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test-script-to-generate-gt-sm.py
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test-script-to-generate-gt-sm.py
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import cv2
import matplotlib.pyplot as plt
import pySaliencyMap
from PIL import Image
import numpy as np
def generateSM(img_path):
# read
img = cv2.imread(img_path)
# initialize
imgsize = img.shape
img_width = imgsize[1]
img_height = imgsize[0]
sm = pySaliencyMap.pySaliencyMap(img_width, img_height)
# computation
saliency_map = sm.SMGetSM(img)
salient_region = sm.SMGetSalientRegion(img)
saliency_map *= 255.0/np.array(saliency_map).max()
return np.array(saliency_map).round()
# save it to the output folder
# '/sm/.."
# '/sm-regions/.."
if __name__=='__main__':
# list all the file names to generate saliency maps of
# loop through all the input files to generate saliency maps and save them to output folder
img_path = 'log-images/log_1698.labels0039.tif'
print(type(img_path))
img = cv2.imread(img_path)
sm_map = generateSM(img_path)
plt.imshow(sm_map,'gray')
plt.show()
cv2.imwrite("output/output1.jpg", np.array(sm_map))