| | import gradio as gr |
| | import requests |
| | import io |
| | import random |
| | import os |
| | from PIL import Image |
| | from deep_translator import GoogleTranslator |
| |
|
| |
|
| | import gradio as gr |
| |
|
| | def welcome(name): |
| | return f"Welcome to Gradio, {name}!" |
| |
|
| | js = """ |
| | function createGradioAnimation() { |
| | var container = document.createElement('div'); |
| | container.id = 'gradio-animation'; |
| | container.style.fontSize = '2em'; |
| | container.style.fontWeight = 'bold'; |
| | container.style.textAlign = 'center'; |
| | container.style.marginBottom = '20px'; |
| | |
| | var text = 'Welcome to Gradio!'; |
| | for (var i = 0; i < text.length; i++) { |
| | (function(i){ |
| | setTimeout(function(){ |
| | var letter = document.createElement('span'); |
| | letter.style.opacity = '0'; |
| | letter.style.transition = 'opacity 0.5s'; |
| | letter.innerText = text[i]; |
| | |
| | container.appendChild(letter); |
| | |
| | setTimeout(function() { |
| | letter.style.opacity = '1'; |
| | }, 50); |
| | }, i * 250); |
| | })(i); |
| | } |
| | |
| | var gradioContainer = document.querySelector('.gradio-container'); |
| | gradioContainer.insertBefore(container, gradioContainer.firstChild); |
| | |
| | return 'Animation created'; |
| | } |
| | """ |
| | with gr.Blocks(js=js) as demo: |
| | inp = gr.Textbox(placeholder="What is your name?") |
| | out = gr.Textbox() |
| | inp.change(welcome, inp, out) |
| |
|
| | demo.launch() |
| |
|
| | html='''<style> |
| | body, html, #app { |
| | margin: 0; |
| | width: 100%; |
| | height: 100%; |
| | } |
| | |
| | #app { |
| | overflow: hidden; |
| | touch-action: pan-up; |
| | color: #ffffff; |
| | font-family: 'Montserrat', sans-serif; |
| | text-align: center; |
| | text-shadow: 0 0 5px #000000, 0 0 20px #000; |
| | user-select: none; |
| | } |
| | |
| | #app h1 { |
| | --fontSize: 50px; |
| | --lineHeight: 70px; |
| | width: auto; |
| | height: calc(2 * var(--lineHeight)); |
| | line-height: var(--lineHeight); |
| | margin: calc(50vh - var(--lineHeight)) auto 0; |
| | font-size: var(--fontSize); |
| | } |
| | |
| | #app a { |
| | margin-top: 10px; |
| | display: inline-block; |
| | text-decoration: none; |
| | color: #fff; |
| | } |
| | |
| | #app canvas { |
| | display: block; |
| | position: fixed; |
| | z-index: -1; |
| | top: 0; |
| | } |
| | </style> |
| | |
| | <script> |
| | import { swarmBackground } from 'https://unpkg.com/threejs-toys@0.0.8/build/threejs-toys.module.cdn.min.js' |
| | |
| | const bg = swarmBackground({ |
| | el: document.getElementById('app'), |
| | eventsEl: document.body, |
| | gpgpuSize: 256, |
| | color: [Math.random() * 0xffffff, Math.random() * 0xffffff], |
| | geometry: 'default' |
| | }) |
| | |
| | bg.three.camera.position.set(0, 0, 200) |
| | |
| | document.body.addEventListener('click', () => { |
| | bg.setColors([Math.random() * 0xffffff, Math.random() * 0xffffff]) |
| | }) |
| | </script> |
| | <div id="app"> |
| | <div id="hero"> |
| | <h1>SWARM<br/>BACKGROUND</h1> |
| | <a target="_blank" href="https://github.com/klevron/threejs-toys">github/threejs-toys</a> |
| | </div> |
| | </div> |
| | ''' |
| | |
| | if not os.path.exists('icon.jpg'): |
| | os.system("wget -O icon.jpg https://i.pinimg.com/564x/64/49/88/644988c59447eb00286834c2e70fdd6b.jpg") |
| | API_URL_DEV = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev" |
| | API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-schnell" |
| | timeout = 100 |
| |
|
| | def query(prompt, is_negative=False, steps=30, cfg_scale=7, sampler="DPM++ 2M Karras", seed=-1, strength=0.7, huggingface_api_key=None, use_dev=False): |
| | |
| | api_url = API_URL_DEV if use_dev else API_URL |
| |
|
| | |
| | is_api_call = huggingface_api_key is not None |
| |
|
| | if is_api_call: |
| | |
| | API_TOKEN = os.getenv("HF_READ_TOKEN") |
| | headers = {"Authorization": f"Bearer {API_TOKEN}"} |
| | else: |
| | |
| | if huggingface_api_key == "": |
| | raise gr.Error("API key is required for API calls.") |
| | headers = {"Authorization": f"Bearer {huggingface_api_key}"} |
| |
|
| | if prompt == "" or prompt is None: |
| | return None |
| |
|
| | key = random.randint(0, 999) |
| |
|
| | prompt = GoogleTranslator(source='ru', target='en').translate(prompt) |
| | print(f'\033[1mGeneration {key} translation:\033[0m {prompt}') |
| |
|
| | prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect." |
| | print(f'\033[1mGeneration {key}:\033[0m {prompt}') |
| |
|
| | |
| | if seed == -1: |
| | seed = random.randint(1, 1000000000) |
| |
|
| | payload = { |
| | "inputs": prompt, |
| | "is_negative": is_negative, |
| | "steps": steps, |
| | "cfg_scale": cfg_scale, |
| | "seed": seed, |
| | "strength": strength |
| | } |
| |
|
| | response = requests.post(api_url, headers=headers, json=payload, timeout=timeout) |
| | if response.status_code != 200: |
| | print(f"Error: Failed to get image. Response status: {response.status_code}") |
| | print(f"Response content: {response.text}") |
| | if response.status_code == 503: |
| | raise gr.Error(f"{response.status_code} : The model is being loaded") |
| | raise gr.Error(f"{response.status_code}") |
| | |
| | try: |
| | image_bytes = response.content |
| | image = Image.open(io.BytesIO(image_bytes)) |
| | print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})') |
| |
|
| | |
| | output_path = f"./output_{key}.png" |
| | image.save(output_path) |
| | |
| | return output_path, seed |
| | except Exception as e: |
| | print(f"Error when trying to open the image: {e}") |
| | return None, None |
| |
|
| | css = """ |
| | #app-container { |
| | max-width: 600px; |
| | margin-left: auto; |
| | margin-right: auto; |
| | } |
| | #title-container { |
| | display: flex; |
| | align-items: center; |
| | justify-content: center; |
| | } |
| | #title-icon { |
| | width: 32px; /* Adjust the width of the icon as needed */ |
| | height: auto; |
| | margin-right: 10px; /* Space between icon and title */ |
| | } |
| | #title-text { |
| | font-size: 24px; /* Adjust font size as needed */ |
| | font-weight: bold; |
| | } |
| | """ |
| | with gr.Blocks(js=js) as demo: |
| | inp = gr.Textbox(placeholder="What is your name?") |
| | out = gr.Textbox() |
| | inp.change(welcome, inp, out) |
| | |
| | with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app: |
| | gr.HTML(""" |
| | <center> |
| | <div id="title-container"> |
| | <img id="title-icon" src="icon.jpg" alt="Icon"> |
| | <h1 id="title-text">FLUX Capacitor</h1> |
| | </div> |
| | </center> |
| | """+html) |
| |
|
| | with gr.Column(elem_id="app-container"): |
| | with gr.Row(): |
| | with gr.Column(elem_id="prompt-container"): |
| | with gr.Row(): |
| | text_prompt = gr.Textbox(label="Prompt", placeholder="Enter a prompt here", lines=2, elem_id="prompt-text-input") |
| | with gr.Row(): |
| | with gr.Accordion("Advanced Settings", open=False): |
| | negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="What should not be in the image", value="(deformed, distorted, disfigured), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, misspellings, typos", lines=3, elem_id="negative-prompt-text-input") |
| | steps = gr.Slider(label="Sampling steps", value=35, minimum=1, maximum=100, step=1) |
| | cfg = gr.Slider(label="CFG Scale", value=7, minimum=1, maximum=20, step=1) |
| | method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"]) |
| | strength = gr.Slider(label="Strength", value=0.7, minimum=0, maximum=1, step=0.001) |
| | seed = gr.Slider(label="Seed", value=-1, minimum=-1, maximum=1000000000, step=1) |
| | huggingface_api_key = gr.Textbox(label="Hugging Face API Key (required for API calls)", placeholder="Enter your Hugging Face API Key here", type="password", elem_id="api-key") |
| | use_dev = gr.Checkbox(label="Use Dev API", value=False, elem_id="use-dev-checkbox") |
| |
|
| | with gr.Row(): |
| | text_button = gr.Button("Run", variant='primary', elem_id="gen-button") |
| | with gr.Row(): |
| | image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery") |
| | seed_output = gr.Textbox(label="Seed Used", elem_id="seed-output") |
| | |
| | |
| | text_button.click(query, inputs=[text_prompt, negative_prompt, steps, cfg, method, seed, strength, huggingface_api_key, use_dev], outputs=[image_output, seed_output]) |
| |
|
| | app.launch(show_api=True, share=False) |