samples: use findFile() in "python"

samples/python/tutorial_code/core/AddingImages/adding_images.py

@@ -16,8 +16,8 @@ input_alpha = float(raw_input().strip())
 if 0 <= alpha <= 1:
     alpha = input_alpha
 # [load]
-src1 = cv.imread('../../../../data/LinuxLogo.jpg')
-src2 = cv.imread('../../../../data/WindowsLogo.jpg')
+src1 = cv.imread(cv.samples.findFile('LinuxLogo.jpg'))
+src2 = cv.imread(cv.samples.findFile('WindowsLogo.jpg'))
 # [load]
 if src1 is None:
     print("Error loading src1")

samples/python/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.py

@@ -10,16 +10,16 @@ def print_help():
     This program demonstrated the use of the discrete Fourier transform (DFT).
     The dft of an image is taken and it's power spectrum is displayed.
     Usage:
-    discrete_fourier_transform.py [image_name -- default ../../../../data/lena.jpg]''')
+    discrete_fourier_transform.py [image_name -- default lena.jpg]''')
 
 
 def main(argv):
 
     print_help()
 
-    filename = argv[0] if len(argv) > 0 else "../../../../data/lena.jpg"
+    filename = argv[0] if len(argv) > 0 else 'lena.jpg'
 
-    I = cv.imread(filename, cv.IMREAD_GRAYSCALE)
+    I = cv.imread(cv.samples.findFile(filename), cv.IMREAD_GRAYSCALE)
     if I is None:
         print('Error opening image')
         return -1

samples/python/tutorial_code/core/mat_mask_operations/mat_mask_operations.py

@@ -45,7 +45,7 @@ def sharpen(my_image):
 ## [basic_method]
 
 def main(argv):
-    filename = "../../../../data/lena.jpg"
+    filename = 'lena.jpg'
 
     img_codec = cv.IMREAD_COLOR
     if argv:
@@ -53,12 +53,12 @@ def main(argv):
         if len(argv) >= 2 and sys.argv[2] == "G":
             img_codec = cv.IMREAD_GRAYSCALE
 
-    src = cv.imread(filename, img_codec)
+    src = cv.imread(cv.samples.findFile(filename), img_codec)
 
     if src is None:
         print("Can't open image [" + filename + "]")
         print("Usage:")
-        print("mat_mask_operations.py [image_path -- default ../../../../data/lena.jpg] [G -- grayscale]")
+        print("mat_mask_operations.py [image_path -- default lena.jpg] [G -- grayscale]")
         return -1
 
     cv.namedWindow("Input", cv.WINDOW_AUTOSIZE)