tracker.py

import numpy as np


class Tracker:
    def __init__(self,
                 Mywindow_width,
                 Mywindow_height,
                 Mymargin,
                 My_ym=1,
                 My_xm=1,
                 Mysmooth_factor=15):
        self.recent_centers = []
        self.window_width = Mywindow_width
        self.window_height = Mywindow_height
        self.margin = Mymargin
        self.ym_per_pix = My_ym
        self.xm_per_pix = My_xm
        self.smoothing_factor = Mysmooth_factor

    def find_window_centroids(self, warped):
        window_width = self.window_width
        window_height = self.window_height
        margin = self.margin

        window_centroids = []
        window = np.ones(window_width)

        l_sum = np.sum(warped[int(3*warped.shape[0]/4):, :int(warped.shape[1]/2)], axis=0)
        l_center = np.argmax(np.convolve(window, l_sum))-window_width/2
        r_sum = np.sum(warped[int(3*warped.shape[0]/4):, int(warped.shape[1]/2):], axis=0)
        r_center = np.argmax(np.convolve(window, r_sum))-window_width/2+int(warped.shape[1]/2)

        window_centroids.append((l_center, r_center))

        for level in range(1, int(warped.shape[0]/window_height)):
            image_layer = np.sum(warped[int(warped.shape[0]-(level+1)*window_height): int(warped.shape[0]-level*window_height),:], axis=0)
            conv_signal = np.convolve(window, image_layer)

            offset = window_width / 2
            l_min_index = int(max(l_center+offset-margin, 0))
            l_max_index = int(min(l_center+offset+margin, warped.shape[1]))
            l_center = np.argmax(conv_signal[l_min_index:l_max_index])+l_min_index-offset

            r_min_index = int(max(r_center+offset-margin, 0))
            r_max_index = int(min(r_center+offset+margin, warped.shape[1]))
            r_center = np.argmax(conv_signal[r_min_index:r_max_index])+r_min_index-offset

            window_centroids.append((l_center, r_center))

        self.recent_centers.append(window_centroids)
        return np.average(self.recent_centers[-self.smoothing_factor:], axis=0)