peyer

GHMLoss-caffe

GHMCLoss

hcl

alipay_autojs

最最最简单的蚂蚁森林自动收能量脚本

caffe

Caffe: a fast open framework for deep learning.

caffe-ssd-optimized

deeplearning.ai

Some work of Andrew Ng's course on Coursera

DeRPN

Dimension decomposition region proposal network -- a novel region proposal method for more general object detection.

Detectron

FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.

ESPNetv2

A light-weight, power efficient, and general purpose convolutional neural network

FaceBoxes

FaceBoxes: A CPU Real-time Face Detector with High Accuracy

Flow-Guided-Feature-Aggregation

Flow-Guided Feature Aggregation for Video Object Detection

gloo

Collective communications library with various primitives for multi-machine training.

KCF

High-Speed Tracking with Kernelized Correlation Filters

mace

Mobile AI Compute Engine

mayo

Mayo: Auto-generating hardware-friendly deep neural networks.

ML-KWS-for-MCU

Keyword spotting on Arm Cortex-M Microcontrollers

MobileNet-Caffe

Caffe Implementation of Google's MobileNets (v1 and v2)

MobileNet-SSD

Caffe implementation of Google MobileNet SSD detection network, with pretrained weights on VOC0712 and mAP=0.727.

MobileNetv2-SSDLite

Caffe implementation of SSD and SSDLite detection on MobileNetv2, converted from tensorflow.

MobilenetV2_tf_to_caffe

convert tensorflow mobilenet-v2 checkpoint to caffemodel

Pelee

Pelee: A Real-Time Object Detection System on Mobile Devices

pytorch-retinanet

Pytorch implementation of RetinaNet object detection.

qcom_hexagon_sdk

qcom_qnn

qcom qnn 2.13.0.230730

RCNN-Vehicle-Tracking-Lane-Detection

Vehicle Detection using Mask R-CNN and Computer Vision based Lane Detection

ResNet-18-Caffemodel-on-ImageNet

ResNet-18 Caffemodel @ilsvrc12 shrt 256 with Top-1 69% Top-5 89%

TensorRT-Prelu

TensorRT prelu and slice

TNN

TNN: developed by Tencent Youtu Lab and Guangying Lab, a lightweight and high-performance deep learning framework for mobile inference. TNN is distinguished by several outstanding features, including its cross-platform capability, high performance, model compression and code pruning. Based on ncnn and Rapidnet, TNN further strengthens the support and performance optimization for mobile devices, and also draws on the advantages of good extensibility and high performance from existed open source efforts. TNN has been deployed in multiple Apps from Tencent, such as Mobile QQ, Weishi, Pitu, etc. Contributions are welcome to work in collaborative with us and make TNN a better framework. TNN：由腾讯优图实验室和光影实验室协同打造，移动端高性能、轻量级推理框架，同时拥有跨平台、高性能、模型压缩、代码裁剪等众多突出优势。TNN框架在原有Rapidnet、ncnn框架的基础上进一步加强了移动端设备的支持以及性能优化，同时也借鉴了业界主流开源框架高性能和良好拓展性的优点。目前TNN已经在手Q、微视、P图等应用中落地，欢迎大家参与协同共建，促进TNN推理框架进一步完善。

UsefulLibs

set of some common hardware libraries

wide-residual-networks

3.8% and 18.3% on CIFAR-10 and CIFAR-100