What is DetectionSuite?
DetectionSuite consists of a set of utilities oriented to simplify developing and testing solutions based on object detection.
DeepLearningSuite is a tool designed to experiment upon datasets and networks using various frameworks. Currently it has the following utilities:
- Auto Evaluator
Every tool in DeepLearningSuite requires a config file to run, and currently YAML file format is supported. See below on how to create a custom config file.
Each tool may have different requirements for keys in config file, and they can be known by passing the
Creating a custom
It is recommended to create and assign a dedicated directory for storing all datasets, weights and config files, for easier access and a cleaner
For Instance we will be using
/opt/datasets/ for demonstration purposes.
Create the following directories in
Again, these names are temporary and can be changed, but must also be changed in
cfg: This directory will store config files for various networks. For example, yolo-voc.cfg.
names: This directory will contain class names for various datasets. For example, voc.names.
weights: This directory will contain weights for various networks, such as yolo-voc.weights for yolo or a frozen inference graph for tensorflow trained networks.
eval: Evaluations path.
Once done, you can create your own custom appConfig.yml like the one mentioned.
datasetPath: /opt/datasets/ evaluationsPath: /opt/datasets/eval weightsPath: /opt/datasets/weights netCfgPath: /opt/datasets/cfg namesPath: /opt/datasets/names inferencesPath: /opt/datasets
Place your weights in weights directory, config files in cfg directory, classname files in names. And you are ready to go ⚡️ .