README.md

metadata

title: CompVis Stable Diffusion V1 4
emoji: 🏃
colorFrom: pink
colorTo: purple
sdk: gradio
pinned: false
license: bigscience-openrail-m
sdk_version: 5.12.0

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118 # GPU support pip install diffusers transformers flask pillow accelerate from diffusers import StableDiffusionPipeline import torch

Authenticate Hugging Face

from huggingface_hub import login login(token="your_hugging_face_token")

Load Stable Diffusion v1-4

model_id = "CompVis/stable-diffusion-v1-4" pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) pipe = pipe.to("cuda") # Use GPU for faster performance prompt = "A luxurious futuristic bathroom with marble walls and golden accents, panoramic views of a tropical jungle, ultra-realistic, 32k resolution" num_steps = 50 # Number of diffusion steps guidance_scale = 7.5 # Higher = more faithful to the prompt

Generate an image

image = pipe(prompt, num_inference_steps=num_steps, guidance_scale=guidance_scale).images[0]

Save the image

image.save("generated_image.png") from flask import Flask, request, jsonify, send_file from diffusers import StableDiffusionPipeline import torch

app = Flask(name)

Load Stable Diffusion v1-4

model_id = "CompVis/stable-diffusion-v1-4" pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16) pipe = pipe.to("cuda")

@app.route("/generate", methods=["POST"]) def generate_image(): data = request.json prompt = data.get("prompt", "A beautiful fantasy landscape") num_steps = data.get("steps", 50) guidance_scale = data.get("guidance_scale", 7.5)

# Generate image
image = pipe(prompt, num_inference_steps=num_steps, guidance_scale=guidance_scale).images[0]
output_path = "output.png"
image.save(output_path)

return send_file(output_path, mimetype="image/png")

if name == "main": app.run(host="0.0.0.0", port=5000)

Stable Diffusion v1-4 Image Generator

Prompt:


Inference Steps:


Guidance Scale:


Generate Image

<h2>Generated Image:</h2>
<img id="generated-image" alt="Generated Image" style="max-width: 100%;">

<script>
    document.getElementById("image-form").addEventListener("submit", async (event) => {
        event.preventDefault();

        const prompt = document.getElementById("prompt").value;
        const steps = document.getElementById("steps").value;
        const guidanceScale = document.getElementById("guidance_scale").value;

        const response = await fetch("http://localhost:5000/generate", {
            method: "POST",
            headers: {
                "Content-Type": "application/json",
            },
            body: JSON.stringify({ prompt, steps, guidance_scale: guidanceScale }),
        });

        if (response.ok) {
            const blob = await response.blob();
            const url = URL.createObjectURL(blob);
            document.getElementById("generated-image").src = url;
        } else {
            console.error("Error generating image");
        }
    });
</script>