yolo1_tensorflow

Simple implementation of yolo v1 and yolo v2 by TensorFlow

Introduction

Paper yolo v1: You Only Look Once: Unified, Real-Time Object Detection

Paper yolo v2: YOLO9000: Better, Faster, Stronger

The code of yolo v2, we use 9 anchors which is calculated by k-means on COCO dataset.

What is normalized offset?

Requirements

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1. python3.5
2. tensorflow1.4.0
3. pillow
4. numpy
5. scipy

Pretrained VGG16: Google Drive: https://drive.google.com/open?id=1LTptCY96ABAUlJHUJq6MhqNrDQN7JfQP

Dataset: Pascal voc 2007: https://pjreddie.com/media/files/VOCtrainval_06-Nov-2007.tar

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Results

Reference

[1]. Redmon, Joseph, et al. "You only look once: Unified, real-time object detection." Proceedings of the IEEE conference on computer vision and pattern recognition. 2016.

[2]. Redmon J, Farhadi A. YOLO9000: better, faster, stronger[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2017: 7263-7271.