Supercharging Object Detection in Videos: Setup

We started from the Python object detector performance as baseline (~ 19 fps). Next we ditch Python and all our pre-installed libraries and custom build everything. C++ will become the development environment not just because it's more "bare bones" than Python and thus more performant but also to access functionality not available in Python. Environment … Continue reading Supercharging Object Detection in Videos: Setup →

Supercharging Object Detection in Video: Optimizing Decoding and Graph Feeding

In the previous post we validated our install and ran a simple detector in C++. It is now time to start optimizing it. Source code for the finished project is here. Optimizing Video Decoding If we build and run the video_reader.cpp OpenCV sample, we will observe a staggering performance improvement available in OpenCV for decoding … Continue reading Supercharging Object Detection in Video: Optimizing Decoding and Graph Feeding →

Detecting Faces with Dlib from F#. IFSharp Notebook

The Choices I have experimented with OpenCV and Dlib face detection in my computer vision pipeline. Both work well, but the Dlib one worked better: it is more sensitive with (in my case) almost no false positives right out of the box! Dlib uses several HOG filters that account for profile as well as frontal … Continue reading Detecting Faces with Dlib from F#. IFSharp Notebook →

Capture Video in 2 Lines of Code

Literally. Well almost. 2 meaningful lines + some boilerplate. This has got to be easier than even Python! Using EmguCV, a wrapper around OpenCV and F# Interactive: