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import gradio as gr |
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import requests |
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import io |
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import random |
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import os |
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from PIL import Image |
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list_models = [ |
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"SDXL 1.0", "SD 1.5", "OpenJourney", "Anything V4.0", |
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"Disney Pixar Cartoon", "Pixel Art XL", "Dalle 3 XL", |
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"Midjourney V4 XL", "Open Diffusion V1", "SSD 1B", |
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"Segmind Vega", "Animagine XL-2.0", "Animagine XL-3.0", |
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"OpenDalle", "OpenDalle V1.1", "PlaygroundV2 1024px aesthetic", |
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] |
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def generate_txt2img(current_model, prompt, is_negative=False, image_style="None style", steps=50, cfg_scale=7, seed=None): |
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if current_model == "SD 1.5": |
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API_URL = "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5" |
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elif current_model == "SDXL 1.0": |
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API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0" |
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elif current_model == "OpenJourney": |
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API_URL = "https://api-inference.huggingface.co/models/prompthero/openjourney" |
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elif current_model == "Anything V4.0": |
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API_URL = "https://api-inference.huggingface.co/models/xyn-ai/anything-v4.0" |
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elif current_model == "Disney Pixar Cartoon": |
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API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/disney-pixar-cartoon" |
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elif current_model == "Pixel Art XL": |
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API_URL = "https://api-inference.huggingface.co/models/nerijs/pixel-art-xl" |
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elif current_model == "Dalle 3 XL": |
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API_URL = "https://api-inference.huggingface.co/models/openskyml/dalle-3-xl" |
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elif current_model == "Midjourney V4 XL": |
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API_URL = "https://api-inference.huggingface.co/models/openskyml/midjourney-v4-xl" |
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elif current_model == "Open Diffusion V1": |
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API_URL = "https://api-inference.huggingface.co/models/openskyml/open-diffusion-v1" |
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elif current_model == "SSD 1B": |
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API_URL = "https://api-inference.huggingface.co/models/segmind/SSD-1B" |
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elif current_model == "Segmind Vega": |
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API_URL = "https://api-inference.huggingface.co/models/segmind/Segmind-Vega" |
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elif current_model == "Animagine XL-2.0": |
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API_URL = "https://api-inference.huggingface.co/models/Linaqruf/animagine-xl-2.0" |
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elif current_model == "Animagine XL-3.0": |
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API_URL = "https://api-inference.huggingface.co/models/cagliostrolab/animagine-xl-3.0" |
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elif current_model == "OpenDalle": |
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API_URL = "https://api-inference.huggingface.co/models/dataautogpt3/OpenDalle" |
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elif current_model == "OpenDalle V1.1": |
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API_URL = "https://api-inference.huggingface.co/models/dataautogpt3/OpenDalleV1.1" |
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elif current_model == "PlaygroundV2 1024px aesthetic": |
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API_URL = "https://api-inference.huggingface.co/models/playgroundai/playground-v2-1024px-aesthetic" |
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API_TOKEN = os.environ.get("HF_READ_TOKEN") |
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headers = {"Authorization": f"Bearer {API_TOKEN}"} |
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if image_style == "None style": |
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payload = { |
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"inputs": prompt + ", 8k", |
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"is_negative": is_negative, |
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"steps": steps, |
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"cfg_scale": cfg_scale, |
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"seed": seed if seed is not None else random.randint(-1, 2147483647) |
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} |
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elif image_style == "Cinematic": |
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payload = { |
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"inputs": prompt + ", realistic, detailed, textured, skin, hair, eyes, by Alex Huguet, Mike Hill, Ian Spriggs, JaeCheol Park, Marek Denko", |
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"is_negative": is_negative + ", abstract, cartoon, stylized", |
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"steps": steps, |
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"cfg_scale": cfg_scale, |
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"seed": seed if seed is not None else random.randint(-1, 2147483647) |
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} |
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elif image_style == "Digital Art": |
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payload = { |
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"inputs": prompt + ", faded , vintage , nostalgic , by Jose Villa , Elizabeth Messina , Ryan Brenizer , Jonas Peterson , Jasmine Star", |
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"is_negative": is_negative + ", sharp , modern , bright", |
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"steps": steps, |
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"cfg_scale": cfg_scale, |
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"seed": seed if seed is not None else random.randint(-1, 2147483647) |
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} |
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elif image_style == "Portrait": |
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payload = { |
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"inputs": prompt + ", soft light, sharp, exposure blend, medium shot, bokeh, (hdr:1.4), high contrast, (cinematic, teal and orange:0.85), (muted colors, dim colors, soothing tones:1.3), low saturation, (hyperdetailed:1.2), (noir:0.4), (natural skin texture, hyperrealism, soft light, sharp:1.2)", |
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"is_negative": is_negative, |
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"steps": steps, |
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"cfg_scale": cfg_scale, |
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"seed": seed if seed is not None else random.randint(-1, 2147483647) |
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} |
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image_bytes = requests.post(API_URL, headers=headers, json=payload).content |
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image = Image.open(io.BytesIO(image_bytes)) |
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return image |
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def read_css_from_file(filename): |
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with open(filename, "r") as file: |
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return file.read() |
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css = read_css_from_file("style.css") |
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PTI_SD_DESCRIPTION = ''' |
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<div id="content_align"> |
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<span style="color:darkred;font-size:32px;font-weight:bold"> |
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Stable Diffusion Models Image Generation |
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</span> |
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</div> |
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<div id="content_align"> |
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<span style="color:blue;font-size:16px;font-weight:bold"> |
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Generate images directly from text prompts (no parameter tuning required) |
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</span> |
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</div> |
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<div id="content_align" style="margin-top: 10px;"> |
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</div> |
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''' |
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with gr.Blocks(css=css) as demo: |
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gr.Markdown(PTI_SD_DESCRIPTION) |
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with gr.Row(): |
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with gr.Column(): |
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current_model = gr.Dropdown(label="Select Model", choices=list_models, value=list_models[1]) |
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text_prompt = gr.Textbox(label="Input Prompt", placeholder="Example: A blue jay ", lines=2) |
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with gr.Column(): |
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negative_prompt = gr.Textbox(label="Negative Prompt (optional)", placeholder="Example: blurry, unfocused", lines=2) |
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image_style = gr.Dropdown(label="Select Style", choices=["None style", "Cinematic", "Digital Art", "Portrait"], value="None style") |
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generate_button = gr.Button("Generate Image", variant='primary') |
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with gr.Row(): |
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image_output = gr.Image(type="pil", label="Image Output") |
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generate_button.click(generate_txt2img, inputs=[current_model, text_prompt, negative_prompt, image_style], outputs=image_output) |
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demo.launch() |
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