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| import gradio as gr | |
| import requests | |
| import time | |
| import json | |
| from contextlib import closing | |
| from websocket import create_connection | |
| from deep_translator import GoogleTranslator | |
| from langdetect import detect | |
| import os | |
| from PIL import Image | |
| import io | |
| from io import BytesIO | |
| import base64 | |
| import re | |
| from gradio_client import Client | |
| from fake_useragent import UserAgent | |
| import random | |
| def flip_text(prompt, negative_prompt, task, steps, sampler, cfg_scale, seed): | |
| result = {"prompt": prompt,"negative_prompt": negative_prompt,"task": task,"steps": steps,"sampler": sampler,"cfg_scale": cfg_scale,"seed": seed} | |
| print(result) | |
| try: | |
| language = detect(prompt) | |
| if language == 'ru': | |
| prompt = GoogleTranslator(source='ru', target='en').translate(prompt) | |
| print(prompt) | |
| except: | |
| pass | |
| prompt = re.sub(r'[^a-zA-Zа-яА-Я\s]', '', prompt) | |
| cfg = int(cfg_scale) | |
| steps = int(steps) | |
| seed = int(seed) | |
| width = 1024 | |
| height = 1024 | |
| if task == "Playground v2": | |
| ua = UserAgent() | |
| headers = { | |
| 'user-agent': f'{ua.random}' | |
| } | |
| client = Client("https://ashrafb-arpr.hf.space/", headers=headers) | |
| result = client.predict(prompt, fn_index=0) | |
| return result | |
| if task == "Artigen v3": | |
| ua = UserAgent() | |
| headers = { | |
| 'user-agent': f'{ua.random}' | |
| } | |
| client = Client("https://ashrafb-arv3s.hf.space/", headers=headers) | |
| result = client.predict(prompt,0,"Cinematic", fn_index=0) | |
| return result | |
| try: | |
| with closing(create_connection("wss://google-sdxl.hf.space/queue/join")) as conn: | |
| conn.send('{"fn_index":3,"session_hash":""}') | |
| conn.send(f'{{"data":["{prompt}, 4k photo","[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry",7.5,"(No style)"],"event_data":null,"fn_index":3,"session_hash":""}}') | |
| c = 0 | |
| while c < 60: | |
| status = json.loads(conn.recv())['msg'] | |
| if status == 'estimation': | |
| c += 1 | |
| time.sleep(1) | |
| continue | |
| if status == 'process_starts': | |
| break | |
| photo = json.loads(conn.recv())['output']['data'][0][0] | |
| photo = photo.replace('data:image/jpeg;base64,', '').replace('data:image/png;base64,', '') | |
| photo = Image.open(io.BytesIO(base64.decodebytes(bytes(photo, "utf-8")))) | |
| return photo | |
| except: | |
| try: | |
| ua = UserAgent() | |
| headers = { | |
| 'authority': 'ehristoforu-dalle-3-xl-lora-v2.hf.space', | |
| 'accept': 'text/event-stream', | |
| 'accept-language': 'ru,en;q=0.9,la;q=0.8,ja;q=0.7', | |
| 'cache-control': 'no-cache', | |
| 'referer': 'https://ehristoforu-dalle-3-xl-lora-v2.hf.space/?__theme=light', | |
| 'sec-ch-ua': '"Not_A Brand";v="8", "Chromium";v="120", "YaBrowser";v="24.1", "Yowser";v="2.5"', | |
| 'sec-ch-ua-mobile': '?0', | |
| 'sec-ch-ua-platform': '"Windows"', | |
| 'sec-fetch-dest': 'empty', | |
| 'sec-fetch-mode': 'cors', | |
| 'sec-fetch-site': 'same-origin', | |
| 'user-agent': f'{ua.random}' | |
| } | |
| client = Client("ehristoforu/dalle-3-xl-lora-v2", headers=headers) | |
| result = client.predict(prompt,"(deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation",True,0,1024,1024,6,True, api_name='/run') | |
| return result[0][0]['image'] | |
| except: | |
| try: | |
| ua = UserAgent() | |
| headers = { | |
| 'authority': 'nymbo-sd-xl.hf.space', | |
| 'accept': 'text/event-stream', | |
| 'accept-language': 'ru,en;q=0.9,la;q=0.8,ja;q=0.7', | |
| 'cache-control': 'no-cache', | |
| 'referer': 'https://nymbo-sd-xl.hf.space/?__theme=light', | |
| 'sec-ch-ua': '"Not_A Brand";v="8", "Chromium";v="120", "YaBrowser";v="24.1", "Yowser";v="2.5"', | |
| 'sec-ch-ua-mobile': '?0', | |
| 'sec-ch-ua-platform': '"Windows"', | |
| 'sec-fetch-dest': 'empty', | |
| 'sec-fetch-mode': 'cors', | |
| 'sec-fetch-site': 'same-origin', | |
| 'user-agent': f'{ua.random}' | |
| } | |
| client = Client("Nymbo/SD-XL", headers=headers) | |
| result = client.predict(prompt,negative_prompt,"","",True,False,False,0,1024,1024,7,1,25,25,False,api_name="/run") | |
| return result | |
| except: | |
| try: | |
| ua = UserAgent() | |
| headers = { | |
| 'authority': 'radames-real-time-text-to-image-sdxl-lightning.hf.space', | |
| 'accept': 'text/event-stream', | |
| 'accept-language': 'ru,en;q=0.9,la;q=0.8,ja;q=0.7', | |
| 'cache-control': 'no-cache', | |
| 'referer': 'https://radames-real-time-text-to-image-sdxl-lightning.hf.space/?__theme=light', | |
| 'sec-ch-ua': '"Not_A Brand";v="8", "Chromium";v="120", "YaBrowser";v="24.1", "Yowser";v="2.5"', | |
| 'sec-ch-ua-mobile': '?0', | |
| 'sec-ch-ua-platform': '"Windows"', | |
| 'sec-fetch-dest': 'empty', | |
| 'sec-fetch-mode': 'cors', | |
| 'sec-fetch-site': 'same-origin', | |
| 'user-agent': f'{ua.random}' | |
| } | |
| client = Client("radames/Real-Time-Text-to-Image-SDXL-Lightning", headers=headers) | |
| result = client.predict(prompt, [], 0, random.randint(1, 999999), fn_index=0) | |
| return result | |
| except: | |
| try: | |
| ua = UserAgent() | |
| headers = { | |
| 'user-agent': f'{ua.random}' | |
| } | |
| client = Client("https://ashrafb-arpr.hf.space/", headers=headers) | |
| result = client.predict(prompt, fn_index=0) | |
| return result | |
| except: | |
| ua = UserAgent() | |
| headers = { | |
| 'user-agent': f'{ua.random}' | |
| } | |
| client = Client("https://ashrafb-arv3s.hf.space/", headers=headers) | |
| result = client.predict(prompt,0,"Cinematic", fn_index=0) | |
| return result | |
| def mirror(image_output, scale_by, method, gfpgan, codeformer): | |
| url_up = "https://darkstorm2150-protogen-web-ui.hf.space/run/predict/" | |
| url_up_f = "https://darkstorm2150-protogen-web-ui.hf.space/file=" | |
| scale_by = int(scale_by) | |
| gfpgan = int(gfpgan) | |
| codeformer = int(codeformer) | |
| with open(image_output, "rb") as image_file: | |
| encoded_string2 = base64.b64encode(image_file.read()) | |
| encoded_string2 = str(encoded_string2).replace("b'", '') | |
| encoded_string2 = "data:image/png;base64," + encoded_string2 | |
| data = {"fn_index":81,"data":[0,0,encoded_string2,None,"","",True,gfpgan,codeformer,0,scale_by,512,512,None,method,"None",1,False,[],"",""],"session_hash":""} | |
| r = requests.post(url_up, json=data, timeout=100) | |
| print(r.text) | |
| print(r.json()['data'][0][0]['name']) | |
| ph = "https://darkstorm2150-protogen-web-ui.hf.space/file=" + str(r.json()['data'][0][0]['name']) | |
| print(ph) | |
| response2 = requests.get(ph) | |
| img = Image.open(BytesIO(response2.content)) | |
| return img | |
| css = """ | |
| #generate { | |
| width: 100%; | |
| background: #e253dd !important; | |
| border: none; | |
| border-radius: 50px; | |
| outline: none !important; | |
| color: white; | |
| } | |
| #generate:hover { | |
| background: #de6bda !important; | |
| outline: none !important; | |
| color: #fff; | |
| } | |
| #image_output { | |
| height: 100% !important; | |
| } | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| with gr.Tab("Базовые настройки"): | |
| with gr.Row(): | |
| prompt = gr.Textbox(placeholder="Введите описание изображения...", show_label=True, label='Описание изображения:', lines=3) | |
| with gr.Row(): | |
| task = gr.Radio(interactive=True, value="Stable Diffusion XL 1.0", show_label=True, label="Модель нейросети:", choices=['Stable Diffusion XL 1.0', 'Crystal Clear XL', | |
| 'Juggernaut XL', 'DreamShaper XL', | |
| 'SDXL Niji', 'Cinemax SDXL', 'NightVision XL', | |
| 'Playground v2', 'Artigen v3']) | |
| with gr.Tab("Расширенные настройки"): | |
| with gr.Row(): | |
| negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=True, label='Negative Prompt:', lines=3, value="[deformed | disfigured], poorly drawn, [bad : wrong] anatomy, [extra | missing | floating | disconnected] limb, (mutated hands and fingers), blurry") | |
| with gr.Row(): | |
| sampler = gr.Dropdown(value="DPM++ SDE Karras", show_label=True, label="Sampling Method:", choices=[ | |
| "Euler", "Euler a", "Heun", "DPM++ 2M", "DPM++ SDE", "DPM++ 2M Karras", "DPM++ SDE Karras", "DDIM"]) | |
| with gr.Row(): | |
| steps = gr.Slider(show_label=True, label="Sampling Steps:", minimum=1, maximum=50, value=35, step=1) | |
| with gr.Row(): | |
| cfg_scale = gr.Slider(show_label=True, label="CFG Scale:", minimum=1, maximum=20, value=7, step=1) | |
| with gr.Row(): | |
| seed = gr.Number(show_label=True, label="Seed:", minimum=-1, maximum=1000000, value=-1, step=1) | |
| with gr.Tab("Настройки апскейлинга"): | |
| with gr.Column(): | |
| with gr.Row(): | |
| scale_by = gr.Number(show_label=True, label="Во сколько раз увеличить:", minimum=1, maximum=2, value=2, step=1) | |
| with gr.Row(): | |
| method = gr.Dropdown(show_label=True, value="ESRGAN_4x", label="Алгоритм увеличения", choices=["ScuNET GAN", "SwinIR 4x", "ESRGAN_4x", "R-ESRGAN 4x+", "R-ESRGAN 4x+ Anime6B"]) | |
| with gr.Column(): | |
| with gr.Row(): | |
| gfpgan = gr.Slider(show_label=True, label="Эффект GFPGAN (для улучшения лица)", minimum=0, maximum=1, value=0, step=0.1) | |
| with gr.Row(): | |
| codeformer = gr.Slider(show_label=True, label="Эффект CodeFormer (для улучшения лица)", minimum=0, maximum=1, value=0, step=0.1) | |
| with gr.Column(): | |
| text_button = gr.Button("Сгенерировать изображение", variant='primary', elem_id="generate") | |
| with gr.Column(): | |
| image_output = gr.Image(show_download_button=True, interactive=False, label='Результат:', elem_id='image_output', type='filepath') | |
| text_button.click(flip_text, inputs=[prompt, negative_prompt, task, steps, sampler, cfg_scale, seed], outputs=image_output, concurrency_limit=48) | |
| img2img_b = gr.Button("Увеличить изображение", variant='secondary') | |
| image_i2i = gr.Image(show_label=True, label='Увеличенное изображение:') | |
| img2img_b.click(mirror, inputs=[image_output, scale_by, method, gfpgan, codeformer], outputs=image_i2i, concurrency_limit=48) | |
| demo.launch() |