samples: use findFile() in "python"

samples/python/asift.py

@@ -116,11 +116,11 @@ if __name__ == '__main__':
     try:
         fn1, fn2 = args
     except:
-        fn1 = '../data/aero1.jpg'
-        fn2 = '../data/aero3.jpg'
+        fn1 = 'aero1.jpg'
+        fn2 = 'aero3.jpg'
 
-    img1 = cv.imread(fn1, 0)
-    img2 = cv.imread(fn2, 0)
+    img1 = cv.imread(cv.samples.findFile(fn1), cv.IMREAD_GRAYSCALE)
+    img2 = cv.imread(cv.samples.findFile(fn2), cv.IMREAD_GRAYSCALE)
     detector, matcher = init_feature(feature_name)
 
     if img1 is None:

samples/python/browse.py

@@ -32,7 +32,7 @@ if __name__ == '__main__':
     print()
 
     if len(sys.argv) > 1:
-        fn = sys.argv[1]
+        fn = cv.samples.findFile(sys.argv[1])
         print('loading %s ...' % fn)
         img = cv.imread(fn)
         if img is None:

samples/python/calibrate.py

@@ -53,7 +53,7 @@ if __name__ == '__main__':
 
     obj_points = []
     img_points = []
-    h, w = cv.imread(img_names[0], 0).shape[:2]  # TODO: use imquery call to retrieve results
+    h, w = cv.imread(img_names[0], cv.IMREAD_GRAYSCALE).shape[:2]  # TODO: use imquery call to retrieve results
 
     def processImage(fn):
         print('processing %s... ' % fn)

samples/python/camera_calibration_show_extrinsics.py

@@ -160,7 +160,7 @@ def draw_camera_boards(ax, camera_matrix, cam_width, cam_height, scale_focal,
 def main():
     parser = argparse.ArgumentParser(description='Plot camera calibration extrinsics.',
                                      formatter_class=argparse.ArgumentDefaultsHelpFormatter)
-    parser.add_argument('--calibration', type=str, default="../data/left_intrinsics.yml",
+    parser.add_argument('--calibration', type=str, default='left_intrinsics.yml',
                         help='YAML camera calibration file.')
     parser.add_argument('--cam_width', type=float, default=0.064/2,
                         help='Width/2 of the displayed camera.')
@@ -172,7 +172,7 @@ def main():
                         help='The calibration board is static and the camera is moving.')
     args = parser.parse_args()
 
-    fs = cv.FileStorage(args.calibration, cv.FILE_STORAGE_READ)
+    fs = cv.FileStorage(cv.samples.findFile(args.calibration), cv.FILE_STORAGE_READ)
     board_width = int(fs.getNode('board_width').real())
     board_height = int(fs.getNode('board_height').real())
     square_size = fs.getNode('square_size').real()

samples/python/coherence.py

@@ -51,9 +51,9 @@ if __name__ == '__main__':
     try:
         fn = sys.argv[1]
     except:
-        fn = '../data/baboon.jpg'
+        fn = 'baboon.jpg'
 
-    src = cv.imread(fn)
+    src = cv.imread(cv.samples.findFile(fn))
 
     def nothing(*argv):
         pass

samples/python/color_histogram.py

@@ -39,7 +39,7 @@ if __name__ == '__main__':
         fn = sys.argv[1]
     except:
         fn = 0
-    cam = video.create_capture(fn, fallback='synth:bg=../data/baboon.jpg:class=chess:noise=0.05')
+    cam = video.create_capture(fn, fallback='synth:bg=baboon.jpg:class=chess:noise=0.05')
 
     while True:
         flag, frame = cam.read()

samples/python/deconvolution.py

@@ -19,11 +19,11 @@ Usage:
     ESC   - exit
 
 Examples:
-  deconvolution.py --angle 135 --d 22  ../data/licenseplate_motion.jpg
+  deconvolution.py --angle 135 --d 22  licenseplate_motion.jpg
     (image source: http://www.topazlabs.com/infocus/_images/licenseplate_compare.jpg)
 
-  deconvolution.py --angle 86 --d 31  ../data/text_motion.jpg
-  deconvolution.py --circle --d 19  ../data/text_defocus.jpg
+  deconvolution.py --angle 86 --d 31  text_motion.jpg
+  deconvolution.py --circle --d 19  text_defocus.jpg
     (image source: compact digital photo camera, no artificial distortion)
 
 
@@ -73,11 +73,11 @@ if __name__ == '__main__':
     try:
         fn = args[0]
     except:
-        fn = '../data/licenseplate_motion.jpg'
+        fn = 'licenseplate_motion.jpg'
 
     win = 'deconvolution'
 
-    img = cv.imread(fn, 0)
+    img = cv.imread(cv.samples.findFile(fn), cv.IMREAD_GRAYSCALE)
     if img is None:
         print('Failed to load file:', fn)
         sys.exit(1)

samples/python/dft.py

@@ -38,8 +38,8 @@ def shift_dft(src, dst=None):
 
     h, w = src.shape[:2]
 
-    cx1 = cx2 = w/2
-    cy1 = cy2 = h/2
+    cx1 = cx2 = w // 2
+    cy1 = cy2 = h // 2
 
     # if the size is odd, then adjust the bottom/right quadrants
     if w % 2 != 0:
@@ -65,11 +65,13 @@ def shift_dft(src, dst=None):
 if __name__ == "__main__":
 
     if len(sys.argv) > 1:
-        im = cv.imread(sys.argv[1])
+        fname = sys.argv[1]
     else:
-        im = cv.imread('../data/baboon.jpg')
+        fname = 'baboon.jpg'
         print("usage : python dft.py <image_file>")
 
+    im = cv.imread(cv.samples.findFile(fname))
+
     # convert to grayscale
     im = cv.cvtColor(im, cv.COLOR_BGR2GRAY)
     h, w = im.shape[:2]

samples/python/digits.py

@@ -3,7 +3,7 @@
 '''
 SVM and KNearest digit recognition.
 
-Sample loads a dataset of handwritten digits from '../data/digits.png'.
+Sample loads a dataset of handwritten digits from 'digits.png'.
 Then it trains a SVM and KNearest classifiers on it and evaluates
 their accuracy.
 
@@ -42,7 +42,7 @@ from common import clock, mosaic
 
 SZ = 20 # size of each digit is SZ x SZ
 CLASS_N = 10
-DIGITS_FN = '../data/digits.png'
+DIGITS_FN = 'digits.png'
 
 def split2d(img, cell_size, flatten=True):
     h, w = img.shape[:2]
@@ -54,8 +54,9 @@ def split2d(img, cell_size, flatten=True):
     return cells
 
 def load_digits(fn):
+    fn = cv.samples.findFile(fn)
     print('loading "%s" ...' % fn)
-    digits_img = cv.imread(fn, 0)
+    digits_img = cv.imread(fn, cv.IMREAD_GRAYSCALE)
     digits = split2d(digits_img, (SZ, SZ))
     labels = np.repeat(np.arange(CLASS_N), len(digits)/CLASS_N)
     return digits, labels

samples/python/distrans.py

@@ -24,10 +24,11 @@ if __name__ == '__main__':
     try:
         fn = sys.argv[1]
     except:
-        fn = '../data/fruits.jpg'
+        fn = 'fruits.jpg'
     print(__doc__)
 
-    img = cv.imread(fn, 0)
+    fn = cv.samples.findFile(fn)
+    img = cv.imread(fn, cv.IMREAD_GRAYSCALE)
     if img is None:
         print('Failed to load fn:', fn)
         sys.exit(1)

samples/python/facedetect.py

@@ -40,8 +40,8 @@ if __name__ == '__main__':
     except:
         video_src = 0
     args = dict(args)
-    cascade_fn = args.get('--cascade', "../../data/haarcascades/haarcascade_frontalface_alt.xml")
-    nested_fn  = args.get('--nested-cascade', "../../data/haarcascades/haarcascade_eye.xml")
+    cascade_fn = args.get('--cascade', "data/haarcascades/haarcascade_frontalface_alt.xml")
+    nested_fn  = args.get('--nested-cascade', "data/haarcascades/haarcascade_eye.xml")
 
     cascade = cv.CascadeClassifier(cv.samples.findFile(cascade_fn))
     nested = cv.CascadeClassifier(cv.samples.findFile(nested_fn))

samples/python/find_obj.py

@@ -147,11 +147,11 @@ if __name__ == '__main__':
     try:
         fn1, fn2 = args
     except:
-        fn1 = '../data/box.png'
-        fn2 = '../data/box_in_scene.png'
+        fn1 = 'box.png'
+        fn2 = 'box_in_scene.png'
 
-    img1 = cv.imread(fn1, 0)
-    img2 = cv.imread(fn2, 0)
+    img1 = cv.imread(cv.samples.findFile(fn1), cv.IMREAD_GRAYSCALE)
+    img2 = cv.imread(cv.samples.findFile(fn2), cv.IMREAD_GRAYSCALE)
     detector, matcher = init_feature(feature_name)
 
     if img1 is None:

samples/python/floodfill.py

@@ -25,10 +25,10 @@ if __name__ == '__main__':
     try:
         fn = sys.argv[1]
     except:
-        fn = '../data/fruits.jpg'
+        fn = 'fruits.jpg'
     print(__doc__)
 
-    img = cv.imread(fn, True)
+    img = cv.imread(cv.samples.findFile(fn))
     if img is None:
         print('Failed to load image file:', fn)
         sys.exit(1)

samples/python/gabor_threads.py

@@ -55,9 +55,9 @@ if __name__ == '__main__':
     try:
         img_fn = sys.argv[1]
     except:
-        img_fn = '../data/baboon.jpg'
+        img_fn = 'baboon.jpg'
 
-    img = cv.imread(img_fn)
+    img = cv.imread(cv.samples.findFile(img_fn))
     if img is None:
         print('Failed to load image file:', img_fn)
         sys.exit(1)

samples/python/grabcut.py

@@ -107,11 +107,11 @@ if __name__ == '__main__':
     if len(sys.argv) == 2:
         filename = sys.argv[1] # for drawing purposes
     else:
-        print("No input image given, so loading default image, ../data/lena.jpg \n")
+        print("No input image given, so loading default image, lena.jpg \n")
         print("Correct Usage: python grabcut.py <filename> \n")
-        filename = '../data/lena.jpg'
+        filename = 'lena.jpg'
 
-    img = cv.imread(filename)
+    img = cv.imread(cv.samples.findFile(filename))
     img2 = img.copy()                               # a copy of original image
     mask = np.zeros(img.shape[:2],dtype = np.uint8) # mask initialized to PR_BG
     output = np.zeros(img.shape,np.uint8)           # output image to be shown

samples/python/hist.py

@@ -60,10 +60,10 @@ if __name__ == '__main__':
     if len(sys.argv)>1:
         fname = sys.argv[1]
     else :
-        fname = '../data/lena.jpg'
+        fname = 'lena.jpg'
         print("usage : python hist.py <image_file>")
 
-    im = cv.imread(fname)
+    im = cv.imread(cv.samples.findFile(fname))
 
     if im is None:
         print('Failed to load image file:', fname)

samples/python/houghcircles.py

@@ -5,7 +5,7 @@ This example illustrates how to use cv.HoughCircles() function.
 
 Usage:
     houghcircles.py [<image_name>]
-    image argument defaults to ../data/board.jpg
+    image argument defaults to board.jpg
 '''
 
 # Python 2/3 compatibility
@@ -21,9 +21,9 @@ if __name__ == '__main__':
     try:
         fn = sys.argv[1]
     except IndexError:
-        fn = "../data/board.jpg"
+        fn = 'board.jpg'
 
-    src = cv.imread(fn, 1)
+    src = cv.imread(cv.samples.findFile(fn))
     img = cv.cvtColor(src, cv.COLOR_BGR2GRAY)
     img = cv.medianBlur(img, 5)
     cimg = src.copy() # numpy function

samples/python/houghlines.py

@@ -5,7 +5,7 @@ This example illustrates how to use Hough Transform to find lines
 
 Usage:
     houghlines.py [<image_name>]
-    image argument defaults to ../data/pic1.png
+    image argument defaults to pic1.png
 '''
 
 # Python 2/3 compatibility
@@ -22,9 +22,9 @@ if __name__ == '__main__':
     try:
         fn = sys.argv[1]
     except IndexError:
-        fn = "../data/pic1.png"
+        fn = 'pic1.png'
 
-    src = cv.imread(fn)
+    src = cv.imread(cv.samples.findFile(fn))
     dst = cv.Canny(src, 50, 200)
     cdst = cv.cvtColor(dst, cv.COLOR_GRAY2BGR)
 

samples/python/inpaint.py

@@ -27,11 +27,11 @@ if __name__ == '__main__':
     try:
         fn = sys.argv[1]
     except:
-        fn = '../data/fruits.jpg'
+        fn = 'fruits.jpg'
 
     print(__doc__)
 
-    img = cv.imread(fn)
+    img = cv.imread(cv.samples.findFile(fn))
     if img is None:
         print('Failed to load image file:', fn)
         sys.exit(1)

samples/python/letter_recog.py

@@ -158,10 +158,12 @@ if __name__ == '__main__':
     args, dummy = getopt.getopt(sys.argv[1:], '', ['model=', 'data=', 'load=', 'save='])
     args = dict(args)
     args.setdefault('--model', 'svm')
-    args.setdefault('--data', '../data/letter-recognition.data')
+    args.setdefault('--data', 'letter-recognition.data')
 
-    print('loading data %s ...' % args['--data'])
-    samples, responses = load_base(args['--data'])
+    datafile = cv.samples.findFile(args['--data'])
+
+    print('loading data %s ...' % datafile)
+    samples, responses = load_base(datafile)
     Model = models[args['--model']]
     model = Model()
 

samples/python/logpolar.py

@@ -22,9 +22,9 @@ if __name__ == '__main__':
     try:
         fn = sys.argv[1]
     except IndexError:
-        fn = '../data/fruits.jpg'
+        fn = 'fruits.jpg'
 
-    img = cv.imread(fn)
+    img = cv.imread(cv.samples.findFile(fn))
     if img is None:
         print('Failed to load image file:', fn)
         sys.exit(1)

samples/python/morphology.py

@@ -31,9 +31,9 @@ if __name__ == '__main__':
     try:
         fn = sys.argv[1]
     except:
-        fn = '../data/baboon.jpg'
+        fn = 'baboon.jpg'
 
-    img = cv.imread(fn)
+    img = cv.imread(cv.samples.findFile(fn))
 
     if img is None:
         print('Failed to load image file:', fn)

samples/python/peopledetect.py

@@ -40,7 +40,7 @@ if __name__ == '__main__':
     hog = cv.HOGDescriptor()
     hog.setSVMDetector( cv.HOGDescriptor_getDefaultPeopleDetector() )
 
-    default = ['../data/basketball2.png '] if len(sys.argv[1:]) == 0 else []
+    default = [cv.samples.findFile('basketball2.png')] if len(sys.argv[1:]) == 0 else []
 
     for fn in it.chain(*map(glob, default + sys.argv[1:])):
         print(fn, ' - ',)

samples/python/stereo_match.py

@@ -35,8 +35,8 @@ def write_ply(fn, verts, colors):
 
 if __name__ == '__main__':
     print('loading images...')
-    imgL = cv.pyrDown( cv.imread('../data/aloeL.jpg') )  # downscale images for faster processing
-    imgR = cv.pyrDown( cv.imread('../data/aloeR.jpg') )
+    imgL = cv.pyrDown(cv.imread(cv.samples.findFile('aloeL.jpg')))  # downscale images for faster processing
+    imgR = cv.pyrDown(cv.imread(cv.samples.findFile('aloeR.jpg')))
 
     # disparity range is tuned for 'aloe' image pair
     window_size = 3

samples/python/texture_flow.py

@@ -21,9 +21,9 @@ if __name__ == '__main__':
     try:
         fn = sys.argv[1]
     except:
-        fn = '../data/starry_night.jpg'
+        fn = 'starry_night.jpg'
 
-    img = cv.imread(fn)
+    img = cv.imread(cv.samples.findFile(fn))
     if img is None:
         print('Failed to load image file:', fn)
         sys.exit(1)

samples/python/tst_scene_render.py

@@ -98,8 +98,8 @@ class TestSceneRender():
 
 if __name__ == '__main__':
 
-    backGr = cv.imread('../data/graf1.png')
-    fgr = cv.imread('../data/box.png')
+    backGr = cv.imread(cv.samples.findFile('graf1.png'))
+    fgr = cv.imread(cv.samples.findFile('box.png'))
 
     render = TestSceneRender(backGr, fgr)
 

samples/python/tutorial_code/Histograms_Matching/histogram_calculation/calcHist_Demo.py

@@ -6,10 +6,10 @@ import argparse
 
 ## [Load image]
 parser = argparse.ArgumentParser(description='Code for Histogram Calculation tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/lena.jpg')
+parser.add_argument('--input', help='Path to input image.', default='lena.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/Histograms_Matching/histogram_equalization/EqualizeHist_Demo.py

@@ -4,10 +4,10 @@ import argparse
 
 ## [Load image]
 parser = argparse.ArgumentParser(description='Code for Histogram Equalization tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/lena.jpg')
+parser.add_argument('--input', help='Path to input image.', default='lena.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/ImgTrans/Filter2D/filter2D.py

@@ -11,15 +11,15 @@ def main(argv):
     window_name = 'filter2D Demo'
 
     ## [load]
-    imageName = argv[0] if len(argv) > 0 else "../data/lena.jpg"
+    imageName = argv[0] if len(argv) > 0 else 'lena.jpg'
 
     # Loads an image
-    src = cv.imread(imageName, cv.IMREAD_COLOR)
+    src = cv.imread(cv.samples.findFile(imageName), cv.IMREAD_COLOR)
 
     # Check if image is loaded fine
     if src is None:
         print ('Error opening image!')
-        print ('Usage: filter2D.py [image_name -- default ../data/lena.jpg] \n')
+        print ('Usage: filter2D.py [image_name -- default lena.jpg] \n')
         return -1
     ## [load]
     ## [init_arguments]

samples/python/tutorial_code/ImgTrans/HoughCircle/hough_circle.py

@@ -5,11 +5,11 @@ import numpy as np
 
 def main(argv):
     ## [load]
-    default_file =  "../../../../data/smarties.png"
+    default_file = 'smarties.png'
     filename = argv[0] if len(argv) > 0 else default_file
 
     # Loads an image
-    src = cv.imread(filename, cv.IMREAD_COLOR)
+    src = cv.imread(cv.samples.findFile(filename), cv.IMREAD_COLOR)
 
     # Check if image is loaded fine
     if src is None:

samples/python/tutorial_code/ImgTrans/HoughLine/hough_lines.py

@@ -10,11 +10,11 @@ import numpy as np
 
 def main(argv):
     ## [load]
-    default_file =  "../../../../data/sudoku.png"
+    default_file = 'sudoku.png'
     filename = argv[0] if len(argv) > 0 else default_file
 
     # Loads an image
-    src = cv.imread(filename, cv.IMREAD_GRAYSCALE)
+    src = cv.imread(cv.samples.findFile(filename), cv.IMREAD_GRAYSCALE)
 
     # Check if image is loaded fine
     if src is None:

samples/python/tutorial_code/ImgTrans/LaPlace/laplace_demo.py

@@ -14,14 +14,14 @@ def main(argv):
     # [variables]
 
     # [load]
-    imageName = argv[0] if len(argv) > 0 else "../data/lena.jpg"
+    imageName = argv[0] if len(argv) > 0 else 'lena.jpg'
 
-    src = cv.imread(imageName, cv.IMREAD_COLOR) # Load an image
+    src = cv.imread(cv.samples.findFile(imageName), cv.IMREAD_COLOR) # Load an image
 
     # Check if image is loaded fine
     if src is None:
         print ('Error opening image')
-        print ('Program Arguments: [image_name -- default ../data/lena.jpg]')
+        print ('Program Arguments: [image_name -- default lena.jpg]')
         return -1
     # [load]
 

samples/python/tutorial_code/ImgTrans/MakeBorder/copy_make_border.py

@@ -14,15 +14,15 @@ def main(argv):
     window_name = "copyMakeBorder Demo"
     ## [variables]
     ## [load]
-    imageName = argv[0] if len(argv) > 0 else "../data/lena.jpg"
+    imageName = argv[0] if len(argv) > 0 else 'lena.jpg'
 
     # Loads an image
-    src = cv.imread(imageName, cv.IMREAD_COLOR)
+    src = cv.imread(cv.samples.findFile(imageName), cv.IMREAD_COLOR)
 
     # Check if image is loaded fine
     if src is None:
         print ('Error opening image!')
-        print ('Usage: copy_make_border.py [image_name -- default ../data/lena.jpg] \n')
+        print ('Usage: copy_make_border.py [image_name -- default lena.jpg] \n')
         return -1
     ## [load]
     # Brief how-to for this program

samples/python/tutorial_code/ImgTrans/canny_detector/CannyDetector_Demo.py

@@ -17,10 +17,10 @@ def CannyThreshold(val):
     cv.imshow(window_name, dst)
 
 parser = argparse.ArgumentParser(description='Code for Canny Edge Detector tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/fruits.jpg')
+parser.add_argument('--input', help='Path to input image.', default='fruits.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image: ', args.input)
     exit(0)

samples/python/tutorial_code/ImgTrans/distance_transformation/imageSegmentation.py

@@ -11,10 +11,10 @@ rng.seed(12345)
 parser = argparse.ArgumentParser(description='Code for Image Segmentation with Distance Transform and Watershed Algorithm.\
     Sample code showing how to segment overlapping objects using Laplacian filtering, \
     in addition to Watershed and Distance Transformation')
-parser.add_argument('--input', help='Path to input image.', default='../data/cards.png')
+parser.add_argument('--input', help='Path to input image.', default='cards.png')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py

@@ -32,11 +32,11 @@ def update_map(ind, map_x, map_y):
 ## [Update]
 
 parser = argparse.ArgumentParser(description='Code for Remapping tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/chicky_512.png')
+parser.add_argument('--input', help='Path to input image.', default='chicky_512.png')
 args = parser.parse_args()
 
 ## [Load]
-src = cv.imread(args.input, cv.IMREAD_COLOR)
+src = cv.imread(cv.samples.findFile(args.input), cv.IMREAD_COLOR)
 if src is None:
     print('Could not open or find the image: ', args.input)
     exit(0)

samples/python/tutorial_code/ImgTrans/warp_affine/Geometric_Transforms_Demo.py

@@ -5,10 +5,10 @@ import argparse
 
 ## [Load the image]
 parser = argparse.ArgumentParser(description='Code for Affine Transformations tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/lena.jpg')
+parser.add_argument('--input', help='Path to input image.', default='lena.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/ShapeDescriptors/bounding_rects_circles/generalContours_demo1.py

@@ -53,10 +53,10 @@ def thresh_callback(val):
 ## [setup]
 # Load source image
 parser = argparse.ArgumentParser(description='Code for Creating Bounding boxes and circles for contours tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/stuff.jpg')
+parser.add_argument('--input', help='Path to input image.', default='stuff.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/ShapeDescriptors/bounding_rotated_ellipses/generalContours_demo2.py

@@ -53,10 +53,10 @@ def thresh_callback(val):
 ## [setup]
 # Load source image
 parser = argparse.ArgumentParser(description='Code for Creating Bounding rotated boxes and ellipses for contours tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/stuff.jpg')
+parser.add_argument('--input', help='Path to input image.', default='stuff.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/ShapeDescriptors/find_contours/findContours_demo.py

@@ -26,10 +26,10 @@ def thresh_callback(val):
 
 # Load source image
 parser = argparse.ArgumentParser(description='Code for Finding contours in your image tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/HappyFish.jpg')
+parser.add_argument('--input', help='Path to input image.', default='HappyFish.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/ShapeDescriptors/hull/hull_demo.py

@@ -33,10 +33,10 @@ def thresh_callback(val):
 
 # Load source image
 parser = argparse.ArgumentParser(description='Code for Convex Hull tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/stuff.jpg')
+parser.add_argument('--input', help='Path to input image.', default='stuff.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/ShapeDescriptors/moments/moments_demo.py

@@ -54,10 +54,10 @@ def thresh_callback(val):
 ## [setup]
 # Load source image
 parser = argparse.ArgumentParser(description='Code for Image Moments tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/stuff.jpg')
+parser.add_argument('--input', help='Path to input image.', default='stuff.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/TrackingMotion/corner_subpixels/cornerSubPix_Demo.py

@@ -50,10 +50,10 @@ def goodFeaturesToTrack_Demo(val):
 
 # Load source image and convert it to gray
 parser = argparse.ArgumentParser(description='Code for Shi-Tomasi corner detector tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/pic3.png')
+parser.add_argument('--input', help='Path to input image.', default='pic3.png')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/TrackingMotion/generic_corner_detector/cornerDetector_Demo.py

@@ -35,10 +35,10 @@ def myShiTomasi_function(val):
 
 # Load source image and convert it to gray
 parser = argparse.ArgumentParser(description='Code for Creating your own corner detector tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/building.jpg')
+parser.add_argument('--input', help='Path to input image.', default='building.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/TrackingMotion/good_features_to_track/goodFeaturesToTrack_Demo.py

@@ -38,10 +38,10 @@ def goodFeaturesToTrack_Demo(val):
 
 # Load source image and convert it to gray
 parser = argparse.ArgumentParser(description='Code for Shi-Tomasi corner detector tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/pic3.png')
+parser.add_argument('--input', help='Path to input image.', default='pic3.png')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/TrackingMotion/harris_detector/cornerHarris_Demo.py

@@ -35,10 +35,10 @@ def cornerHarris_demo(val):
 
 # Load source image and convert it to gray
 parser = argparse.ArgumentParser(description='Code for Harris corner detector tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/building.jpg')
+parser.add_argument('--input', help='Path to input image.', default='building.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

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)

samples/python/tutorial_code/features2D/akaze_matching/AKAZE_match.py

@@ -6,18 +6,18 @@ from math import sqrt
 
 ## [load]
 parser = argparse.ArgumentParser(description='Code for AKAZE local features matching tutorial.')
-parser.add_argument('--input1', help='Path to input image 1.', default='../data/graf1.png')
-parser.add_argument('--input2', help='Path to input image 2.', default='../data/graf3.png')
-parser.add_argument('--homography', help='Path to the homography matrix.', default='../data/H1to3p.xml')
+parser.add_argument('--input1', help='Path to input image 1.', default='graf1.png')
+parser.add_argument('--input2', help='Path to input image 2.', default='graf3.png')
+parser.add_argument('--homography', help='Path to the homography matrix.', default='H1to3p.xml')
 args = parser.parse_args()
 
-img1 = cv.imread(args.input1, cv.IMREAD_GRAYSCALE)
-img2 = cv.imread(args.input2, cv.IMREAD_GRAYSCALE)
+img1 = cv.imread(cv.samples.findFile(args.input1), cv.IMREAD_GRAYSCALE)
+img2 = cv.imread(cv.samples.findFile(args.input2), cv.IMREAD_GRAYSCALE)
 if img1 is None or img2 is None:
     print('Could not open or find the images!')
     exit(0)
 
-fs = cv.FileStorage(args.homography, cv.FILE_STORAGE_READ)
+fs = cv.FileStorage(cv.samples.findFile(args.homography), cv.FILE_STORAGE_READ)
 homography = fs.getFirstTopLevelNode().mat()
 ## [load]
 

samples/python/tutorial_code/features2D/feature_description/SURF_matching_Demo.py

@@ -4,12 +4,12 @@ import numpy as np
 import argparse
 
 parser = argparse.ArgumentParser(description='Code for Feature Detection tutorial.')
-parser.add_argument('--input1', help='Path to input image 1.', default='../data/box.png')
-parser.add_argument('--input2', help='Path to input image 2.', default='../data/box_in_scene.png')
+parser.add_argument('--input1', help='Path to input image 1.', default='box.png')
+parser.add_argument('--input2', help='Path to input image 2.', default='box_in_scene.png')
 args = parser.parse_args()
 
-img1 = cv.imread(args.input1, cv.IMREAD_GRAYSCALE)
-img2 = cv.imread(args.input2, cv.IMREAD_GRAYSCALE)
+img1 = cv.imread(cv.samples.findFile(args.input1), cv.IMREAD_GRAYSCALE)
+img2 = cv.imread(cv.samples.findFile(args.input2), cv.IMREAD_GRAYSCALE)
 if img1 is None or img2 is None:
     print('Could not open or find the images!')
     exit(0)

samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py

@@ -4,10 +4,10 @@ import numpy as np
 import argparse
 
 parser = argparse.ArgumentParser(description='Code for Feature Detection tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/box.png')
+parser.add_argument('--input', help='Path to input image.', default='box.png')
 args = parser.parse_args()
 
-src = cv.imread(args.input, cv.IMREAD_GRAYSCALE)
+src = cv.imread(cv.samples.findFile(args.input), cv.IMREAD_GRAYSCALE)
 if src is None:
     print('Could not open or find the image:', args.input)
     exit(0)

samples/python/tutorial_code/features2D/feature_flann_matcher/SURF_FLANN_matching_Demo.py

@@ -4,12 +4,12 @@ import numpy as np
 import argparse
 
 parser = argparse.ArgumentParser(description='Code for Feature Matching with FLANN tutorial.')
-parser.add_argument('--input1', help='Path to input image 1.', default='../data/box.png')
-parser.add_argument('--input2', help='Path to input image 2.', default='../data/box_in_scene.png')
+parser.add_argument('--input1', help='Path to input image 1.', default='box.png')
+parser.add_argument('--input2', help='Path to input image 2.', default='box_in_scene.png')
 args = parser.parse_args()
 
-img1 = cv.imread(args.input1, cv.IMREAD_GRAYSCALE)
-img2 = cv.imread(args.input2, cv.IMREAD_GRAYSCALE)
+img1 = cv.imread(cv.samples.findFile(args.input1), cv.IMREAD_GRAYSCALE)
+img2 = cv.imread(cv.samples.findFile(args.input2), cv.IMREAD_GRAYSCALE)
 if img1 is None or img2 is None:
     print('Could not open or find the images!')
     exit(0)

samples/python/tutorial_code/features2D/feature_homography/SURF_FLANN_matching_homography_Demo.py

@@ -4,12 +4,12 @@ import numpy as np
 import argparse
 
 parser = argparse.ArgumentParser(description='Code for Feature Matching with FLANN tutorial.')
-parser.add_argument('--input1', help='Path to input image 1.', default='../data/box.png')
-parser.add_argument('--input2', help='Path to input image 2.', default='../data/box_in_scene.png')
+parser.add_argument('--input1', help='Path to input image 1.', default='box.png')
+parser.add_argument('--input2', help='Path to input image 2.', default='box_in_scene.png')
 args = parser.parse_args()
 
-img_object = cv.imread(args.input1, cv.IMREAD_GRAYSCALE)
-img_scene = cv.imread(args.input2, cv.IMREAD_GRAYSCALE)
+img_object = cv.imread(cv.samples.findFile(args.input1), cv.IMREAD_GRAYSCALE)
+img_scene = cv.imread(cv.samples.findFile(args.input2), cv.IMREAD_GRAYSCALE)
 if img_object is None or img_scene is None:
     print('Could not open or find the images!')
     exit(0)

samples/python/tutorial_code/highgui/trackbar/AddingImagesTrackbar.py

@@ -15,14 +15,14 @@ def on_trackbar(val):
 ## [on_trackbar]
 
 parser = argparse.ArgumentParser(description='Code for Adding a Trackbar to our applications tutorial.')
-parser.add_argument('--input1', help='Path to the first input image.', default='../data/LinuxLogo.jpg')
-parser.add_argument('--input2', help='Path to the second input image.', default='../data/WindowsLogo.jpg')
+parser.add_argument('--input1', help='Path to the first input image.', default='LinuxLogo.jpg')
+parser.add_argument('--input2', help='Path to the second input image.', default='WindowsLogo.jpg')
 args = parser.parse_args()
 
 ## [load]
 # Read images ( both have to be of the same size and type )
-src1 = cv.imread(args.input1)
-src2 = cv.imread(args.input2)
+src1 = cv.imread(cv.samples.findFile(args.input1))
+src2 = cv.imread(cv.samples.findFile(args.input2))
 ## [load]
 if src1 is None:
     print('Could not open or find the image: ', args.input1)

samples/python/tutorial_code/imgProc/Pyramids/pyramids.py

@@ -11,10 +11,10 @@ def main(argv):
     * [ESC] -> Close program
     """)
     ## [load]
-    filename = argv[0] if len(argv) > 0 else "../data/chicky_512.png"
+    filename = argv[0] if len(argv) > 0 else 'chicky_512.png'
 
     # Load the image
-    src = cv.imread(filename)
+    src = cv.imread(cv.samples.findFile(filename))
 
     # Check if image is loaded fine
     if src is None:

samples/python/tutorial_code/imgProc/Smoothing/smoothing.py

@@ -17,10 +17,10 @@ def main(argv):
     cv.namedWindow(window_name, cv.WINDOW_AUTOSIZE)
 
     # Load the source image
-    imageName = argv[0] if len(argv) > 0 else "../data/lena.jpg"
+    imageName = argv[0] if len(argv) > 0 else 'lena.jpg'
 
     global src
-    src = cv.imread(imageName, 1)
+    src = cv.imread(cv.samples.findFile(imageName))
     if src is None:
         print ('Error opening image')
         print ('Usage: smoothing.py [image_name -- default ../data/lena.jpg] \n')

samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/BasicLinearTransforms.py

@@ -7,10 +7,10 @@ import argparse
 # Read image given by user
 ## [basic-linear-transform-load]
 parser = argparse.ArgumentParser(description='Code for Changing the contrast and brightness of an image! tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/lena.jpg')
+parser.add_argument('--input', help='Path to input image.', default='lena.jpg')
 args = parser.parse_args()
 
-image = cv.imread(args.input)
+image = cv.imread(cv.samples.findFile(args.input))
 if image is None:
     print('Could not open or find the image: ', args.input)
     exit(0)

samples/python/tutorial_code/imgProc/changing_contrast_brightness_image/changing_contrast_brightness_image.py

@@ -44,10 +44,10 @@ def on_gamma_correction_trackbar(val):
     gammaCorrection()
 
 parser = argparse.ArgumentParser(description='Code for Changing the contrast and brightness of an image! tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/lena.jpg')
+parser.add_argument('--input', help='Path to input image.', default='lena.jpg')
 args = parser.parse_args()
 
-img_original = cv.imread(args.input)
+img_original = cv.imread(cv.samples.findFile(args.input))
 if img_original is None:
     print('Could not open or find the image: ', args.input)
     exit(0)

samples/python/tutorial_code/imgProc/erosion_dilatation/morphology_1.py

@@ -42,10 +42,10 @@ def dilatation(val):
     cv.imshow(title_dilatation_window, dilatation_dst)
 
 parser = argparse.ArgumentParser(description='Code for Eroding and Dilating tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/LinuxLogo.jpg')
+parser.add_argument('--input', help='Path to input image.', default='LinuxLogo.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image: ', args.input)
     exit(0)

samples/python/tutorial_code/imgProc/hough_line_transform/hough_line_transform.py

 import cv2 as cv
 import numpy as np
 
-img = cv.imread('../data/sudoku.png')
+img = cv.imread(cv.samples.findFile('sudoku.png'))
 gray = cv.cvtColor(img,cv.COLOR_BGR2GRAY)
 edges = cv.Canny(gray,50,150,apertureSize = 3)
 

samples/python/tutorial_code/imgProc/hough_line_transform/probabilistic_hough_line_transform.py

 import cv2 as cv
 import numpy as np
 
-img = cv.imread('../data/sudoku.png')
+img = cv.imread(cv.samples.findFile('sudoku.png'))
 gray = cv.cvtColor(img,cv.COLOR_BGR2GRAY)
 edges = cv.Canny(gray,50,150,apertureSize = 3)
 lines = cv.HoughLinesP(edges,1,np.pi/180,100,minLineLength=100,maxLineGap=10)

samples/python/tutorial_code/imgProc/opening_closing_hats/morphology_2.py

@@ -31,10 +31,10 @@ def morphology_operations(val):
     cv.imshow(title_window, dst)
 
 parser = argparse.ArgumentParser(description='Code for More Morphology Transformations tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/LinuxLogo.jpg')
+parser.add_argument('--input', help='Path to input image.', default='LinuxLogo.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image: ', args.input)
     exit(0)

samples/python/tutorial_code/imgProc/threshold/threshold.py

@@ -23,12 +23,12 @@ def Threshold_Demo(val):
 ## [Threshold_Demo]
 
 parser = argparse.ArgumentParser(description='Code for Basic Thresholding Operations tutorial.')
-parser.add_argument('--input', help='Path to input image.', default='../data/stuff.jpg')
+parser.add_argument('--input', help='Path to input image.', default='stuff.jpg')
 args = parser.parse_args()
 
 ## [load]
 # Load an image
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 if src is None:
     print('Could not open or find the image: ', args.input)
     exit(0)

samples/python/tutorial_code/ml/introduction_to_pca/introduction_to_pca.py

@@ -61,10 +61,10 @@ def getOrientation(pts, img):
 # Load image
 parser = argparse.ArgumentParser(description='Code for Introduction to Principal Component Analysis (PCA) tutorial.\
                                               This program demonstrates how to use OpenCV PCA to extract the orientation of an object.')
-parser.add_argument('--input', help='Path to input image.', default='../data/pca_test1.jpg')
+parser.add_argument('--input', help='Path to input image.', default='pca_test1.jpg')
 args = parser.parse_args()
 
-src = cv.imread(args.input)
+src = cv.imread(cv.samples.findFile(args.input))
 # Check if image is loaded successfully
 if src is None:
     print('Could not open or find the image: ', args.input)

samples/python/tutorial_code/objectDetection/cascade_classifier/objectDetection.py

@@ -23,8 +23,8 @@ def detectAndDisplay(frame):
     cv.imshow('Capture - Face detection', frame)
 
 parser = argparse.ArgumentParser(description='Code for Cascade Classifier tutorial.')
-parser.add_argument('--face_cascade', help='Path to face cascade.', default='../../data/haarcascades/haarcascade_frontalface_alt.xml')
-parser.add_argument('--eyes_cascade', help='Path to eyes cascade.', default='../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml')
+parser.add_argument('--face_cascade', help='Path to face cascade.', default='data/haarcascades/haarcascade_frontalface_alt.xml')
+parser.add_argument('--eyes_cascade', help='Path to eyes cascade.', default='data/haarcascades/haarcascade_eye_tree_eyeglasses.xml')
 parser.add_argument('--camera', help='Camera devide number.', type=int, default=0)
 args = parser.parse_args()
 
@@ -35,10 +35,10 @@ face_cascade = cv.CascadeClassifier()
 eyes_cascade = cv.CascadeClassifier()
 
 #-- 1. Load the cascades
-if not face_cascade.load(face_cascade_name):
+if not face_cascade.load(cv.samples.findFile(face_cascade_name)):
     print('--(!)Error loading face cascade')
     exit(0)
-if not eyes_cascade.load(eyes_cascade_name):
+if not eyes_cascade.load(cv.samples.findFile(eyes_cascade_name)):
     print('--(!)Error loading eyes cascade')
     exit(0)
 

samples/python/tutorial_code/video/background_subtraction/bg_sub.py

@@ -4,7 +4,7 @@ import argparse
 
 parser = argparse.ArgumentParser(description='This program shows how to use background subtraction methods provided by \
                                               OpenCV. You can process both videos and images.')
-parser.add_argument('--input', type=str, help='Path to a video or a sequence of image.', default='../data/vtest.avi')
+parser.add_argument('--input', type=str, help='Path to a video or a sequence of image.', default='vtest.avi')
 parser.add_argument('--algo', type=str, help='Background subtraction method (KNN, MOG2).', default='MOG2')
 args = parser.parse_args()
 
@@ -17,7 +17,7 @@ else:
 ## [create]
 
 ## [capture]
-capture = cv.VideoCapture(args.input)
+capture = cv.VideoCapture(cv.samples.findFileOrKeep(args.input))
 if not capture.isOpened:
     print('Unable to open: ' + args.input)
     exit(0)

samples/python/video.py

@@ -20,8 +20,8 @@ Usage:
      - synth:<params> for procedural video
 
 Synth examples:
-    synth:bg=../data/lena.jpg:noise=0.1
-    synth:class=chess:bg=../data/lena.jpg:noise=0.1:size=640x480
+    synth:bg=lena.jpg:noise=0.1
+    synth:class=chess:bg=lena.jpg:noise=0.1:size=640x480
 
 Keys:
     ESC    - exit
@@ -49,7 +49,7 @@ class VideoSynthBase(object):
         self.bg = None
         self.frame_size = (640, 480)
         if bg is not None:
-            self.bg = cv.imread(bg, 1)
+            self.bg = cv.imread(cv.samples.findFile(bg))
             h, w = self.bg.shape[:2]
             self.frame_size = (w, h)
 
@@ -85,8 +85,8 @@ class VideoSynthBase(object):
 class Book(VideoSynthBase):
     def __init__(self, **kw):
         super(Book, self).__init__(**kw)
-        backGr = cv.imread('../data/graf1.png')
-        fgr = cv.imread('../data/box.png')
+        backGr = cv.imread(cv.samples.findFile('graf1.png'))
+        fgr = cv.imread(cv.samples.findFile('box.png'))
         self.render = TestSceneRender(backGr, fgr, speed = 1)
 
     def read(self, dst=None):
@@ -98,7 +98,7 @@ class Book(VideoSynthBase):
 class Cube(VideoSynthBase):
     def __init__(self, **kw):
         super(Cube, self).__init__(**kw)
-        self.render = TestSceneRender(cv.imread('../data/pca_test1.jpg'), deformation = True,  speed = 1)
+        self.render = TestSceneRender(cv.imread(cv.samples.findFile('pca_test1.jpg')), deformation = True,  speed = 1)
 
     def read(self, dst=None):
         noise = np.zeros(self.render.sceneBg.shape, np.int8)
@@ -158,10 +158,10 @@ classes = dict(chess=Chess, book=Book, cube=Cube)
 
 presets = dict(
     empty = 'synth:',
-    lena = 'synth:bg=../data/lena.jpg:noise=0.1',
-    chess = 'synth:class=chess:bg=../data/lena.jpg:noise=0.1:size=640x480',
-    book = 'synth:class=book:bg=../data/graf1.png:noise=0.1:size=640x480',
-    cube = 'synth:class=cube:bg=../data/pca_test1.jpg:noise=0.0:size=640x480'
+    lena = 'synth:bg=lena.jpg:noise=0.1',
+    chess = 'synth:class=chess:bg=lena.jpg:noise=0.1:size=640x480',
+    book = 'synth:class=book:bg=graf1.png:noise=0.1:size=640x480',
+    cube = 'synth:class=cube:bg=pca_test1.jpg:noise=0.0:size=640x480'
 )
 
 

samples/python/watershed.py

@@ -80,6 +80,6 @@ if __name__ == '__main__':
     try:
         fn = sys.argv[1]
     except:
-        fn = '../data/fruits.jpg'
+        fn = 'fruits.jpg'
     print(__doc__)
-    App(fn).run()
+    App(cv.samples.findFile(fn)).run()