Computer Vision Using Go And OpenCV 3
summary
Shows the GoCV package calling OpenCV 3 via cgo to run real code: webcam hello‑world, face blurring via a cascade classifier, motion detection with MOG2 plus contour area thresholds, and MJPEG web streaming. Demonstrates cross‑platform Go performance and portability, how images are Mats, and how frames are encoded. Ends with object classification and tracking on a TensorFlow-enabled drone — neural inference on the edge works but wireless interference makes the flight demo flaky though it lands successfully.
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chapters (14)
- 0:00Start
- 2:53What Is Computer Vision
- 3:39Augmented Humans
- 4:24Why You Should Use Go for Computer Vision
- 4:56How Go Cv Works
- 6:19Hello World of Video
- 10:37Real-World Applications Using Go Cv
- 10:56Phase Tracking
- 11:27Cascade Classifier
- 16:59Motion Detection and Tracking
- 21:54Web Video Streaming
- 27:06Object Classification / Tracking with a Deep Neural Network and a Drone
- 29:37Deep Neural Network
- 35:16Humanity Is Acquiring All the Right Technology for All the Wrong Reasons
