ChasingTrainFramework_GeneralOneClassDetection

ChasingTrainFramework_GeneralSingleClassDetection

ChasingTrainFramework_GeneralSingleClassDetection is a simple wrapper based on MXNet Module API for general one class detection. Chasing is just a project code.

Framework Introduction

• data_iterator_base provide some utils for batch iterator. The design of a data iterator relies on the specific task. So we do not provide a default iterator here.

• data_provider_base reformat, pack raw data. In most cases, we can load all data into the memory for fast access.

• image_augmentation provide some often used augmentations.

• inference_speed_eval provide two ways for inference speed evaluation -- MXNet with CUDNN and TensorRT with CUDNN.

• loss_layer_farm provide customized loss type like hard negative mining, focal loss.

• logging_GOCD is a logging wrapper.

• solver_GOCD execute training process.

• train_GOCD is the entrance of the framework.