import numpy as np

import cv2

import os

import pytest

import matplotlib.pyplot as plt

images_path = "./numpy/images"

def load_dataset(image_folder):

files = sorted(os.listdir(image_folder))

images = []

for f in files:

path = os.path.join(image_folder, f)

img = cv2.imread(path)

img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)

images.append(img)

images = np.stack(images, axis=0)

return images

def thresh(images, t=85):

if len(images.shape) < 3:

images = np.expand_dims(images, axis=0)

thresh_imgs = []

for i in range(images.shape[0]):

img = images[i]

ret, thresh_img = cv2.threshold(img, t, 255, cv2.THRESH_BINARY)

thresh_imgs.append(thresh_img)

thresh_imgs = np.stack(thresh_imgs, axis=0)

return thresh_imgs

def plot_image(img, img1, img2, xor_img, t1, t2):

f, ax = plt.subplots(2, 2)

ax[0, 0].imshow(img1, 'gray')

ax[0, 0].title.set_text("Binned Image 1. t1 = " + str(t1))

ax[0, 1].imshow(img2, 'gray')

ax[0, 1].title.set_text("Binned Image 2. t2 = " + str(t2))

ax[1, 0].imshow(img, 'gray')

ax[1, 0].title.set_text("Saturdated Image")

ax[1, 1].imshow(xor_img, 'gray')

ax[1, 1].title.set_text("XOR Image")

f.tight_layout()

plt.show()

@pytest.mark.parametrize("t1", [100, 150, 200, 250])

def bench_edge_detection(tacoBench, t1, plot):

images = load_dataset(images_path)

sat_images = images[:,:,:,1]

img = sat_images[0]

t2 = t1 - 50

bin_img1 = thresh(img, t1)

bin_img2 = thresh(img, t2)

num_elements = float(np.prod(bin_img1.shape))

def bench():

xor_img = np.logical_xor(bin_img1[0], bin_img2[0]).astype('int')

return xor_img

ret = tacoBench(bench)

xor_img = bench()

if plot:

plot_image(img, bin_img1[0], bin_img2[0], xor_img, t1, t2)

print("Sparsity img 1 ", np.sum(bin_img1 != 0) / num_elements)

print("Sparsity img 2 ", np.sum(bin_img2 != 0) / num_elements)

print("Sparsity xor ", np.sum(xor_img != 0) / num_elements)

if __name__=="__main__":

main()