DIGITS API documentation for object detection (using DetectNet) using Caffe

Hi all,

I’m looking for REST API documentation to train an object detection model using my own dataset (which has labels in KITTI data format) using DetectNet with Caffe framework. I looked into REST API documentation for classification and regression tasks in the following link -https://github.com/NVIDIA/DIGITS/blob/master/docs/API.md#regression

But, this link doesn’t have good explanation on how to use a custom object detection dataset (with labels in KITTI format) to train DetectNet model using Caffe. Essentially, I’m looking for an API call which I could use to create a training job on DIGITS for object detection and to obtain model file (snapshot_iter_xxx.caffemodel) after training is complete. Please point me in the right direction. Any help would be appreciated.


Since this is a pretty advanced use case, I encourage you to take a look at create_model classmethod in digits/model/images/generic/test_views.py. It shows how to construct the complete payload of POST method to /models/images/generic.