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import random |
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import numpy as np |
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from PIL import Image |
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import base64 |
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from io import BytesIO |
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import torch |
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import torchvision.transforms.functional as F |
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from diffusers import ControlNetModel, StableDiffusionControlNetPipeline |
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import gradio as gr |
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device = "mps" |
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weight_type = torch.float16 |
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controlnet = ControlNetModel.from_pretrained( |
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"IDKiro/sdxs-512-dreamshaper-sketch", torch_dtype=weight_type |
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).to(device) |
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pipe = StableDiffusionControlNetPipeline.from_pretrained( |
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"IDKiro/sdxs-512-dreamshaper", controlnet=controlnet, torch_dtype=weight_type |
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) |
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pipe.to(device) |
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style_list = [ |
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{ |
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"name": "No Style", |
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"prompt": "{prompt}", |
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}, |
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{ |
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"name": "Cinematic", |
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"prompt": "cinematic still {prompt} . emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy", |
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}, |
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{ |
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"name": "3D Model", |
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"prompt": "professional 3d model {prompt} . octane render, highly detailed, volumetric, dramatic lighting", |
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}, |
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{ |
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"name": "Anime", |
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"prompt": "anime artwork {prompt} . anime style, key visual, vibrant, studio anime, highly detailed", |
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}, |
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{ |
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"name": "Digital Art", |
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"prompt": "concept art {prompt} . digital artwork, illustrative, painterly, matte painting, highly detailed", |
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}, |
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{ |
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"name": "Photographic", |
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"prompt": "cinematic photo {prompt} . 35mm photograph, film, bokeh, professional, 4k, highly detailed", |
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}, |
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{ |
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"name": "Pixel art", |
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"prompt": "pixel-art {prompt} . low-res, blocky, pixel art style, 8-bit graphics", |
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}, |
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{ |
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"name": "Fantasy art", |
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"prompt": "ethereal fantasy concept art of {prompt} . magnificent, celestial, ethereal, painterly, epic, majestic, magical, fantasy art, cover art, dreamy", |
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}, |
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{ |
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"name": "Neonpunk", |
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"prompt": "neonpunk style {prompt} . cyberpunk, vaporwave, neon, vibes, vibrant, stunningly beautiful, crisp, detailed, sleek, ultramodern, magenta highlights, dark purple shadows, high contrast, cinematic, ultra detailed, intricate, professional", |
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}, |
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{ |
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"name": "Manga", |
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"prompt": "manga style {prompt} . vibrant, high-energy, detailed, iconic, Japanese comic style", |
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}, |
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] |
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styles = {k["name"]: k["prompt"] for k in style_list} |
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STYLE_NAMES = list(styles.keys()) |
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DEFAULT_STYLE_NAME = "No Style" |
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MAX_SEED = np.iinfo(np.int32).max |
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def pil_image_to_data_url(img, format="PNG"): |
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buffered = BytesIO() |
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img.save(buffered, format=format) |
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img_str = base64.b64encode(buffered.getvalue()).decode() |
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return f"data:image/{format.lower()};base64,{img_str}" |
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def randomize_seed_fn(seed: int, randomize_seed: bool) -> int: |
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if randomize_seed: |
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seed = random.randint(0, MAX_SEED) |
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return seed |
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def run( |
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image, |
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prompt, |
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prompt_template, |
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style_name, |
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controlnet_conditioning_scale, |
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device_type="GPU", |
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param_dtype='torch.float16', |
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): |
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if device_type == "CPU": |
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device = "cpu" |
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param_dtype = 'torch.float32' |
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else: |
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device = "mps" |
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pipe.to(torch_device=device, torch_dtype=torch.float16 if param_dtype == 'torch.float16' else torch.float32) |
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print(f"prompt: {prompt}") |
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print("sketch updated") |
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if image is None: |
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ones = Image.new("L", (512, 512), 255) |
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temp_url = pil_image_to_data_url(ones) |
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return ones, gr.update(link=temp_url), gr.update(link=temp_url) |
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prompt = prompt_template.replace("{prompt}", prompt) |
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control_image = image.convert("RGB") |
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control_image = Image.fromarray(255 - np.array(control_image)) |
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output_pil = pipe( |
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prompt=prompt, |
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image=control_image, |
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width=512, |
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height=512, |
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guidance_scale=0.0, |
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num_inference_steps=1, |
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num_images_per_prompt=1, |
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output_type="pil", |
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controlnet_conditioning_scale=controlnet_conditioning_scale, |
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).images[0] |
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input_sketch_url = pil_image_to_data_url(control_image) |
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output_image_url = pil_image_to_data_url(output_pil) |
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return ( |
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output_pil, |
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gr.update(link=input_sketch_url), |
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gr.update(link=output_image_url), |
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) |
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def update_canvas(use_line, use_eraser): |
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if use_eraser: |
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_color = "#ffffff" |
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brush_size = 20 |
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if use_line: |
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_color = "#000000" |
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brush_size = 8 |
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return gr.update(brush_radius=brush_size, brush_color=_color, interactive=True) |
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def upload_sketch(file): |
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_img = Image.open(file.name) |
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_img = _img.convert("L") |
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return gr.update(value=_img, source="upload", interactive=True) |
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scripts = """ |
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async () => { |
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globalThis.theSketchDownloadFunction = () => { |
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console.log("test") |
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var link = document.createElement("a"); |
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dataUrl = document.getElementById('download_sketch').href |
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link.setAttribute("href", dataUrl) |
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link.setAttribute("download", "sketch.png") |
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document.body.appendChild(link); // Required for Firefox |
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link.click(); |
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document.body.removeChild(link); // Clean up |
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// also call the output download function |
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theOutputDownloadFunction(); |
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return false |
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} |
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globalThis.theOutputDownloadFunction = () => { |
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console.log("test output download function") |
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var link = document.createElement("a"); |
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dataUrl = document.getElementById('download_output').href |
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link.setAttribute("href", dataUrl); |
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link.setAttribute("download", "output.png"); |
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document.body.appendChild(link); // Required for Firefox |
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link.click(); |
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document.body.removeChild(link); // Clean up |
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return false |
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} |
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globalThis.UNDO_SKETCH_FUNCTION = () => { |
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console.log("undo sketch function") |
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var button_undo = document.querySelector('#input_image > div.image-container.svelte-p3y7hu > div.svelte-s6ybro > button:nth-child(1)'); |
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// Create a new 'click' event |
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var event = new MouseEvent('click', { |
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'view': window, |
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'bubbles': true, |
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'cancelable': true |
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}); |
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button_undo.dispatchEvent(event); |
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} |
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globalThis.DELETE_SKETCH_FUNCTION = () => { |
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console.log("delete sketch function") |
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var button_del = document.querySelector('#input_image > div.image-container.svelte-p3y7hu > div.svelte-s6ybro > button:nth-child(2)'); |
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// Create a new 'click' event |
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var event = new MouseEvent('click', { |
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'view': window, |
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'bubbles': true, |
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'cancelable': true |
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}); |
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button_del.dispatchEvent(event); |
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} |
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globalThis.togglePencil = () => { |
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el_pencil = document.getElementById('my-toggle-pencil'); |
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el_pencil.classList.toggle('clicked'); |
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// simulate a click on the gradio button |
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btn_gradio = document.querySelector("#cb-line > label > input"); |
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var event = new MouseEvent('click', { |
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'view': window, |
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'bubbles': true, |
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'cancelable': true |
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}); |
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btn_gradio.dispatchEvent(event); |
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if (el_pencil.classList.contains('clicked')) { |
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document.getElementById('my-toggle-eraser').classList.remove('clicked'); |
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document.getElementById('my-div-pencil').style.backgroundColor = "gray"; |
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document.getElementById('my-div-eraser').style.backgroundColor = "white"; |
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} |
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else { |
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document.getElementById('my-toggle-eraser').classList.add('clicked'); |
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document.getElementById('my-div-pencil').style.backgroundColor = "white"; |
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document.getElementById('my-div-eraser').style.backgroundColor = "gray"; |
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} |
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} |
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globalThis.toggleEraser = () => { |
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element = document.getElementById('my-toggle-eraser'); |
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element.classList.toggle('clicked'); |
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// simulate a click on the gradio button |
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btn_gradio = document.querySelector("#cb-eraser > label > input"); |
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var event = new MouseEvent('click', { |
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'view': window, |
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'bubbles': true, |
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'cancelable': true |
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}); |
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btn_gradio.dispatchEvent(event); |
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if (element.classList.contains('clicked')) { |
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document.getElementById('my-toggle-pencil').classList.remove('clicked'); |
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document.getElementById('my-div-pencil').style.backgroundColor = "white"; |
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document.getElementById('my-div-eraser').style.backgroundColor = "gray"; |
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} |
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else { |
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document.getElementById('my-toggle-pencil').classList.add('clicked'); |
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document.getElementById('my-div-pencil').style.backgroundColor = "gray"; |
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document.getElementById('my-div-eraser').style.backgroundColor = "white"; |
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} |
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} |
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} |
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""" |
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with gr.Blocks(css="style.css") as demo: |
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gr.Markdown("# SDXS-512-DreamShaper-Sketch") |
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line = gr.Checkbox(label="line", value=False, elem_id="cb-line") |
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eraser = gr.Checkbox(label="eraser", value=False, elem_id="cb-eraser") |
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with gr.Row(elem_id="main_row"): |
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with gr.Column(elem_id="column_input"): |
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gr.Markdown("## INPUT", elem_id="input_header") |
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image = gr.Image( |
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source="canvas", tool="color-sketch", type="pil", image_mode="L", |
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invert_colors=True, shape=(512, 512), brush_radius=8, height=440, width=440, |
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brush_color="#000000", interactive=True, show_download_button=True, elem_id="input_image", show_label=False) |
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download_sketch = gr.Button("Download sketch", scale=1, elem_id="download_sketch") |
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gr.HTML(""" |
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<div class="button-row"> |
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<div id="my-div-pencil" class="pad2"> <button id="my-toggle-pencil" onclick="return togglePencil(this)"></button> </div> |
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<div id="my-div-eraser" class="pad2"> <button id="my-toggle-eraser" onclick="return toggleEraser(this)"></button> </div> |
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<div class="pad2"> <button id="my-button-undo" onclick="return UNDO_SKETCH_FUNCTION(this)"></button> </div> |
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<div class="pad2"> <button id="my-button-clear" onclick="return DELETE_SKETCH_FUNCTION(this)"></button> </div> |
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<div class="pad2"> <button href="TODO" download="image" id="my-button-down" onclick='return theSketchDownloadFunction()'></button> </div> |
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</div> |
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""") |
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prompt = gr.Textbox(label="Prompt", value="", show_label=True) |
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with gr.Row(): |
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style = gr.Dropdown(label="Style", choices=STYLE_NAMES, value=DEFAULT_STYLE_NAME, scale=1) |
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prompt_temp = gr.Textbox(label="Prompt Style Template", value=styles[DEFAULT_STYLE_NAME], scale=2, max_lines=1) |
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controlnet_conditioning_scale = gr.Slider(label="Control Strength", minimum=0, maximum=1, step=0.01, value=0.8) |
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device_choices = ['GPU','CPU'] |
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device_type = gr.Radio(device_choices, label='Device', |
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value=device_choices[0], |
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interactive=True, |
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info='Please choose GPU if you have a GPU.') |
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dtype_choices = ['torch.float16','torch.float32'] |
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param_dtype = gr.Radio(dtype_choices,label='torch.weight_type', |
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value=dtype_choices[0], |
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interactive=True, |
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info='To save GPU memory, use torch.float16. For better quality, use torch.float32.') |
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with gr.Column(elem_id="column_process", min_width=50, scale=0.4): |
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gr.Markdown("## SDXS-Sketch", elem_id="description") |
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run_button = gr.Button("Run", min_width=50) |
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with gr.Column(elem_id="column_output"): |
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gr.Markdown("## OUTPUT", elem_id="output_header") |
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result = gr.Image(label="Result", height=440, width=440, elem_id="output_image", show_label=False, show_download_button=True) |
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download_output = gr.Button("Download output", elem_id="download_output") |
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gr.Markdown("### Instructions") |
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gr.Markdown("**1**. Enter a text prompt (e.g. cat)") |
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gr.Markdown("**2**. Start sketching") |
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gr.Markdown("**3**. Change the image style using a style template") |
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gr.Markdown("**4**. Adjust the effect of sketch guidance using the slider") |
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eraser.change(fn=lambda x: gr.update(value=not x), inputs=[eraser], outputs=[line]).then(update_canvas, [line, eraser], [image]) |
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line.change(fn=lambda x: gr.update(value=not x), inputs=[line], outputs=[eraser]).then(update_canvas, [line, eraser], [image]) |
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demo.load(None,None,None,_js=scripts) |
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inputs = [image, prompt, prompt_temp, style, controlnet_conditioning_scale, device_type, param_dtype] |
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outputs = [result, download_sketch, download_output] |
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prompt.submit(fn=run, inputs=inputs, outputs=outputs) |
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style.change(lambda x: styles[x], inputs=[style], outputs=[prompt_temp]).then( |
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fn=run, inputs=inputs, outputs=outputs,) |
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run_button.click(fn=run, inputs=inputs, outputs=outputs) |
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image.change(run, inputs=inputs, outputs=outputs,) |
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if __name__ == "__main__": |
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demo.queue().launch(debug=True, share=True) |