program to train and test the linear Support Vector Machine (SVM) classifier for pedestrian detection using the extracted features from part 1.

1. a)Train the SVM classifier with HOG features of the training set (use built-in function/library (e.g.from sklearn.svm import SVC)).
2. b)ClassifytheHOGfeaturesofthetestingimages(bothpositiveandnegativessamples) using the trained SVM model (use built-in function/library).
3. c)Compute the accuracy, false positive rate, and the miss rate.

DATASET IN LINK

https://drive.google.com/file/d/1oi3KhjcsUI1SOeeIFAx1jvVPWr0ZNNvQ/view?usp=sharing