gittongzhen/detectionstudio

Tool to evaluate deep-learning detection and segmentation models, and to create datasets

Detection Studio

More info and documentation here.

Detection Studio is a set of tools to evaluate object detection neural networks models over the common object detection datasets. The tools can be accessed using the GUI or the command line applications. In the picture below, the general architecture is displayed.

The tools provided are:

• Viewer: view the dataset images with the annotations.
• Detector: run a model over a dataset and get generate a new annotated dataset.
• Evaluator: evaluate the ground truth dataset with another one and get the comparison metrics.
• Deployer: run a model over different inputs like a video or webcam and generate a new annotated dataset.
• Converter: convert a dataset into another dataset format.
• Command line application (CLI): access Detection Studio toolset through command line
• Detection Studio as ROS Node: use Detection Studio as a ROS Node.

• Labelling: add or modify labels in the datasets in runtime when running Deployer.

The idea is to offer a generic infrastructure to evaluate object detection models against a dataset and compute the common statistics:

• mAP
• mAR
• Mean inference time.

What's supported in Detection Studio.

Support	Detail
Supported OS	Linux, MacOS
Supported datasets	COCO, ImageNet, Pascal VOC, Jderobot recorder logs, Princeton RGB dataset, Spinello dataset
Supported frameworks	TensorFlow, Keras, PyTorch, Yolo-OpenCV, Caffe, Background substraction
Supported inputs in Deployer	WebCamera/USB Camera, Videos, Streams from ROS, Streams from ICE, JdeRobot Recorder Logs

Installation

Check the installation guide here.

Starting with Detection Studio

Check out the beginner's tutorial.

General Detection Studio GUI

The top toolbar shows the different tools available.

Example of detection and console output in Detection Studio

Two image views are displayed, one with the ground truth and the other with the detected annotations. In the console output, log info is shown.