DEVLOG 3 — Training the First Gestures
Finally got everything working. I set up a data collection script that opens the webcam, lets a gesture label be selected, and then starts recording when space is pressed. From there, every frame grabs 63 normalized MediaPipe landmark values and saves them into a CSV row with the label attached. I collected about 300 samples per gesture, which sounds like a lot, but it’s actually pretty quick roughly 30–40 seconds per gesture since it just keeps recording while the sign is held, with natural movement built in. First quick test was super simple: yes/no, thumbs up vs thumbs down. Then I ran training and somehow hit 100% test accuracy by epoch 3, which honestly caught me off guard. The model itself is pretty small and just four dense layers (128 → 64 → 32 → output). But since the input is already structured landmark data instead of raw images, it picks up the patterns almost immediately.