import torch
from diffusers import StableDiffusionPipeline

pipe = StableDiffusionPipeline.from_pretrained(
    "P-RAJIV/cxr_stable_diffusion_v1_4",
    torch_dtype=torch.float16
).to("cuda")

prompt = "Normal chest X-ray"

image = pipe(prompt, num_inference_steps=30, guidance_scale=7.5).images[0]
image.save("output.png")

markdown

🧪 Example Prompts
"Normal chest X-ray"
"Chest X-ray showing cardiomegaly"
"Lung opacity in right lower lobe"
"Severe pneumonia chest radiograph"

⚠️ Limitations
Generated images are synthetic and not for clinical use
May produce anatomically inconsistent outputs
Performance depends heavily on prompt quality

📚 Training Details
Base Model: Stable Diffusion v1.5
Domain: Chest X-ray imaging
Fine-tuning: Text-to-image diffusion training

🧠 Intended Use
Research in medical imaging
Data augmentation
Diffusion model experimentation

❗ Disclaimer
This model is not intended for medical diagnosis or clinical decision-making.