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mlnd_distracted_driver_detection

基于深度学习的驾驶员状态检测，不仅仅可以识别出疲劳驾驶，还能够识别出各种各样的状态

mlofandrew-ng

吴恩达机器学习课程的讲义，欢迎大家一起学习

mmdetection_impl

mmdetection_object_detection_demo

How to train an object detection model with mmdetection

mnn-applications

MNN applications by MNN, JNI exec, RK3399. Support tflite\tensorflow\caffe\onnx models.

mnn-lanenet

Lane detection model for mobile device via MNN project

mnn-yolov3

MNN demo of Strongeryolo, including channel pruning, android support...

mnn_example

alibaba MNN, mobilenet classifier, centerface detecter, ultraface detecter, pfld landmarker and zqlandmarker, mobilefacenet

mnn_facetrack

开源视频人脸跟踪算法,MNN基于mtcnn人脸检测+onet人脸跟踪,在i7-9700k的cpu检测速度可高达500fps

mnn_test

learn how to use mnn.

mobile-lpr

Mobile-LPR 是一个面向移动端的准商业级车牌识别库，以NCNN作为推理后端，使用DNN作为算法核心，支持多种车牌检测算法，支持车牌识别和车牌颜色识别。

mobile-yolov5-pruning-distillation

mobilev2-yolov5s剪枝、蒸馏，支持ncnn，tensorRT部署。ultra-light but better performence！

mobilenet-yolo

A caffe implementation of MobileNet-YOLO detection network

mobilenetv2-ssdlite

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

mobilenetv2-yolov3

MobileNetV2-YoloV3-Nano: 0.5BFlops 3MB HUAWEI P40: 6ms/img, YoloFace-500k:0.1Bflops 420KB:fire::fire::fire:

mobileunet-tensorflow

Lane segmentation model trained with tensorflow implementation MobileNetV2 based U-Net

moc-detector

Actions as Moving Points

model-compression

model compression based on pytorch (1、quantization: 16/8/4/2 bits(dorefa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、ternary/binary value(twn/bnn/xnor-net)；2、 pruning: normal、regular and group convolutional channel pruning；3、 group convolution structure；4、batch-normalization folding for quantization)

model-quantization

Collections of model quantization algorithms

modern-cpp-features

A cheatsheet of modern C++ language and library features.

monocameracalibrate

monocular_measure

vo

mot-ctracker

Code for ECCV 2020 paper (Spotlight) "Chained-Tracker: Chaining Paired Attentive Regression Results for End-to-End Joint Multiple-Object Detection and Tracking"

mot_annot

Annotation tools in Python for labeling multiple object tracking in a single camera and across multiple cameras

mot_kalman

C++ implementation of 2D single camera tracking based on Kalman filter

motpy

Library for tracking-by-detection multi object tracking implemented in python

moving-average-filter

The purpose is to calculate a weighted moving average filter with real time input

mtcnn_face_detection_and_tracking

An MTCNN based face detection and an optical-flow based tracking running in two threads.

muiltiple-object-tracking

Project-Using Background Subtraction Method, Kalman Filter and Hungary Algorithm.

multi-camera-person-re-identification

State-of-the-art model for person re-identification in Multi-camera Multi-Target Tracking. Benchmarked on Market-1501 and DukeMTMTC-reID datasets.