A minimal Tensorflow2.0 implementation of YOLOv2.
-
Updated
Nov 28, 2020 - Python
A minimal Tensorflow2.0 implementation of YOLOv2.
Yolo-v2 based single object detection network. It can be further used to classify different objects by changing anchor boxes.
In this project, YOLOv2 and Detectron are used to track the distance between individuals in a video.
Java implementation of the K-means algorithm using IOU distance metric
Classify pictures by architectural style and recognize objects with CNNs and YOLO
A mobile application to aid visually impaired students to navigate the university of Ghana campus.
Yolo algorithm applied on a video file so as to detect cars, traffic lights and a few other classes.
This repo stores the draft and code used in the blog post
Tensorrt implementation for Yolo
A system of neural networks to detect and recognize faces. We use techniques developed in FaceNet and DeepFace for face recognition and create a simplified YOLO algorithm for face detection.
Use Producer + Consumer model and tensorflow do object detecion by YOLOv2 algorithm
A framework going to contain all detection methods, now Faster-RCNN and YOLOv2. It's convenient enough for your experiments.
This project uses transfer learning from a pre-trained Tiny Yolo V2 model to train a custom dataset which has 800 pictures contain rubik's cube. Darknet framework is used to training this model.
tf-keras-implemented YOLOv2
Add a description, image, and links to the yolov2 topic page so that developers can more easily learn about it.
To associate your repository with the yolov2 topic, visit your repo's landing page and select "manage topics."