A Checklist for Training YOLOv3 for Our Own Dataset

Source: Deep Learning on Medium


a case study on object detection in image recognition

My last post “Exploring OpenCV’s Deep Learning Object Detection Library” had given a review on SSD/MobileNet and YOLOv2 under OpenCV 3.4.1 Deep Neural Network Module for object detection. It had also shown some examples detected by these two models. (ref: Figure 1 and Figure 2)

Figure 1.
Figure 2.

Because OpenCV 3.4.1 Deep Neural Network Module doesn’t support training on our own dataset, I am searching for other solutions which can support my future research on object detection. I have reviewed two implementations of YOLOv3 by Keras and Tensorflow on the Github:

Here is a brief on the pre-trained models and the training steps under the implementation of qqwweee.

Detection by the Pre-trained Model

Checklist for Training Your Dragon

(moving the scrollbar to check the full table)

What kind of object detection tasks I am working on? To be continued …

Acknowledgements: Thanks to the original work of YOLOv3 and the implementation by qqwweee.