def vehicle_detect_data_summary():
clf = classifier.Classifier()
clf.summarize_dataset()
cars, not_cars = clf._get_dataset()
single_car, single_not_car = image.load_img(
random.choice(cars)), image.load_img(random.choice(not_cars))
plotter.Plotter(True).plot_images(single_car, single_not_car)
def vehicle_detect_hog_sample():
clf = classifier.Classifier()
cars, not_cars = clf._get_dataset()
single_car = image.convert_color(image.load_img(random.choice(cars)),
features.COLOR_SPACE)
_, single_car_hog = features.hog_features_by_channel(single_car,
0,
visualise=True)
plotter.Plotter(True).plot_images(single_car, single_car_hog)
single_not_car = image.convert_color(
image.load_img(random.choice(not_cars)), features.COLOR_SPACE)
_, single_not_car_hog = features.hog_features_by_channel(single_not_car,
0,
visualise=True)
plotter.Plotter(True).plot_images(single_not_car, single_not_car_hog)
def vehicle_detect_single_image(img_path=None):
if not img_path:
img_path = 'test_images/test1.jpg'
init_logging()
clf = classifier.Classifier()
clf.from_pickle(VEHICLE_DETECTION_CLASSIFIER_PATH)
detect = detector.Detector(clf)
img = image.load_img(img_path)
calibrator = camera_calibration.CameraCalibration(get_plotter())
calibrator.config()
undisorted = calibrator.undistort(img)
output = detect.identify_vehicles(undisorted)
plotter.Plotter(True).plot_images(output)
#!/usr/bin/env python3
import logging as log
import os
from clize import run
import cv2
from moviepy.editor import VideoFileClip
from lane_finder import camera_calibration, plotter, lane_finder
PLOT = plotter.Plotter(False)
INIT = False
CAMERA_CALIBRATION_PICKLE_PATH = 'camera_calibration.P'
def init_logging():
log.basicConfig(
format='%(asctime)s %(message)s',
level=log.INFO)
def get_plotter(show_plots=False):
PLOT.show_plots = show_plots
return PLOT
def test_calibrate_camera():
init_logging()
plot = get_plotter()
calibrator = camera_calibration.CameraCalibration(plot)
calibrator.config()