car-speed-detection 0.7.6

Speed detection library for automobile

Car-Speed-Detection

Car-Speed-Detection provides a python library to detect the speed of the driving car itself by the video stream from the dashboard camera installed on the car.

Car-Speed-Detection separates the speed detection process into three steps, preprocessing, training, and speed detection. By using Gunnar-Farneback optical flow algorithm along with the pipeline we developed, we are able to extract each frame into a small size matrix depends on developers preference. We use the Artifitial Neural Network (ANN) to train our model with the preprocessed matrix acquired from preprocessing function. Developers could use the trained model to detect the speed of the car at each frame using our speed detection function.

Getting Started

Installation

Car-Speed-Detection is available on PyPI and can be installed via pip. See car-speed-detection.readthedocs.io to learn about system dependencies and installation alternatives and recommendations.

pip install car-speed-detection

Read, Preprocess, Train, and Detect the Car Speed

The Car-Speed-Detection library consists of the following parts:

• Read (Read the mp4 video and output each frame into a designated directory)
• Preprocess (Preprocess each frame and output a feature set for training)
• Train (Train the model using the feature set and Artifitial Neural Network)
• Speed Detection (Detect the speed using the model and video)

Take a look at the API to know more about the Application Programming Interface and Sample for further information on how to use our library

Result

Acknowledge

Team Leader and Software Architecture: Shao-Chieh Lien

Research Paper Writer: Meenakshi Pavithran

Training Data Generator: Christopher Crocker