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DiffusionArtco
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Duplicate from DiffusionArtco/Diffusion50
Browse files- .gitattributes +34 -0
- README.md +13 -0
- app.py +35 -0
.gitattributes
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README.md
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---
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title: ImagineAI Imagine Generator
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emoji: 💩
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colorFrom: yellow
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colorTo: pink
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sdk: gradio
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sdk_version: 3.24.1
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app_file: app.py
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pinned: false
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duplicated_from: DiffusionArtco/Diffusion50
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import gradio as gr
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import requests
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from PIL import Image
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from io import BytesIO
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import base64
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api_url = "https://5cb20b40-572c-426f-9466-995256f9b6eb.id.repl.co/generate_image"
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def generate_image(model="Deliberate", prompt="", seed=0, negative_prompt="", sampler="k_dpmpp_2s_a", steps=50):
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data = "?model=" + model + "&prompt=" + prompt + "&seed=" + str(seed) + "&negative_prompt=" + negative_prompt + "&sampler=" + sampler + "&steps=" + str(steps)
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response = requests.post(api_url + data, timeout=400)
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if response.status_code == 200:
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img_base64 = response.json()["url"]
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img_bytes = base64.b64decode(img_base64)
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img = Image.open(BytesIO(img_bytes))
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return img
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else:
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return None
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inputs = [
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gr.inputs.Dropdown(['Analog Diffusion', 'Anything Diffusion', 'Anything v3', 'ChilloutMix', 'Counterfeit', 'CyriousMix', 'Deliberate', 'Dreamshaper', 'Dreamlike Diffusion', 'Dreamlike Photoreal', 'Experience', 'FaeTastic', 'Hassanblend', 'Mega Merge Diffusion', 'Midjourney Diffusion', 'ModernArt Diffusion', 'Movie Diffusion', 'NeverEnding Dream', 'Perfect World', 'PortraitPlus', 'ProtoGen', 'Protogen Anime', 'Protogen Infinity', 'RealBiter', 'Realism Engine', 'Realistic Vision', 'Rev Animated', 'RPG', 'Seek.art MEGA', 'stable_diffusion', 'stable_diffusion_2.1' , 'Unstable Ink Dream'], label="Model", default="Deliberate"),
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gr.inputs.Textbox(label="Prompt", default=""),
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gr.inputs.Number(label="Seed", default=0),
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gr.inputs.Textbox(label="Negative Prompt", default=""),
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gr.inputs.Dropdown(["k_lms", "k_heun", "k_euler", "k_euler_a", "k_dpm_2", "k_dpm_2_a", "DDIM", "k_dpm_fast", "k_dpm_adaptive", "k_dpmpp_2m", "k_dpmpp_2s_a", "k_dpmpp_sde"], label="Sampler", default="k_dpmpp_2s_a"),
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gr.inputs.Number(label="Steps", default=50)
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]
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outputs = gr.outputs.Image(label="Generated Image", type="pil")
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interface = gr.Interface(generate_image, inputs, outputs, title="Diffusion 50",
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description="<center>Live access to the most popular Diffusion models</center>",
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examples=[])
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interface.launch()
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