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YOLO & RCNN Object Detection and Multi-Object Tracking

YOLO & RCNN Object Detection and Multi-Object Tracking

Object Detection and Tracking

Object detection is a computer technology related to computer vision and image processing that deals with detecting instances of semantic objects of a certain class (such as humans, buildings, or cars) in digital images and videos.
objectdetection

Environment

I have tested on Ubuntu 16.04/18.04. The code may work on other systems.
[Ubuntu-Deep-Learning-Environment-Setup]

  • Ubuntu 16.04 / 18.04
  • ROS Kinetic / Melodic
  • GTX 1080Ti / RTX 2080Ti
  • python 2.7 / 3.6

Installation

Clone the repository

git clone https://github.com/yehengchen/Object-Detection-and-Tracking.git

[OneStage]

YOLO: Real-Time Object Detection and Tracking

How to train a YOLOv3 model on custom images - [Link]


output_49


sort_1


Darknet_ROS: Real-Time Object Detection and Rotation Grasp Detection With ROS

output


output


chair_pin


SSD: Single Shot MultiBox Detector


[TwoStage]

R-CNN: Region-based methods

Fast R-CNN / Faster R-CNN / Mask R-CNN

How to train a Mask R-CNN model on own images - [Link]

mask_rcnn

This project is ROS package of Mask R-CNN algorithm for object detection and segmentation.


COCO & VOC Datasets


Paper list from 2014 to now(2019)

deep_learning_object_detection_history

GitHub

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