kann VS ZLib

TensorFlow has C APIs. I developed KANN from scratch for deep learning. It supports CNN, LSTM and complex topologies. For simple MLPs, you can implement your own as a practice. Use a BLAS library for performance.

After some research, I have reached the conclusion that I should use Faster R-CNN. So far, I have completed a classification task with a basic CNN using the C Kann library, as it can create basic layers and has basic functionalities..

I'm trying to use the kann library to create a model that classifies color images using a CNN, following the mnist cnn example.

KANN - Two-file ANN library. MIT

A fix has been checked into the upstream git repo: https://github.com/madler/zlib/pull/843 but a release has not yet been made including it.

So the real issue here is that the lack of tree validation before the tree construction, I believe. I'm surprised that this check was not yet implemented (I actually checked libwebp to make sure that I was missing one). Given this blind spot, an automated test based on the domain knowledge is likely useless to catch this bug.

[1] https://github.com/madler/zlib/blob/master/examples/enough.c

In the source code of the Node.js opensource project, lib folder contains JavaScript code, mostly wrappers over C++ and function definitions. On the contrary, src folder contains C++ implementations of the functions, which pulls dependencies from the V8 project, the libuv project, the zlib project, the llhttp project, and many more - which are all placed at the deps folder.

Seeing the text in red got me thinking for a moment, "wow, didn't realize pirates had such love for an open-source compression library"

cd "${srcdir}/zlib-$pkgver/contrib/minizip" make install DESTDIR="${pkgdir}" install -D -m644 "${srcdir}/zlib-$pkgver/LICENSE" "${pkgdir}/usr/share/licenses/minizip/LICENSE" # https://github.com/madler/zlib/pull/229 rm "${pkgdir}/usr/include/minizip/crypt.h"