import gradio as gr from all_models import models from prompt import thePrompt from externalmod import gr_Interface_load, save_image, randomize_seed import asyncio import os from threading import RLock from datetime import datetime # preSetPrompt = "tall slender athletic 18+ caucasian woman. gorgeous face. perfect small tits. short hair. sassy smile. shredded ripped torn shirt. unbuttoned jeans. explicit. artistic. photorealistic. f1.4" preSetPrompt = thePrompt negPreSetPrompt = "[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry, text, fuzziness" lock = RLock() HF_TOKEN = os.environ.get("HF_TOKEN") if os.environ.get("HF_TOKEN") else None # If private or gated models aren't used, ENV setting is unnecessary. def get_current_time(): now = datetime.now() current_time = now.strftime("%y-%m-%d %H:%M:%S") return current_time def load_fn(models): global models_load models_load = {} for model in models: if model not in models_load.keys(): try: m = gr_Interface_load(f'models/{model}', hf_token=HF_TOKEN) except Exception as error: print(error) m = gr.Interface(lambda: None, ['text'], ['image']) models_load.update({model: m}) load_fn(models) num_models = 3 max_images = 3 inference_timeout = 400 default_models = models[:num_models] MAX_SEED = 2**32-1 def imgageHasUpdated(theImage): print(theImage) # outputs=lnk_output def extend_choices(choices): return choices[:num_models] + (num_models - len(choices[:num_models])) * ['NA'] def update_imgbox(choices): choices_plus = extend_choices(choices[:num_models]) return [gr.Image(None, label=m, visible=(m!='NA')) for m in choices_plus] def random_choices(): import random random.seed() return random.choices(models, k=num_models) async def infer(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1, timeout=inference_timeout): kwargs = {} if height > 0: kwargs["height"] = height if width > 0: kwargs["width"] = width if steps > 0: kwargs["num_inference_steps"] = steps if cfg > 0: cfg = kwargs["guidance_scale"] = cfg if seed == -1: theSeed = randomize_seed() else: theSeed = seed kwargs["seed"] = theSeed task = asyncio.create_task(asyncio.to_thread(models_load[model_str].fn, prompt=prompt, negative_prompt=nprompt, **kwargs, token=HF_TOKEN)) await asyncio.sleep(0) try: result = await asyncio.wait_for(task, timeout=timeout) except asyncio.TimeoutError as e: print(e) print(f"infer: Task timed out: {model_str}") if not task.done(): task.cancel() result = None raise Exception(f"Task timed out: {model_str}") from e except Exception as e: print(e) print(f"infer: exception: {model_str}") if not task.done(): task.cancel() result = None raise Exception() from e if task.done() and result is not None and not isinstance(result, tuple): with lock: png_path = model_str.replace("/", "_") + " - " + get_current_time() + "_" + str(theSeed) + ".png" image = save_image(result, png_path, model_str, prompt, nprompt, height, width, steps, cfg, theSeed) return image return None def gen_fn(model_str, prompt, nprompt="", height=0, width=0, steps=0, cfg=0, seed=-1): try: loop = asyncio.new_event_loop() result = loop.run_until_complete(infer(model_str, prompt, nprompt, height, width, steps, cfg, seed, inference_timeout)) except (Exception, asyncio.CancelledError) as e: print(e) print(f"gen_fn: Task aborted: {model_str}") result = None raise gr.Error(f"Task aborted: {model_str}, Error: {e}") finally: loop.close() return result def add_gallery(image, model_str, gallery): if gallery is None: gallery = [] with lock: if image is not None: gallery.insert(0, (image, model_str)) # if image is not None: imgageHasUpdated(model_str) return gallery JS=""" <script> // Function to monitor image src changes and automatically download the image function monitorImageSrcChanges() { // Set of recently downloaded image URLs to avoid re-triggering the download const downloadedImages = new Set(); // Track the last time a download occurred (in milliseconds) let lastDownloadTime = Date.now(); // Create a MutationObserver instance const observer = new MutationObserver((mutationsList, observer) => { // Loop through all mutations mutationsList.forEach(mutation => { // Check if any new image tags were added if (mutation.type === 'childList') { mutation.addedNodes.forEach(node => { if (node.nodeName === 'IMG') { // New image added, monitor its src and download it observeImageSrc(node); } }); } // Check if an image src attribute has changed if (mutation.type === 'attributes' && mutation.attributeName === 'src') { console.log('Image src changed:', mutation.target.src); downloadImage(mutation.target.src); } }); }); // Options for the observer (what to monitor) const config = { childList: true, attributes: true, subtree: true, attributeFilter: ['src'] }; // Start observing the document body (or any specific element) observer.observe(document.body, config); // Initial monitoring of images already in the DOM document.querySelectorAll('img').forEach(img => { observeImageSrc(img); }); // Function to observe an image's src attribute changes function observeImageSrc(img) { const srcObserver = new MutationObserver(mutations => { mutations.forEach(mutation => { if (mutation.type === 'attributes' && mutation.attributeName === 'src') { console.log('Image src changed:', img.src); downloadImage(img.src); } }); }); // Start observing src attribute changes of the image srcObserver.observe(img, { attributes: true, attributeFilter: ['src'] }); } // Function to download an image automatically with a cooldown to prevent multiple downloads function downloadImage(src) { // Check if the image has been downloaded recently if (downloadedImages.has(src)) { return; // Prevent duplicate downloads } // Add the image src to the set of downloaded images downloadedImages.add(src); // Trigger the download const link = document.createElement('a'); link.href = src; link.download = src.split('/').pop(); // Use the file name from the URL (last part of the src) link.style.display = 'none'; // Hide the link document.body.appendChild(link); link.click(); // Trigger the download document.body.removeChild(link); // Clean up the DOM by removing the link after download // Set a cooldown to allow the download to be triggered again after a delay (e.g., 500ms) setTimeout(() => { downloadedImages.delete(src); // Remove from the set after the cooldown }, 500); // 500ms cooldown (adjust as needed) // After download is triggered, click the button with id "TheButt" setTimeout(() => { const button = document.getElementById('TheButt'); if (button) { button.click(); // Click the button } else { console.error('Button with id "TheButt" not found!'); } }, 500); // Adjust the timeout if needed to make sure the download starts before clicking // Update the last download time lastDownloadTime = Date.now(); } // Function to check for inactivity and reload the page if no download happened in 400 seconds setInterval(() => { const currentTime = Date.now(); if (currentTime - lastDownloadTime >= 400000) { // 400,000ms = 400 seconds console.log("No download detected for 400 seconds, reloading the page..."); location.reload(); // Reload the page } }, 1000); // Check every second } window.addEventListener('load', () => { monitorImageSrcChanges(); console.log("Yo"); }); </script> """ CSS=""" <style> .image-monitor { border:1px solid red; } /* .svelte-1pijsyv{ border:1px solid green; } */ .gallery-container{ max-height: 512px; } .butt{ background-color:#2b4764 !important } .butt:hover{ background-color:#3a6c9f !important; } </style> """ with gr.Blocks(head=CSS + JS) as demo: with gr.Column(scale=2): with gr.Group(): txt_input = gr.Textbox(label='Your prompt:', value=preSetPrompt, lines=3, autofocus=1) lnk_output = gr.Textbox(label='The Link:',visible=True,interactive=False,elem_id="LnkBox") neg_input = gr.Textbox(label='Negative prompt:', value=negPreSetPrompt, lines=1) with gr.Accordion("Advanced", open=False, visible=True): with gr.Row(): width = gr.Slider(label="Width", info="If 0, the default value is used.", maximum=1216, step=32, value=0) height = gr.Slider(label="Height", info="If 0, the default value is used.", maximum=1216, step=32, value=0) with gr.Row(): steps = gr.Slider(label="Number of inference steps", info="If 0, the default value is used.", maximum=100, step=1, value=0) cfg = gr.Slider(label="Guidance scale", info="If 0, the default value is used.", maximum=30.0, step=0.1, value=0) seed = gr.Slider(label="Seed", info="Randomize Seed if -1.", minimum=-1, maximum=MAX_SEED, step=1, value=-1) seed_rand = gr.Button("Randomize Seed 🎲", size="sm", variant="secondary") seed_rand.click(randomize_seed, None, [seed], queue=False) with gr.Row(): gen_button = gr.Button(f'Generate up to {int(num_models)} images', variant='primary', scale=3, elem_classes=["butt"], elem_id=["TheButt"]) random_button = gr.Button(f'Randomize Models', variant='secondary', scale=1) with gr.Column(scale=1): with gr.Group(): with gr.Row(): output = [gr.Image(label=m, show_download_button=True, interactive=False, width=112, height=112, show_share_button=False, format="png", visible=True) for m in default_models] current_models = [gr.Textbox(m, visible=False) for m in default_models] with gr.Column(scale=2): gallery = gr.Gallery(label="Output", show_download_button=True,interactive=False, show_share_button=False, container=True, format="png", preview=True, object_fit="cover", columns=2, rows=2) for m, o in zip(current_models, output): gen_event = gr.on(triggers=[gen_button.click, txt_input.submit], fn=gen_fn,inputs=[m, txt_input, neg_input, height, width, steps, cfg, seed], outputs=[o], concurrency_limit=None, queue=False) # o.change(add_gallery, [o, m, gallery], [gallery]) # o.change(imgageHasUpdated,[o]) with gr.Column(scale=4): with gr.Accordion('Model selection'): model_choice = gr.CheckboxGroup(models, label = f'Choose up to {int(num_models)} different models from the {len(models)} available!', value=default_models, interactive=True) model_choice.change(update_imgbox, model_choice, output) model_choice.change(extend_choices, model_choice, current_models) random_button.click(random_choices, None, model_choice) demo.launch(show_api=False, max_threads=400)