import gradio as gr import os, requests from inference import setup_model, colorize_grayscale, predict_anchors ## download checkpoint def download_file_from_google_drive(id, destination): def get_confirm_token(response): for key, value in response.cookies.items(): if key.startswith('download_warning'): return value return None def save_response_content(response, destination): CHUNK_SIZE = 32768 with open(destination, "wb") as f: for chunk in response.iter_content(CHUNK_SIZE): if chunk: # filter out keep-alive new chunks f.write(chunk) URL = "https://docs.google.com/uc?export=download" session = requests.Session() response = session.get(URL, params = { 'id' : id }, stream = True) token = get_confirm_token(response) if token: params = { 'id' : id, 'confirm' : token } response = session.get(URL, params = params, stream = True) save_response_content(response, destination) id = "1J4vB6kG4xBLUUKpXr5IhnSSa4maXgRvQ" destination = "disco-beta.pth.rar" download_file_from_google_drive(id, destination) os.rename("disco-beta.pth.tar", "./checkpoints/disco-beta.pth.tar") ## step 1: set up model device = "cuda" checkpt_path = "./checkpoints/disco-beta.pth.tar" assert os.path.exists(checkpt_path), "No checkpoint found!" colorizer, colorLabeler = setup_model(checkpt_path, device=device) def click_colorize(rgb_img, hint_img, n_anchors, is_high_res, is_editable): if hint_img is None: hint_img = rgb_img output = colorize_grayscale(colorizer, colorLabeler, rgb_img, hint_img, n_anchors, is_high_res, is_editable, device) return output def click_predanchors(rgb_img, n_anchors, is_high_res, is_editable): output = predict_anchors(colorizer, colorLabeler, rgb_img, n_anchors, is_high_res, is_editable, device) return output ## step 2: configure interface def switch_states(is_checked): if is_checked: return gr.Image.update(visible=True), gr.Button.update(visible=True) else: return gr.Image.update(visible=False), gr.Button.update(visible=False) demo = gr.Blocks(title="DISCO: Image Colorization") with demo: gr.Markdown(value="""**DISCO: image colorization that disentangles color multimodality and spatial affinity via global anchors**.""") with gr.Row(): with gr.Column(scale=1): Image_input = gr.Image(type="numpy", label="Input", interactive=True) Image_anchor = gr.Image(type="numpy", label="Anchor", tool="color-sketch", interactive=True, visible=False) with gr.Row(): Num_anchor = gr.Number(type="int", value=8, label="Num. of anchors (3~14)") Radio_resolution = gr.Radio(type="index", choices=["Low (256x256)", "High (512x512)"], \ label="Colorization resolution", value="Low (256x256)") Ckeckbox_editable = gr.Checkbox(default=False, label='Show editable anchors') with gr.Row(): Button_show_anchor = gr.Button(value="Predict anchors", visible=False) Button_run = gr.Button(value="Colorize") with gr.Column(scale=1): Image_output = gr.Image(type="numpy", label="Output", shape=[100,100]) Ckeckbox_editable.change(fn=switch_states, inputs=Ckeckbox_editable, outputs=[Image_anchor, Button_show_anchor]) Button_show_anchor.click(fn=click_predanchors, inputs=[Image_input, Num_anchor, Radio_resolution, Ckeckbox_editable], outputs=Image_anchor) Button_run.click(fn=click_colorize, inputs=[Image_input, Image_anchor, Num_anchor, Radio_resolution, Ckeckbox_editable], \ outputs=Image_output) ## guiline gr.Markdown(value=""" **Guideline** 1. Upload your image; 2. Set up the arguments: "Num. of anchors" and "Colorization resolution"; 3. Two modes are supported: - **Editable**: check ""Show editable anchors" and click "Predict anchors". Then, modify the colors of the predicted anchors (anchor mask will be applied afterward). Finally, click "Colorize" to get the result. - **Automatic**: click "Colorize" to get the automatically colorized output. *To know more about the method, please refer to our project page: [https://menghanxia.github.io/projects/disco.html](https://menghanxia.github.io/projects/disco.html)* """) demo.launch(server_name='9.134.253.83',server_port=7788)