Sensovision Systems has developed an instance segmentation model using the MASK R-CNN network architecture to predict traffic density from a camera. The model is trained on a small dataset of images of traffic density, and the output is the segmentation of vehicles in the image. This project will help in better traffic management and planning. Here’s an example of how you can use the model to predict traffic density:

1. Capture an image using a camera.

2. Feed the image to the model.

3. It can also segment the large vehicles, medium and small vehicles as 3 separate types.