This repository implements the research paper 'Image as an IMU: Estimating Camera Motion from a Single Motion-Blurred Image'. It provides code for training a neural network to estimate camera motion (rotation and translation) from a single motion-blurred image, using synthetic data generated from ScanNet++ and real-world fine-tuning data. The repository includes utilities for processing data from the StrayScanner iOS app, evaluating baselines (COLMAP, DROID-SLAM, MASt3R), and running real-time demos. The core contribution is a model that predicts optical flow, depth, and camera pose from a blurred image, then resolves motion direction ambiguity via photometric consistency checks.