def get_average_heatmap(self):
"""
get average heatmap from internal buffered heatmaps
"""
average_heatmap = np.average(self.heat_maps, axis=0)
average_heatmap = Helpers.apply_threshold(average_heatmap, PipelineParameters.AVG_HEAT_THRESHOLD)
return average_heatmap
def scan_all_cars(self, image, classifier, vis=False):
"""
scan the whole imag for cars
"""
small_car_start_y = 380
small_car_end_y = 540
small_car_bboxes = Pipeline.find_cars(image, classifier, small_car_start_y, small_car_end_y, 1.2)
middle_car_start_y = 380
middle_car_end_y = 580
middle_car_bboxes = Pipeline.find_cars(image, classifier, middle_car_start_y, middle_car_end_y, 1.8)
big_car_start_y = 380
big_car_end_y = 640
big_car_bboxes = Pipeline.find_cars(image, classifier, big_car_start_y, big_car_end_y, 2.4)
bboxes = small_car_bboxes + middle_car_bboxes + big_car_bboxes
heat = np.zeros_like(image[:, :, 0]).astype(np.float)
heat = Helpers.add_heat(heat, bboxes)
heat = Helpers.apply_threshold(heat, PipelineParameters.FRAME_HEAT_THRESHOLD)
heat = np.clip(heat, 0, 255)
self.add_heatmap(heat)
avg_heatmap = self.get_average_heatmap()
labels = label(avg_heatmap)
draw_img = Helpers.draw_labeled_bboxes(np.copy(image), labels)
if vis:
image = np.copy(image)
small = Helpers.draw_boxes(np.copy(image), small_car_bboxes, color=(0, 0, 1), thickness=3)
middle = Helpers.draw_boxes(np.copy(image), middle_car_bboxes, color=(0, 0, 1), thickness=3)
big = Helpers.draw_boxes(np.copy(image), big_car_bboxes, color=(0, 0, 1), thickness=3)
PlotHelper.three_color_images(small, 'scale=1.2', middle, 'scale=1.8', big, 'scale=2.4')
PlotHelper.two_images(draw_img, 'Car Positions', heat, 'Heat Map', left_cmap=None, right_cmap='hot')
return draw_img
