Computer Vision2023
Real-Time Text Detection in Video with EasyOCR and OpenCV
A lightweight OCR pipeline that reads text frame by frame, draws it back onto the video and writes an annotated output file. Small project, direct answer to a common video analytics need.
- Stack
- EasyOCR · OpenCV · Python · NumPy
Context
Video analytics work often needs to read text off a frame: a plate, a panel label, a printed sign. The question was how far a lightweight OCR stack could go without a heavy detection model behind it.
Problem
Running OCR on video is not the same as running it on an image. Every frame is a new inference, output has to be drawn back onto the frame in the right position, and the whole thing has to keep up with playback while still producing a saved artefact someone can review afterwards.
Approach
The pipeline reads video frame by frame with OpenCV, passes each frame to EasyOCR, and maps detected text regions back to bounding boxes on the original frame. Annotated frames are written out to a new video file, so results are reviewable rather than just printed to a console.
Results
Real-time bounding box visualization of detected text on each frame
Frame-by-frame processing with annotated output written to a new video file
A reusable base for video analytics use cases that need text extraction
Notes
Built as a focused exercise in OCR integration for video rather than a production system. It remains the piece I reach for first when a new project needs to prove that text can be read reliably off a specific camera angle.
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