The Wayback Machine - https://web.archive.org/web/20200626113317/https://github.com/topics/dnn
Skip to content
#

dnn

Here are 552 public repositories matching this topic...

pranavsharma
pranavsharma commented Feb 27, 2020

Several parts of the op sec like the main op description, attributes, input and output descriptions become part of the binary that consumes ONNX e.g. onnxruntime causing an increase in its size due to strings that take no part in the execution of the model or its verification.

Setting __ONNX_NO_DOC_STRINGS doesn't really help here since (1) it's not used in the SetDoc(string) overload (s

hyousefGopher
hyousefGopher commented Mar 6, 2020

In the installation instructions for Windows at [GoCV][1] we've the below line:

Download and run the MinGW-W64 compiler installer from https://sourceforge.net/projects/mingw-w64/?source=typ_redirect.

I downloaded the mentioned file, but could not find executor file, and could not find anything like x86_64-7.3.0-posix-seh-rt_v5-rev2 as mentioned in the instuctions, any help?

pytorch-kaldi

pytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.

  • Updated Jun 11, 2020
  • Python
Dnn.Platform

Heterogeneous Run Time version of Caffe. Added heterogeneous capabilities to the Caffe, uses heterogeneous computing infrastructure framework to speed up Deep Learning on Arm-based heterogeneous embedded platform. It also retains all the features of the original Caffe architecture which users deploy their applications seamlessly.

  • Updated Oct 16, 2018
  • C++

Improve this page

Add a description, image, and links to the dnn topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the dnn topic, visit your repo's landing page and select "manage topics."

Learn more

You can’t perform that action at this time.