |
| .dark .footer {border-color: #303030} | |
| .dark .footer>p {background: #0b0f19} | |
| .acknowledgments h4{margin: 1.25em 0 .25em 0;font-weight: bold;font-size: 115%} | |
| #image_upload .touch-none{display: flex} | |
| @keyframes spin { | |
| from { | |
| transform: rotate(0deg); | |
| } | |
| to { | |
| transform: rotate(360deg); | |
| } | |
| } | |
| #share-btn-container { | |
| display: flex; padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; width: 13rem; | |
| } | |
| #share-btn { | |
| all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem !important; padding-top: 0.25rem !important; padding-bottom: 0.25rem !important; | |
| } | |
| #share-btn * { | |
| all: unset; | |
| } | |
| #share-btn-container div:nth-child(-n+2){ | |
| width: auto !important; | |
| min-height: 0px !important; | |
| } | |
| #share-btn-container .wrap { | |
| display: none !important; | |
| } | |
| ''' | |
| example={} | |
| ref_dir='examples/reference' | |
| image_dir='examples/image' | |
| ref_list=[os.path.join(ref_dir,file) for file in os.listdir(ref_dir)] | |
| ref_list.sort() | |
| image_list=[os.path.join(image_dir,file) for file in os.listdir(image_dir)] | |
| image_list.sort() | |
| image_blocks = gr.Blocks(css=css) | |
| with image_blocks as demo: | |
| gr.HTML(read_content("header.html")) | |
| with gr.Group(): | |
| with gr.Box(): | |
| with gr.Row(): | |
| with gr.Column(): | |
| image = gr.Image(source='upload', tool='sketch', elem_id="image_upload", type="pil", label="Source Image") | |
| reference = gr.Image(source='upload', elem_id="image_upload", type="pil", label="Reference Image") | |
| with gr.Column(): | |
| image_out = gr.Image(label="Output", elem_id="output-img").style(height=400) | |
| guidance = gr.Slider(label="Guidance scale", value=5, maximum=15,interactive=True) | |
| steps = gr.Slider(label="Steps", value=50, minimum=2, maximum=75, step=1,interactive=True) | |
| seed = gr.Slider(0, 10000, label='Seed (0 = random)', value=0, step=1) | |
| with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True): | |
| btn = gr.Button("Paint!").style( | |
| margin=False, | |
| rounded=(False, True, True, False), | |
| full_width=True, | |
| ) | |
| with gr.Group(elem_id="share-btn-container"): | |
| community_icon = gr.HTML(community_icon_html, visible=True) | |
| loading_icon = gr.HTML(loading_icon_html, visible=True) | |
| share_button = gr.Button("Share to community", elem_id="share-btn", visible=True) | |
| with gr.Row(): | |
| with gr.Column(): | |
| gr.Examples(image_list, inputs=[image],label="Examples - Source Image",examples_per_page=12) | |
| with gr.Column(): | |
| gr.Examples(ref_list, inputs=[reference],label="Examples - Reference Image",examples_per_page=12) | |
| btn.click(fn=predict, inputs=[image, reference, guidance, seed, steps], outputs=[image_out, community_icon, loading_icon, share_button]) | |
| share_button.click(None, [], [], _js=share_js) | |
| image_blocks.launch(server_name='0.0.0.0') | |