choodly,github

vehicle-detection-and-tracking-using-yolov3-and-deep-sort

I have used YOLOv3 Algorithm for Vehicle Detection and Deep Sort Algorithm for Vehicle Tracking. After tracking the vehicles I have tried counting the number of vehicles in each lane. This will help us in real life implementations like Toll Booths(To cross check the collection) and Traffic Lanes Rules Monitoring(To check if heavy vehicles are following the proper lanes or not).

vehicle-re-id

Viewpoint-aware Attentive Multi-view Inference for Vehicle Re-identification

vehicle-reid-baseline

vehicle re-identification baseline for veri and vehicleID dataset

vehiclereid_baseline

This is a baseline framework for vehicle re-id on the VeRi dataset, implementated by PyTorch.

veri-wild

A Large-Scale Dataset for Vehicle Re-Identification in the Wild

veridataset

This is the project page for veri dataset which is a large scale image dataset for vehicle re-identification in urban traffic surveillance.

vfl-vehicle-re-id

Code of the VFL part proposed in the paper: Variational Representation Learning for Vehicle Re-Identification

vifb

Visible and Infrared Image Fusion Benchmark

vnl_monocular_depth_prediction

Monocular Depth Prediction

yolact

A simple, fully convolutional model for real-time instance segmentation.

yolact_cityscapes_550

Modified real-time instance segmentation network YOLACT for several object categories on CityScapes dataset

yolact_detectron2

Reimplement yolact with detectron2 framework.

yolact_fcos

YOLACT: Real-time Instance Segmentation on the FCOS detector (without bbox cropping), achives 35.2mAP on coco val

yolact_minimal

Minimal PyTorch implementation of YOLACT.

yolact_pytorch

:fire: :fire: :fire:Train Your Own DataSet for YOLACT and YOLACT++ Instance Segmentation Model!!!

yolo-multi-backbones-attention

Model Compression—YOLOv3 with multi lightweight backbones(ShuffleNetV2 HuaWei GhostNet), attention, prune and quantization

yolo-vortex-detection

Built a convolutional deep neural network to detect Vortices in a given 2D velocity field. The neural net outputs individual vortex's location, size and orientation using an an object detection algorithm called YOLO (You Only Look Once).

yolov3-calculate-anchor-boxes

This script performs K-means Clustering on the Berkeley Deep Drive dataset to find the appropriate anchor boxes for YOLOv3. Originally it has 9 anchor boxes and image size is 608x608. For any issues pleas let me know

yolov4-deepsort

Object tracking implemented with YOLOv4, DeepSort, and TensorFlow.

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