tf-yolo

Introduction

an implementation of yolov3 with tensorflow-2.2, which uses tf.data api on tfrecords to feed data. Which makes training faster through data parallelism

Custom training

• convert data in pascal-voc xml format to tfrecords using tfrecord_creator.py. This will create a folder DATA and store the tfrecords in 4 shards there.
• customize main.py according to your dataset and start training

Prediction

• customize demo.py to predict on a new image

TO DO

• Provide a cli for training
• Predict on multiple images
• Add tensorboard summary
• Implement Tiny-YOLO

Reference

• Redmon, J. and Farhadi, A., 2018. Yolov3: An incremental improvement. arXiv 2018. arXiv preprint arXiv:1804.02767, pp.1-6.
• codes from qqwweee's repo were re used