.
├── ...
├── config/                                # configuration file folder.
│   ├── etinynet_ssd_config.py             # The config file to read configuration of network from .yaml.
│   └── Config_etinynet_ssd.yaml           # The configuration parameters of the etinynet network
|   └── squeezenet_ssd_config.py           # The config file to read configuration of network from .yaml.
|   └── Config_squeezenet_ssd.yaml         # The configuration parameters of the squeezenet network
|
├── dataset/                               # dataset file folder.
|   ├── pascal_voc.py                      # dataloader file for images with annotation in pascal voc format
|
├── models/                                # Models file folder.
|   ├──nn/                                 # Backbone file folder + boxes loss function
|       ├── etinynet.py                    # The feature extractor based on EtinyNet architecture 
|       └── squeezenet.py                  # The feature extractor based on SqueezeNet architecture 
|       └── multibox_loss.py               # Object file to compute classification and regression loss
|   ├──ssd/                                # Backbone + SSD file folder
|       ├── ssd.py                         # The SSD object file 
|       └── Squeezenet_ssd.py              # The file to connect SqueezeNet feature extractor with extra-layers and headers,return SSD object
|       └── etinynet_ssd.py                # The file to connect etinynet feature extractor with extra-layers and headers,return SSD object
├── utils/                                 # Utilities file folder.
│   ├── box_utils.py                       # Functions and utilities related to localization boxes.
│   ├── common_tools.py                    # Common tools for evaluation such as mAP.
│   └── misc.py                            # file containig the function to save checkpoints and perform TF 
└── tain_ssd.py                            # file to perform the training
└── eval_ssd.py                            # file to perform evaluation on test data