A minimal Tensorflow2.0 implementation of YOLOv2.
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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.
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
The proposed energy saving home or cabin automation system which could be used to detect the presence of a person inside the cabin and automatically adjust the state of electrical appliances to reduce power consumption. his is done by implementing the object detection YOLO algorithm on Raspberry Pi.
Tool used to generate anchor-boxes required for training YOLO networks
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.
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