SVIRO Object Detection

The code in this repository aims to build an ML solution for object detection, more specifically infant seat localization in the passenger seat of vehicles.

Dataset

The data set used in this work is available at: https://sviro.kl.dfki.de/.

It can be downloaded using the get_data.sh and the auxiliary files .txt that contain the image and bounding boxes links.

The data must be placed in a folder named data.

Solution

We used a Faster R-CNN with ResNet-50 and FPN as backbone. The dataset is artificially increased through Albumentations library.

Usage

• create an environment using the environment.yml file.
• Download the data and unzip it to a folder named data.
• run tools/train.py
• run tools/inference.py
  • optional: download our trained weights

We have tried to make the code as modular as possible. So that, one can modify to train.py and inference.py to, respectively, train and evaluate for other cars models, use different augmentations strategies and so on.

Checkout the notebooks!

Results

We trained the model for 50 epochs on using only the images from x5 car and evaluated this model on the test set of aclass car. Bellow are the COCO metrics:

 Average Precision  (AP) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.431
 Average Precision  (AP) @[ IoU=0.50      | area=   all | maxDets=100 ] = 0.647
 Average Precision  (AP) @[ IoU=0.75      | area=   all | maxDets=100 ] = 0.517
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000
 Average Precision  (AP) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000
 Average Precision  (AP) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.431
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=  1 ] = 0.464
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets= 10 ] = 0.638
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=   all | maxDets=100 ] = 0.638
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= small | maxDets=100 ] = -1.000
 Average Recall     (AR) @[ IoU=0.50:0.95 | area=medium | maxDets=100 ] = -1.000
 Average Recall     (AR) @[ IoU=0.50:0.95 | area= large | maxDets=100 ] = 0.638

References

• https://github.com/SteveCruz/sviro_helperfunctions
• https://github.com/alexhock/object-detection-metrics
• https://github.com/albumentations-team/albumentations/

TODO

• Train an object detection model
• Evaluate results
• Implement using config file