test.py

import cv2
import visualizer
import color_histogram
import matplotlib.image as mpimg
import classifier

image = mpimg.imread('test_images/test4.jpg')
rescaled_image = visualizer.rescale(image)
gray = cv2.cvtColor(rescaled_image,cv2.COLOR_RGB2GRAY)
# bboxes = [((800, 400), (950, 510)), ((1040, 390), (1260, 510))]
# bbox_image = visualizer.draw_boxes(image,bboxes)
# visualizer.draw_image(image)

windows = classifier.slide_window(image, x_start_stop=(None, None), y_start_stop=(None, None),
                       xy_window=(128, 128), xy_overlap=(0.5, 0.5))

window_img = visualizer.draw_boxes(image, windows, color=(0, 0, 255), thick=6)
visualizer.draw_image(window_img)

# rh, gh, bh, bincen, feature_vec = color_histogram.color_hist(image, nbins=32, bins_range=(0, 256))
# visualizer.draw_histograms(rh, gh, bh, bincen)

# visualizer.draw_image(rescaled_image)

# print(len(color_histogram.bin_spatial(image)))

# Define HOG parameters
# orient = 9
# pix_per_cell = 8
# cell_per_block = 2
# features, hog_image = color_histogram.get_hog_features(gray, orient,
#                         pix_per_cell, cell_per_block,
#                         vis=True, feature_vec=False)
# visualizer.draw_image(hog_image)