tf2-yolo3

Introduction

A Tensorflow2.0 implementation of YOLOv3

Quick Start

1. Download yolov3.weights and darknet53.conv.74 from YOLO website.
2. Download COCO dataset
3. Modify the dataset root and weights root in the config file

python main_coco.py --resume load_yolov3 --do_test --net_size 608 --batch_size 8

Training

1. run the following command to start training

python main_voc.py/main_coco.py --resume load_darknet --net_size 480 --batch_size 8

2. The ckpt file will be stored in the ./checkpoints/dummy_name named with epoch number and use --resume xyz to resume from the xyz epoch

Visualization

The Tensorboard is origanized like TF-ObjectDection-API

Performance

Model	Initial weight	basic resolution	VOC2007 Test(mAP)
YoloV3	Darknet53	512	0.7796

Supported Attributes

• Data agumentation
• Multi-scale Training
• Multi-scale Testing(including flip)
• Focal loss
• ....

TODO

• Update VOC performance
• Update COCO performance
• Support distribute training
• Support Custom dataset

Reference

gluon-cv

tf-eager-yolo3

keras-yolo3

stronger-yolo