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ios-cmake-1

A blank iOS app build system written in CMake. Includes building a dynamically linked C++ framework and bundling it into the app.

kcfcpp

C++ Implementation of KCF Tracker

kdmg_counting

Kernel-based Density Map Generation for Dense Object Counting

keras-cats-dogs-tutorial

A practical example of image classifier with Keras 2.x and TensorFlow backend, using the Kaggle Cats vs. Dogs dataset. By taking advantage of Keras' image data augmentation capabilities (and also random cropping), we were able to achieve 99% accuracy on the trained model with only 2,000 images in the training set.

kmeans-gmm-hmm

HMM based on KMeans and GMM

koin_benchmark_dataset

la3-label-aware-autoaugment

lcdpnet

Official PyTorch code and dataset of the paper "Local Color Distributions Prior for Image Enhancement" [ECCV2022]

learnopencv

Learn OpenCV : C++ and Python Examples

led

Learning Enhancement From Degradation: A Diffusion Model For Fundus Image Enhancement

lednet

[ECCV 2022] LEDNet: Joint Low-light Enhancement and Deblurring in the Dark

libfacedetection

A fast binary library for face detection and face landmark detection in images. The face detection speed can reach 1500FPS. You can use it free of charge with any purpose.

lighting-the-darkness-in-the-deep-learning-era-open

lightlayers

lightnet

LightNet: Light-weight Networks for Semantic Image Segmentation (Cityscapes and Mapillary Vistas Dataset)

lightnetplusplus

LightNet++: Boosted Light-weighted Networks for Real-time Semantic Segmentation

lightning

Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems).

lip2speech

A pipeline to read lips and generate speech for the read content, i.e Lip to Speech Synthesis.

local-crowd-counting

Adaptive Mixture Regression Network with Local Counting Map for Crowd Counting (ECCV2020)

lowdino

mace

MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.

machinelearning

A python project for the recognition of text in natural images, based on the Pylearn2 framework. The classifier is a CNN with Dropout. The dataset is the MJSynth dataset: http://www.robots.ox.ac.uk/~vgg/data/text/

manutdzou.github.io

mapready

mediapipe

Cross-platform, customizable ML solutions for live and streaming media.

miccai2022-heatmap-lesion-detection

Implementation for Heatmap Regression for Lesion Detection using Pointwise Annotations

micronet

mini-caffe

Minimal runtime core of Caffe, Forward Only and GPU support.

ml-sota

tracking state of the art in machine learning

mmdetection

OpenMMLab Detection Toolbox and Benchmark