Program not working on GPU but works on CPU

Intermediate
24

chatgpt improved on the code, and now there is some result but imperfect.

Image

generated_image_6072683
generated_image_6072683512×512 472 KB

Code

from flask import Flask, send_file, request
from diffusers import StableDiffusionXLPipeline
import torch, os, numpy as np, random, logging

app = Flask(__name__)
model_dir = "D:\\Ganu\\AIImage\\apache-webserver\\Apache24\\htdocs"
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
print("Using device:", device)
pipeline = None

def load_pipeline():
    global pipeline
    if pipeline is not None:
        return

    print(f"[INFO] Loading full SDXL pipeline on {device} with float32...")

    pipeline_local = StableDiffusionXLPipeline.from_pretrained(
        "stabilityai/stable-diffusion-xl-base-1.0",
        torch_dtype=torch.float32,
        use_safetensors=True
    ).to(device)

    pipeline_local.enable_attention_slicing()
    pipeline_local.safety_checker = lambda images, **kwargs: (images, False)

    pipeline_local.set_progress_bar_config(disable=True)
    pipeline = pipeline_local
    logging.info("[INFO] Full pipeline loaded on GPU.")

@app.route("/")
def home():
    return """
    <html>
        <head><title>SDXL Generator</title></head>
        <body style="font-family: sans-serif;">
            <h1>Stable Diffusion XL (float32)</h1>
            <form action="/generate" method="get">
                Prompt: <input type="text" name="prompt" size="60">
                <input type="submit" value="Generate">
            </form>
            <p>Try: <a href="/generate?prompt=Futuristic+Indian+market">Futuristic Indian market</a></p>
        </body>
    </html>
    """

@app.route("/generate")
def generate_image():
    load_pipeline()

    seed = request.args.get("seed", default=random.randint(0, 9999999), type=int)
    torch.manual_seed(seed)
    np.random.seed(seed)

    prompt = request.args.get("prompt", default="", type=str).strip()
    if not prompt:
        return "Error: prompt required", 400

    width = request.args.get("width", default=512, type=int)
    height = request.args.get("height", default=512, type=int)

    def round_to_64(x): return max(64, int(round(x / 64)) * 64)
    width = min(round_to_64(width), 768)
    height = min(round_to_64(height), 768)

    negative_prompt = (
        "text, watermark, blurry, deformed, double face, bad proportions, UI elements"
    )

    print(f"[INFO] Generating image (seed={seed}, size={width}x{height})")

    result = pipeline(
        prompt=prompt,
        negative_prompt=negative_prompt,
        width=width,
        height=height,
        guidance_scale=7.5,
        num_inference_steps=20
    )

    image = result.images[0]
    output_dir = os.path.join(model_dir, "outputs")
    os.makedirs(output_dir, exist_ok=True)
    output_path = os.path.join(output_dir, f"generated_image_{seed}.png")
    image.save(output_path)

    print(f"[INFO] Image saved: {output_path}")
    return send_file(output_path, mimetype='image/png')

if __name__ == "__main__":
    logging.basicConfig(level=logging.INFO)
    app.run(host="127.0.0.1", port=80, debug=True)
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