Car-Detection

A HOG and SVM based object detection algorithm

Histogram of Oriented Gradient

Histogram of Oriented Gradient is a feature descriptor technique which generates features from images.

The features extracted is used for training in the SVM classifier. The classifier model generated is used for predicting whether a certain region contauns the object or not.

Files

• set_images.py : Transforms any number of images out of the total set in vehiclesand non-vehicles into grayscale and creates a dataset by storing in Pos_img and Neg_img respectively. The number of each set can be decided by the user.
• feature_extract.py : Uses the Histogram of Oriented Gradient Descriptor to create the features out of images.
• sliding_windows.py : Returns windows extracted from a given image to perform training/detection.
• training.py : This performs training of the classifier from the features obtained from feature_extract.py . The trained classifier is stored as a pickle file (model.pkl)
• result.py : This performs detection of cars in any given image of choice using the trained classifier (model.pkl)