Rendernet/SuperfastStableDiffusion

1import numpy as np2import gradio as gr3import requests4import time5import json6import base647import os8from io import BytesIO9import PIL10from PIL.ExifTags import TAGS11import html12import re13 14 15class RenderNet:16    def __init__(self, api_key, base=None):17        self.base = base or "https://app.rendernet.ai/api/"18        self.headers = {19            "rendernetapikey": api_key20        }21    22    def generate(self, params):23        response = self._post(f"{self.base}/generate", params)24        return response.json()25    26    def get_job(self, job_id):27        response = self._get(f"{self.base}/job/{job_id}")28        return response.json()29 30    def wait(self, job):31        job_result = job32 33        while job_result['status'] not in ['succeeded', 'failed']:34            time.sleep(1)35            job_result = self.get_job(job['job'])36            print("Job Result:")37            print(job_result)38        return job_result39 40    def list_models(self):41        response =[42                    'dreamshaper',        43                    'ghost_mix',44                    'proto_vision',       45                    'meina_unreal',46                    'realistic_vision',   47                    'animerge',48                    'oil_painting',       49                    'absolute_reality',50                    'meinamix',           51                    'rpg',52                    'western_animation',  53                    'dynavision',54                    'Realvis_XL',         55                    'abyss_orange_mix',56                    'anything_v5',       57                    'dreamshaper_xl',58                    'epic_realism',       59                    'comicbook_style',60                    'newdawnxl',          61                    'nextphoto',62                    'nightvisionxl',      63                    'juggernaut',64                    'cyber_realistic',    65                    'real_cartoon',66                    'unstable_diffusers', 67                    'cant_believe',68                    'majicmix_fantasy',   69                    'analog_madness',70                    'blazing_drive',     71                    'mysteriousxl',72                    'night_sky',         73                    'never_ending',74                    'dark_sushi',        75                    'meina_pastel',76                    'meina_alter',        77                    'counterfeitxl_v10',78                    'plagion_v10',        79                    'replicant_v3.0'80                    ]81 82        return response83 84    def list_samplers(self):85        response = [86                    'DPM++ SDE Karras',87                    'DPM++ 2M Karras'88                    'DPM++ 2S a Karras',89                    'Euler a',90                    'DPM++ 2M SDE Karras'91                    ]92        return response93 94    def _post(self, url, params):95        headers = {96            **self.headers,97            "Content-Type": "application/json"98        }99        response = requests.post(url, headers=headers, data=json.dumps(params))100 101        if response.status_code != 200:102            raise Exception(f"Bad RenderNet Response: {response.status_code}")103 104        return response105 106    def _get(self, url):107        response = requests.get(url, headers=self.headers)108 109        if response.status_code != 200:110            raise Exception(f"Bad RenderNet Response: {response.status_code}")111 112        return response113 114 115def remove_id_and_ext(text):116    text = re.sub(r'\[.*\]$', '', text)117    extension = text[-12:].strip()118    if extension == "safetensors":119        text = text[:-13]120    elif extension == "ckpt":121        text = text[:-4]122    return text123 124def get_data(text):125    results = {}126    patterns = {127        'prompt': r'(.*)',128        'negative_prompt': r'Negative prompt: (.*)',129        'steps': r'Steps: (\d+),',130        'seed': r'Seed: (\d+),',131        'sampler': r'Sampler:\s*([^\s,]+(?:\s+[^\s,]+)*)', 132        'model': r'Model:\s*([^\s,]+)',133        'cfg_scale': r'CFG scale:\s*([\d\.]+)',134        'size': r'Size:\s*([0-9]+x[0-9]+)'135        }136    for key in ['prompt', 'negative_prompt', 'steps', 'seed', 'sampler', 'model', 'cfg_scale', 'size']:137        match = re.search(patterns[key], text)138        if match:139            results[key] = match.group(1)140        else:141            results[key] = None142    if results['size'] is not None:143        w, h = results['size'].split("x")144        results['w'] = w145        results['h'] = h146    else:147        results['w'] = None148        results['h'] = None149    return results150 151def send_to_txt2img(image):152    153    result = {tabs: gr.Tabs.update(selected="t2i")}154 155    try:156        text = image.info['parameters']157        data = get_data(text)158        result[prompt] = gr.update(value=data['prompt'])159        result[negative_prompt] = gr.update(value=data['negative_prompt']) if data['negative_prompt'] is not None else gr.update()160        result[steps] = gr.update(value=int(data['steps'])) if data['steps'] is not None else gr.update()161        result[seed] = gr.update(value=int(data['seed'])) if data['seed'] is not None else gr.update()162        result[cfg_scale] = gr.update(value=float(data['cfg_scale'])) if data['cfg_scale'] is not None else gr.update()163        result[width] = gr.update(value=int(data['w'])) if data['w'] is not None else gr.update()164        result[height] = gr.update(value=int(data['h'])) if data['h'] is not None else gr.update()165        result[sampler] = gr.update(value=data['sampler']) if data['sampler'] is not None else gr.update()166        if model in model_names:167            result[model] = gr.update(value=model_names[model])168        else:169            result[model] = gr.update()170        return result171 172    except Exception as e:173        print(e)174        result[prompt] = gr.update()175        result[negative_prompt] = gr.update()176        result[steps] = gr.update()177        result[seed] = gr.update()178        result[cfg_scale] = gr.update()179        result[width] = gr.update()180        result[height] = gr.update()181        result[sampler] = gr.update()182        result[model] = gr.update()183 184        return result185 186 187rendernet_client = RenderNet(api_key=os.getenv("API_KEY"))188model_list = rendernet_client.list_models()189model_names = {}190 191for model_name in model_list:192    name_without_ext = remove_id_and_ext(model_name)193    print(name_without_ext)194    model_names[name_without_ext] = model_name195    print(model_names)196 197def txt2img(prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed):198    result = rendernet_client.generate({199        "prompt": prompt,200        "negative_prompt": negative_prompt,201        "model": model,202        "steps": steps,203        "sampler": sampler,204        "cfg_scale": cfg_scale,205        "width": width,206        "height": height,207        "seed": seed208    })209    210    print("Result Value:")211    print("")212    print(result)213 214    print("Job Value:")215    print("")216    job = rendernet_client.wait(result)217 218    return job["imageUrl"]219    220# Static Image URL221static_image_url = "https://baseavaar2.s3.amazonaws.com/banner.png"222static_image_link_url="https://rendernet.ai"223 224css = """225#generate {226    height: 100%;227}228"""229 230with gr.Blocks(css=css) as demo:231 232    # Add a Row for the Static Image233    with gr.Row():234        with gr.Column():235            static_image_with_link = gr.HTML(f'<a href="{static_image_link_url}" target="_blank"><img src="{static_image_url}" /></a>')236            237    with gr.Row():238        with gr.Column(scale=6):239            model = gr.Dropdown(interactive=True, value="dreamshaper", show_label=True, label="Stable Diffusion Checkpoint", choices=rendernet_client.list_models())240  241        with gr.Column(scale=1):242            gr.Markdown(elem_id="powered-by-rendernet", value="AUTOMATIC1111 Stable Diffusion Web UI.<br>Powered by [RenderNet](https://rendernet.ai).<br>For advanced features and faster generation times check out our API and Website(https://rendernet.ai/).")243 244 245    with gr.Tabs() as tabs:246        with gr.Tab("txt2img", id='t2i'):247            with gr.Row():248                with gr.Column(scale=6, min_width=600):249                    prompt = gr.Textbox("a master jedi cat in star wars with a lightsaber, wearing a jedi cloak hood in the kitchen (cat:1.3)", placeholder="Prompt", show_label=False, lines=3)250                    negative_prompt = gr.Textbox(placeholder="Negative Prompt", show_label=False, lines=3, value="(worst quality, low quality, normal quality:2)")251                with gr.Column():252                    text_button = gr.Button("Generate", variant='primary', elem_id="generate")253                    254            with gr.Row():255                with gr.Column(scale=3):256                    with gr.Tab("Generation"):257                        with gr.Row():258                            with gr.Column(scale=1):259                                sampler = gr.Dropdown(show_label=True, value="DPM++ SDE Karras", label="Sampling Method", choices=rendernet_client.list_samplers())260                                261                            with gr.Column(scale=1):262                                steps = gr.Slider(label="Sampling Steps", minimum=1, maximum=30, value=25, step=1)263    264                        with gr.Row():265                            with gr.Column(scale=1):266                                width = gr.Slider(label="Width", maximum=1024, value=512, step=8)267                                height = gr.Slider(label="Height", maximum=1024, value=512, step=8)268                            269                            with gr.Column(scale=1):270                                batch_size = gr.Slider(label="Batch Size", maximum=1, value=1)271                                batch_count = gr.Slider(label="Batch Count", maximum=1, value=1)272    273                        cfg_scale = gr.Slider(label="CFG Scale", minimum=1, maximum=20, value=7, step=1)274                        seed = gr.Number(label="Seed", value=-1)275    276                    277                with gr.Column(scale=2):278                    image_output = gr.Image(value="https://app.rendernet.ai/userfiles/1699956614571.5938.png")279    280            text_button.click(txt2img, inputs=[prompt, negative_prompt, model, steps, sampler, cfg_scale, width, height, seed], outputs=image_output)            281 282 283demo.queue(max_size=80, api_open=False).launch(max_threads=256)284