Single Shot MultiBox Detector (SSD)

A TinyDNN implementation of Single Shot MultiBox Detector from the 2016 paper by Wei Liu, Dragomir Anguelov, Dumitru Erhan, Christian Szegedy, Scott Reed, Cheng-Yang, and Alexander C. Berg. The official and original Caffe code can be found here.

Prerequisites for this example

Download PyTorch pretrained models from here
Convert PyTorch models to TinyDNN with following commands

mkdir models
python convert_models.py /path/to/model models

Use SSD in Object Detection

./example_ssd_test /folder/to/models/ /path/to/image

You will get output similar to following:

Bounding box coordinates:
x_min = 19.6578, x_max = 66.2639, y_min = 240.801, y_max = 270.333, class = 1, score = 0.989524
x_min = -3.73388, x_max = 302.883, y_min = 43.5821, y_max = 202.043, class = 1, score = 0.900133
x_min = 17.771, x_max = 54.9812, y_min = 237.505, y_max = 259.987, class = 1, score = 0.660543

If you see the following message:

Failed to load weights from models/01.weights
Failed to load weights from models/02.weights
...
Failed to load weights from models/18.weights

Please make sure the path of weight files.

Detection Results

Here's an example of object detection results produced by SSD.