Learn Damage Assessment and FastAPI side by side.
Two complete learning tracks. The Damage Assessment track covers xBD dataset preprocessing, ResNet-50 + U-Net, ViT-B/16, Siamese change detection, and ONNX export. The FastAPI track teaches you to build the web API that serves those models — from your first endpoint to production deployment.
Damage Assessment
Build a full satellite-image damage-classification pipeline. Start with 16-bit GeoTIFF preprocessing, then train and compare ResNet-50, ViT, and Siamese architectures on the xBD dataset.
FastAPI
Build a modern Python web API to serve damage-classification models. Learn routing, Pydantic schemas, file uploads, ONNX inference, and ATC-20 placard mapping.
Quick links
Jump straight to the explorer, quiz, curriculum, or your progress dashboard.
Core concepts, in plain English
A modern Python framework for building web APIs. The server FastAPI runs is what the browser talks to when you upload an image.
A URL the server knows how to answer — e.g. GET /health returns server status, POST /classify accepts an image and returns a damage class.
A class that declares the exact shape of request and response data, so invalid input is rejected with a clear error before reaching your code.
A portable file format for trained models. Loading model.onnx is faster and requires no PyTorch on the server.
An official post-earthquake/disaster tag system. Engineers post GREEN (safe), YELLOW (restricted), or RED (unsafe) on a building.
A twin-branch neural net that learns to compare two inputs by pushing similar pairs together and dissimilar pairs apart in embedding space.
Vision Transformer — splits an image into patches and processes them with self-attention instead of convolution, excelling at global context.
FastAPI end-to-end pipeline
A quick visual of how the FastAPI app processes a satellite image from upload to ATC-20 placard.
- Duration
- 5 weeks
- Level
- Beginner
- Stack
- FastAPI · ONNX · Rasterio
- ↑↓Image UploadGeoTIFF or JPG/PNG
- ✓↓File ValidationMagic bytes + size
- ⧉↓PreprocessingBands, normalize, tensor
- ◆↓AI InferenceONNX Runtime forward
- %↓Damage ClassSoftmax + entropy
- ▣↓ATC-20 PlacardGREEN / YELLOW / RED
- ✎RecommendationsEngineer action