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sod - An Embedded Computer Vision & Machine Learning Library (CPU Optimized & IoT Capable)

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SOD is an embedded, modern cross-platform computer vision and machine learning software library that expose a set of APIs for deep-learning, advanced media analysis & processing including real-time, multi-class object detection and model training on embedded systems with limited computational resource and IoT devices. SOD was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in open source as well commercial products.

pico - Pixel Intensity Comparison-based Object detection

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The pico framework is a modifcation of the standard Viola-Jones method. The basic idea is to scan the image with a cascade of binary classifers at all reasonable positions and scales. An image region is classifed as an object of interest if it successfully passes all the members of the cascade. Each binary classifier consists of an ensemble of decision trees with pixel intensity comparisons as binary tests in their internal nodes. This enables the detector to process image regions at very high speed.

RPIMotionDetection - Blob detection library with example applications

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If you compile on the RPi: Please note that the compiling of the release version (-O3) requires a big amount of memory. If the compiling fails reduce the memory for the gpu at 64MB (config.txt) or enable swapping. If you compile on other systems: Add the cmake flag -DWITH_RPI=0 to disable the parts which requires RPi dependecies.

MutScan - Detect and visualize target mutations by scanning FastQ files directly

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-t argument specify how many worker threads will be launched. The default thread number is 4. Suggest to use a number less than the CPU cores of your system.








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