Create app.py

app.py

@@ -0,0 +1,232 @@
+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
+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
+    #url_sd1 = os.getenv("url_sd1")
+    #url_sd2 = os.getenv("url_sd2")
+    
+    #url_sd3 = os.getenv("url_sd3")
+    #url_sd4 = os.getenv("url_sd4")
+
+    print("--3-->", url_sd3)
+    print("--4-->", url_sd4)
+    
+    #url_sd5 = os.getenv("url_sd5")
+    #url_sd6 = os.getenv("url_sd6")
+    #hf_token = os.getenv("hf_token")
+    if task == "Playground v2":
+        playground = str(os.getenv("playground"))
+        with closing(create_connection("wss://ashrafb-arpr.hf.space/queue/join", timeout=60)) as conn:
+            conn.send('{"fn_index":0,"session_hash":""}')
+            conn.send(f'{{"fn_index":0,"data":["{prompt}"],"session_hash":""}}')
+            conn.recv()
+            conn.recv()
+            conn.recv()
+            conn.recv()
+            a = conn.recv()
+            print(">> A:", a)
+            photo = json.loads(a)['output']['data'][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
+            
+    if task == "Artigen v3":
+        artigen = str(os.getenv("artigen"))
+        with closing(create_connection("wss://ashrafb-arv3s.hf.space/queue/join", timeout=60)) as conn:
+            conn.send('{"fn_index":0,"session_hash":""}')
+            conn.send(f'{{"fn_index":0,"data":["{prompt}", 0, "No style"],"session_hash":""}}')
+            conn.recv()
+            conn.recv()
+            conn.recv()
+            conn.recv()
+            a = conn.recv()
+            print(">> A:", a)
+            photo = json.loads(a)['output']['data'][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
+        
+    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:
+            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
+
+
+def mirror(image_output, scale_by, method, gfpgan, codeformer):
+
+    url_up = os.getenv("url_up")
+    url_up_f = os.getenv("url_up_f")
+
+    print("~~ up", url_up)
+    print("~~ f", url_up_f)
+
+    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":""}
+    print(data)
+    r = requests.post(f"{url_up}", json=data, timeout=100)
+    print(r.text)
+    ph = f"{url_up_f}" + str(r.json()['data'][0][0]['name'])
+    return ph
+
+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;
+    }
+footer {visibility: hidden !important;}
+#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)
+        
+        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)
+    
+demo.queue(concurrency_count=24)
+demo.launch()