How can I train with my own dataset with darkflow?

Question

I'm a beginner with some programming experince. I'm trying to train darkflow with my own dataset. I'm following these instructions.

https://github.com/thtrieu/darkflow

So far I have done the following steps.

• installed darkflow and the relevant modules

• created test images and made annotations (Pascal VOC).

             https://ibb.co/y4HmtGz  
  
             https://ibb.co/GkxLshK
  

If I have understood correctly the darkflow training requires Pascal VOC?

My problem is that I don't know how to start the training. How can I start the training process and how can I test if the neuralnet is working? Am I supposed to get weights as a result of training?

Answer 1

You can choose to use pre-trained weights from here. Download cfg and weights.

Assuming you have darkflow installed, you can train your network like this:

flow --model cfg/<your-config-filename>.cfg --load bin/<filename>.weights --train --annotation train/Annotations --dataset train/Images --epoch 100 --gpu 1.0

If you want to train your network from scratch w/o using any pre-trained weights, you can do this:

flow --model cfg/<your-config-filename>.cfg --train --annotation train/Annotations --dataset train/Images --epoch 100 --gpu 1.0

After the training starts, model checkpoints are saved inside ckpt directory. You can load latest checkpoint and test on sample images.