VaradBhagwat5/structure-aware-medical-diffusion

A structure-aware conditional diffusion framework for enhancing degraded medical images in low-resource radiology settings, with explicit structural preservation constraints and comparison against GAN-based methods. # Teammate C — Backend + Frontend ## Project structure ``` api/ main.py ← FastAPI app, /enhance endpoint infer.py ← ESRGAN / Pix2Pix inference wrapper requirements.txt frontend/src/app/ services/enhancement.service.ts ← HTTP client components/enhancer/ enhancer.component.ts ← logic enhancer.component.html ← UI: upload · slider · heatmap enhancer.component.scss ← dark-theme styles app.module.ts ``` --- ## Backend setup ```bash cd api python -m venv .venv && source .venv/bin/activate pip install -r requirements.txt uvicorn main:app --reload --port 8000 ``` Health check → localhost ### Connecting real model checkpoints Open `infer.py` and replace the `TODO` lines with your actual checkpoint paths: ```python # ESRGAN m.load_state_dict(torch.load("checkpoints/esrgan_x4.pth", map_location=self.device)) # Pix2Pix m.load_state_dict(torch.load("checkpoints/pix2pix.pth", map_location=self.device)) ``` --- ## Frontend setup ```bash cd frontend npm install ng serve # dev server → localhost ``` ### UI features | Feature | Description | |---|---| | Drag-and-drop upload | Drop zone or click-to-browse | | Model selector | ESRGAN (super-res) · Pix2Pix (translation) | | Scale buttons | ×2 / ×4 / ×8 (ESRGAN) | | Strength slider | Blend 0–100% enhancement | | Before/after comparison | Draggable divider slider | | Attention heatmap | Toggle canvas overlay | | Download | Save enhanced PNG | --- ## API reference ### `POST /enhance` | Field | Type | Default | Description | |---|---|---|---| | `file` | image/* | — | Input image (max 20 MB) | | `model` | string | `esrgan` | `esrgan` or `pix2pix` | | `scale` | int | `4` | Upscale factor (ESRGAN only) | | `strength` | float | `1.0` | Enhancement blend (0.0–1.0) | **Response** ```json { "enhanced_image": " ", "heatmap": " ", "model": "esrgan", "scale": 4, "inference_time_s": 0.342, "original_size": [512, 512], "enhanced …