def process_frame(img):
car_boxes = find_cars(img, clf, scaler, parameter)
from heatmap import HeatMap
heatmap = HeatMap(threshold=3)
heatmap.add_heat(car_boxes)
heatmap.apply_threshold()
from scipy.ndimage.measurements import label
labels = label(heatmap.get_headmap())
label_box_img = draw_labeled_bboxes(np.copy(img), labels)
return label_box_img
test_images = list(
map(lambda img: read_image(img), glob.glob('./test_images/*.jpg')))
model_file = './data/model.p'
print('Loading classifier model from file', model_file)
clf, scaler = load_model(model_file)
parameter = FeatureParameter()
box_imgs = []
for img in test_images:
car_boxes = find_cars(img, clf, scaler, parameter)
car_boxes_img = draw_cars(img, car_boxes)
box_imgs.append(car_boxes_img)
from heatmap import HeatMap
heatmap = HeatMap(threshold=2)
heatmap.add_heat(car_boxes)
heatmap.apply_threshold()
heatmap_img = heatmap.get_headmap()
from scipy.ndimage.measurements import label
labels = label(heatmap_img)
box_imgs.append(heatmap_img)
label_box_img = draw_labeled_bboxes(np.copy(img), labels)
box_imgs.append(label_box_img)
plot_images(box_imgs)