dexter2406's starred repositories
weixin_tuisong
基于猪咪不是猪老哥制作的微信公众号推送教程
drawio-desktop
Official electron build of draw.io
mono_velocity
A PyTorch implementation of the ICRA 2020 paper 'End-to-end Learning for Inter-Vehicle Distance and Relative Velocity Estimation in ADAS with a Monocular Camera'.
Mask_RCNN-TF2
Mask R-CNN matterport fork updated to support TF 2.0
Mask-RCNN-TF2
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
tensorflow-yolov4-tflite
YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
google-research
Google Research
monodepth2
Monocular depth estimation from a single image
TensorFlow2.0_ResNet
A ResNet(ResNet18, ResNet34, ResNet50, ResNet101, ResNet152) implementation using TensorFlow-2.0.
monodepth2
[ICCV 2019] Monocular depth estimation from a single image
Vehicle-Re-identification-on-VeRi-dataset
Modification of cosine_metric_learning from https://github.com/nwojke/cosine_metric_learning/issues
Keras-YOLOv4
yolov4 42.0% mAP.ppyolo 45.1% mAP.
tf-monodepth2
Tensorflow implementation(unofficial) of "Digging into Self-Supervised Monocular Depth Prediction"
Struct2Depth-Video
Get the depth from the frames of the live feed
awesome-cpp
A curated list of awesome C++ (or C) frameworks, libraries, resources, and shiny things. Inspired by awesome-... stuff.
ml-class-assignments
Programming Exercises on http://ml-class.org
Awesome-pytorch-list-CNVersion
Awesome-pytorch-list 翻译工作进行中......
keras-yolo3
A Keras implementation of YOLOv3 (Tensorflow backend)
ud120-projects
Starter project code for students taking Udacity ud120
pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
SfMLearner
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
SimCLRv1-keras-tensorflow
Tensorflow-Keras implementation of SimCLR: Simple Framework for Contrastive Learning of Visual Representations by Chen et al. (2020)
ImageNet-Datasets-Downloader
ImageNet dataset downloader. Creates a custom dataset by specifying the required number of classes and images in a class.