nndl course proj
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from skimage.io import imread, imshow, imsave
from skimage.transform import resize
from skimage.feature import hog
from skimage import exposure
import matplotlib.pyplot as plt
import sys
import cv2
import numpy as np
import ntpath
def display_image(img):
plt.imshow(img)
plt.show()
def path_leaf(path):
head, tail = ntpath.split(path)
return tail or ntpath.basename(head)
if len(sys.argv) < 2:
print("no input image")
exit(1)
if len(sys.argv) < 3:
print("no output folder")
exit(1)
op_path = sys.argv[2]
img = imread(sys.argv[1], as_gray=True)
print(img.shape)
##resizing to 1:2 aspect ratio for easier calc
# resized_img = resize(img,(1024,512))
resized_img = img
print(resized_img.shape)
# display_image(resized_img)
# calc hog
fd, hog_img = hog(resized_img,
orientations=9,
pixels_per_cell=(2,2),
cells_per_block=(1,1),
visualize=True,
multichannel=False )
# display_image(hog_img)
hog_img = np.array(hog_img, dtype='uint8')
imsave( op_path + "/hog_of" + path_leaf(sys.argv[1]), hog_img)