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keras-image-classifer-framework

a general image classifer framework written by Keras

keras-maskrcnn

Keras implementation of MaskRCNN object detection.

keras-oneclassanomalydetection

[5 FPS - 150 FPS] Learning Deep Features for One-Class Classification (AnomalyDetection). Corresponds RaspberryPi3. Convert to Tensorflow, ONNX, Caffe, PyTorch. Implementation by Python + OpenVINO/Tensorflow Lite.

keras-recommendation

Using Keras to implement recommender systems

keras-retinanet

Keras implementation of RetinaNet object detection.

keras-semantic-segmentation

Keras-Semantic-Segmentation

keras-yolo3

A Keras implementation of YOLOv3 (Tensorflow backend)

keras-yolo3-1

Training and Detecting Objects with YOLO3

keras-yolov3-mobilenet

I transfer the backend of yolov3 into Mobilenetv1，VGG16，ResNet101 and ResNeXt101

keras_image_classifier

use keras to do image classification tasks

keras_ocr

用keras实现OCR定位、识别

keras_yolov3_mobilenet_tensorflow-serving

kgqa_hlm

基于知识图谱的《红楼梦》人物关系可视化及问答系统

label-studio

Label Studio is a multi-type data labeling and annotation tool with standardized output format

labelimgtool

LabelImgTool is a graphical image annotation tool which supports CLS,DET and SEG(semantic&instance )

labelme2datasets

用于将LabelMe标注好的数据转换为VOC格式和COCO格式的数据集。

lantern

Lantern官方版本下载 蓝灯 翻墙 代理 科学上网 外网 加速器 梯子 路由 lantern proxy vpn censorship-circumvention censorship gfw accelerator

lcqmc_data

lcqmc dataset three set datas train test dev

learn-nlp-with-transformers

we want to create a repo to illustrate usage of transformers in chinese

learn_dl

Deep learning algorithms source code for beginners

learning-notes

learnopencv

Learn OpenCV : C++ and Python Examples

leeml-notes

李宏毅《机器学习》笔记，在线阅读地址：https://datawhalechina.github.io/leeml-notes

lets_ocr

A repository for OCR, which inlcudes some classical OCR algorithms Pytorch implementation such as CTPN, EAST and CRNN.

lianjiaspider

链家爬虫

libface-detect-recognition

一种适合工业级应用的实时人脸检测与识别算法的C++实现

libtorch-yolov5

A LibTorch inference implementation of the yolov5

license-plate-detect-recognition-via-deep-neural-networks-accuracy-up-to-99.9

works in real-time with detection and recognition accuracy up to 99.8% for Chinese license plates: 100 ms/plate

license-plate-detector

基于Retinaface车牌检测,全新模型仅1.8MB.

lihang-code

《统计学习方法》的代码实现