Fixed shebangs, added error checking

samples/python2/_coverage.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Utility for measuring python opencv API coverage by samples.

samples/python2/_doc.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Scans current directory for *.py files and reports

samples/python2/asift.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Affine invariant feature-based image matching sample.
@@ -21,9 +21,12 @@ USAGE
 
 import numpy as np
 import cv2
+
+# built-in modules
 import itertools as it
 from multiprocessing.pool import ThreadPool
 
+# local modules
 from common import Timer
 from find_obj import init_feature, filter_matches, explore_match
 
@@ -85,15 +88,18 @@ def affine_detect(detector, img, mask=None, pool=None):
         if descrs is None:
             descrs = []
         return keypoints, descrs
+
     keypoints, descrs = [], []
     if pool is None:
         ires = it.imap(f, params)
     else:
         ires = pool.imap(f, params)
+
     for i, (k, d) in enumerate(ires):
         print 'affine sampling: %d / %d\r' % (i+1, len(params)),
         keypoints.extend(k)
         descrs.extend(d)
+
     print
     return keypoints, np.array(descrs)
 
@@ -104,7 +110,8 @@ if __name__ == '__main__':
     opts, args = getopt.getopt(sys.argv[1:], '', ['feature='])
     opts = dict(opts)
     feature_name = opts.get('--feature', 'sift-flann')
-    try: fn1, fn2 = args
+    try:
+        fn1, fn2 = args
     except:
         fn1 = 'data/aero1.jpg'
         fn2 = 'data/aero3.jpg'
@@ -112,11 +119,20 @@ if __name__ == '__main__':
     img1 = cv2.imread(fn1, 0)
     img2 = cv2.imread(fn2, 0)
     detector, matcher = init_feature(feature_name)
-    if detector != None:
-        print 'using', feature_name
-    else:
+    
+    if img1 is None:
+        print 'Failed to load fn1:', fn1
+        sys.exit(1)
+        
+    if img2 is None:
+        print 'Failed to load fn2:', fn2
+        sys.exit(1)
+    
+    if detector is None:
         print 'unknown feature:', feature_name
         sys.exit(1)
+        
+    print 'using', feature_name
 
     pool=ThreadPool(processes = cv2.getNumberOfCPUs())
     kp1, desc1 = affine_detect(detector, img1, pool=pool)

samples/python2/browse.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 browse.py
@@ -14,6 +14,8 @@ browse.py [image filename]
 
 import numpy as np
 import cv2
+
+# built-in modules
 import sys
 
 if __name__ == '__main__':
@@ -25,6 +27,10 @@ if __name__ == '__main__':
         fn = sys.argv[1]
         print 'loading %s ...' % fn
         img = cv2.imread(fn)
+        if img is None:
+            print 'Failed to load fn:', fn
+            sys.exit(1)
+
     else:
         sz = 4096
         print 'generating %dx%d procedural image ...' % (sz, sz)
@@ -33,6 +39,7 @@ if __name__ == '__main__':
         track = np.int32(track*10 + (sz/2, sz/2))
         cv2.polylines(img, [track], 0, 255, 1, cv2.CV_AA)
 
+
     small = img
     for i in xrange(3):
         small = cv2.pyrDown(small)

samples/python2/calibrate.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 import numpy as np
 import cv2
-import os
+
+# local modules
 from common import splitfn
 
+# built-in modules
+import os
+
+
 USAGE = '''
 USAGE: calib.py [--save <filename>] [--debug <output path>] [--square_size] [<image mask>]
 '''
@@ -12,13 +17,17 @@ USAGE: calib.py [--save <filename>] [--debug <output path>] [--square_size] [<im
 
 
 if __name__ == '__main__':
-    import sys, getopt
+    import sys
+    import getopt
     from glob import glob
 
     args, img_mask = getopt.getopt(sys.argv[1:], '', ['save=', 'debug=', 'square_size='])
     args = dict(args)
-    try: img_mask = img_mask[0]
-    except: img_mask = '../cpp/left*.jpg'
+    try:
+        img_mask = img_mask[0]
+    except:
+        img_mask = '../cpp/left*.jpg'
+    
     img_names = glob(img_mask)
     debug_dir = args.get('--debug')
     square_size = float(args.get('--square_size', 1.0))
@@ -34,6 +43,10 @@ if __name__ == '__main__':
     for fn in img_names:
         print 'processing %s...' % fn,
         img = cv2.imread(fn, 0)
+        if img is None:
+          print "Failed to load", fn
+          continue
+        
         h, w = img.shape[:2]
         found, corners = cv2.findChessboardCorners(img, pattern_size)
         if found:

samples/python2/camshift.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Camshift tracker
@@ -24,6 +24,8 @@ Keys:
 
 import numpy as np
 import cv2
+
+# local module
 import video
 
 
@@ -98,8 +100,10 @@ class App(object):
 
                 if self.show_backproj:
                     vis[:] = prob[...,np.newaxis]
-                try: cv2.ellipse(vis, track_box, (0, 0, 255), 2)
-                except: print track_box
+                try:
+                    cv2.ellipse(vis, track_box, (0, 0, 255), 2)
+                except: 
+                    print track_box
 
             cv2.imshow('camshift', vis)
 
@@ -113,8 +117,10 @@ class App(object):
 
 if __name__ == '__main__':
     import sys
-    try: video_src = sys.argv[1]
-    except: video_src = 0
+    try:
+        video_src = sys.argv[1]
+    except: 
+        video_src = 0
     print __doc__
     App(video_src).run()
 

samples/python2/coherence.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Coherence-enhancing filtering example
@@ -40,8 +40,10 @@ def coherence_filter(img, sigma = 11, str_sigma = 11, blend = 0.5, iter_n = 4):
 
 if __name__ == '__main__':
     import sys
-    try: fn = sys.argv[1]
-    except: fn = '../cpp/baboon.jpg'
+    try: 
+        fn = sys.argv[1]
+    except: 
+        fn = '../cpp/baboon.jpg'
 
     src = cv2.imread(fn)
 

samples/python2/color_histogram.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 import numpy as np
 import cv2
-from time import clock
+
+# built-in modules
 import sys
+from time import clock
 
+# local modules
 import video
 
 if __name__ == '__main__':
@@ -24,8 +27,10 @@ if __name__ == '__main__':
         hist_scale = val
     cv2.createTrackbar('scale', 'hist', hist_scale, 32, set_scale)
 
-    try: fn = sys.argv[1]
-    except: fn = 0
+    try:
+        fn = sys.argv[1]
+    except:
+        fn = 0
     cam = video.create_capture(fn, fallback='synth:bg=../cpp/baboon.jpg:class=chess:noise=0.05')
 
     while True:

samples/python2/common.py

-#/usr/bin/env python
-
 '''
 This module contains some common routines used by other samples.
 '''
 
 import numpy as np
 import cv2
+
+# built-in modules
 import os
-from contextlib import contextmanager
 import itertools as it
+from contextlib import contextmanager
 
 image_extensions = ['.bmp', '.jpg', '.jpeg', '.png', '.tif', '.tiff', '.pbm', '.pgm', '.ppm']
 

samples/python2/contours.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 This program illustrates the use of findContours and drawContours.

samples/python2/deconvolution.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Wiener deconvolution.
@@ -32,6 +32,8 @@ Examples:
 
 import numpy as np
 import cv2
+
+# local module
 from common import nothing
 
 
@@ -65,12 +67,18 @@ if __name__ == '__main__':
     import sys, getopt
     opts, args = getopt.getopt(sys.argv[1:], '', ['circle', 'angle=', 'd=', 'snr='])
     opts = dict(opts)
-    try: fn = args[0]
-    except: fn = 'data/licenseplate_motion.jpg'
+    try:
+        fn = args[0]
+    except: 
+        fn = 'data/licenseplate_motion.jpg'
 
     win = 'deconvolution'
 
     img = cv2.imread(fn, 0)
+    if img is None:
+        print 'Failed to load fn1:', fn1
+        sys.exit(1)
+    
     img = np.float32(img)/255.0
     cv2.imshow('input', img)
 

samples/python2/demo.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Sample-launcher application.
 '''
 
-import Tkinter as tk
-from ScrolledText import ScrolledText
-from glob import glob
+# local modules
 from common import splitfn
+
+# built-in modules
+import sys
 import webbrowser
+import Tkinter as tk
+from glob import glob
 from subprocess import Popen
+from ScrolledText import ScrolledText
+
 
 #from IPython.Shell import IPShellEmbed
 #ipshell = IPShellEmbed()
@@ -136,7 +141,8 @@ class App:
         count = tk.IntVar()
         while True:
             match_index = text.search(pattern, 'matchPos', count=count, regexp=regexp, stopindex='end')
-            if not match_index: break
+            if not match_index: 
+                break
             end_index = text.index( "%s+%sc" % (match_index, count.get()) )
             text.mark_set('matchPos', end_index)
             if callable(tag_proc):
@@ -147,7 +153,7 @@ class App:
     def on_run(self, *args):
         cmd = self.cmd_entry.get()
         print 'running:', cmd
-        Popen("python " + cmd, shell=True)
+        Popen(sys.executable + ' ' + cmd, shell=True)
 
     def run(self):
         tk.mainloop()

samples/python2/digits.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 SVM and KNearest digit recognition.
@@ -23,12 +23,19 @@ Usage:
    digits.py
 '''
 
-import numpy as np
-import cv2
+# built-in modules
 from multiprocessing.pool import ThreadPool
-from common import clock, mosaic
+
+import cv2
+
+import numpy as np
 from numpy.linalg import norm
 
+# local modules
+from common import clock, mosaic
+
+
+
 SZ = 20 # size of each digit is SZ x SZ
 CLASS_N = 10
 DIGITS_FN = 'data/digits.png'

samples/python2/digits_adjust.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Digit recognition adjustment.

samples/python2/digits_video.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 import numpy as np
 import cv2
+
+# built-in modules
 import os
 import sys
+
+# local modules
 import video
 from common import mosaic
 
 from digits import *
 
 def main():
-    try: src = sys.argv[1]
-    except: src = 0
+    try: 
+        src = sys.argv[1]
+    except: 
+        src = 0
     cap = video.create_capture(src)
 
     classifier_fn = 'digits_svm.dat'
@@ -30,8 +36,10 @@ def main():
         bin = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY_INV, 31, 10)
         bin = cv2.medianBlur(bin, 3)
         contours, heirs = cv2.findContours( bin.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
-        try: heirs = heirs[0]
-        except: heirs = []
+        try:
+            heirs = heirs[0]
+        except:
+            heirs = []
 
         for cnt, heir in zip(contours, heirs):
             _, _, _, outer_i = heir

samples/python2/distrans.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Distance transform sample.
@@ -15,15 +15,22 @@ Keys:
 import numpy as np
 import cv2
 import cv2.cv as cv
+
 from common import make_cmap
 
 if __name__ == '__main__':
     import sys
-    try: fn = sys.argv[1]
-    except: fn = '../cpp/fruits.jpg'
+    try:
+        fn = sys.argv[1]
+    except:
+        fn = '../cpp/fruits.jpg'
     print __doc__
 
     img = cv2.imread(fn, 0)
+    if img is None:
+        print 'Failed to load fn:', fn
+        sys.exit(1)
+        
     cm = make_cmap('jet')
     need_update = True
     voronoi = False

samples/python2/edge.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 This sample demonstrates Canny edge detection.
@@ -11,15 +11,21 @@ Usage:
 '''
 
 import cv2
+
+# relative module
 import video
+
+# built-in module
 import sys
 
 
 if __name__ == '__main__':
     print __doc__
 
-    try: fn = sys.argv[1]
-    except: fn = 0
+    try:
+        fn = sys.argv[1]
+    except:
+        fn = 0
 
     def nothing(*arg):
         pass

samples/python2/facedetect.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 import numpy as np
 import cv2
 import cv2.cv as cv
+
+# local modules
 from video import create_capture
 from common import clock, draw_str
 
@@ -26,8 +28,10 @@ if __name__ == '__main__':
     print help_message
 
     args, video_src = getopt.getopt(sys.argv[1:], '', ['cascade=', 'nested-cascade='])
-    try: video_src = video_src[0]
-    except: video_src = 0
+    try:
+        video_src = video_src[0]
+    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")

samples/python2/feature_homography.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Feature homography
@@ -24,6 +24,8 @@ Select a textured planar object to track by drawing a box with a mouse.
 
 import numpy as np
 import cv2
+
+# local modules
 import video
 import common
 from common import getsize, draw_keypoints
@@ -85,6 +87,8 @@ if __name__ == '__main__':
     print __doc__
 
     import sys
-    try: video_src = sys.argv[1]
-    except: video_src = 0
+    try:
+        video_src = sys.argv[1]
+    except:
+        video_src = 0
     App(video_src).run()

samples/python2/find_obj.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Feature-based image matching sample.

samples/python2/fitline.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Robust line fitting.
@@ -24,7 +24,11 @@ ESC   - exit
 
 import numpy as np
 import cv2
+
+# built-in modules
 import itertools as it
+
+# local modules
 from common import draw_str
 
 

samples/python2/floodfill.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Floodfill sample.
@@ -19,11 +19,17 @@ import cv2
 
 if __name__ == '__main__':
     import sys
-    try: fn = sys.argv[1]
-    except: fn = '../cpp/fruits.jpg'
+    try:
+        fn = sys.argv[1]
+    except:
+        fn = '../cpp/fruits.jpg'
     print __doc__
 
     img = cv2.imread(fn, True)
+    if img is None:
+        print 'Failed to load image file:', fn
+        sys.exit(1)
+    
     h, w = img.shape[:2]
     mask = np.zeros((h+2, w+2), np.uint8)
     seed_pt = None

samples/python2/gabor_threads.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 gabor_threads.py
@@ -49,10 +49,16 @@ if __name__ == '__main__':
     from common import Timer
 
     print __doc__
-    try: img_fn = sys.argv[1]
-    except: img_fn = '../cpp/baboon.jpg'
+    try:
+        img_fn = sys.argv[1]
+    except: 
+        img_fn = '../cpp/baboon.jpg'
 
     img = cv2.imread(img_fn)
+    if img is None:
+        print 'Failed to load image file:', img_fn
+        sys.exit(1)
+    
     filters = build_filters()
 
     with Timer('running single-threaded'):

samples/python2/gaussian_mix.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 import numpy as np
 from numpy import random

samples/python2/hist.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 ''' This is a sample for histogram plotting for RGB images and grayscale images for better understanding of colour distribution
 
@@ -55,11 +55,16 @@ if __name__ == '__main__':
     import sys
 
     if len(sys.argv)>1:
-        im = cv2.imread(sys.argv[1])
+        fname = sys.argv[1]
     else :
-        im = cv2.imread('../cpp/lena.jpg')
+        fname = '../cpp/lena.jpg'
         print "usage : python hist.py <image_file>"
 
+    im = cv2.imread(fname)
+    
+    if im is None:
+        print 'Failed to load image file:', fname
+        sys.exit(1)
 
     gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
 

samples/python2/inpaint.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Inpainting sample.
@@ -21,11 +21,18 @@ from common import Sketcher
 
 if __name__ == '__main__':
     import sys
-    try: fn = sys.argv[1]
-    except: fn = '../cpp/fruits.jpg'
+    try:
+        fn = sys.argv[1]
+    except: 
+        fn = '../cpp/fruits.jpg'
+        
     print __doc__
 
     img = cv2.imread(fn)
+    if img is None:
+        print 'Failed to load image file:', fn
+        sys.exit(1)
+        
     img_mark = img.copy()
     mark = np.zeros(img.shape[:2], np.uint8)
     sketch = Sketcher('img', [img_mark, mark], lambda : ((255, 255, 255), 255))

samples/python2/kmeans.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 K-means clusterization sample.

samples/python2/lappyr.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 ''' An example of Laplacian Pyramid construction and merging.
 
@@ -40,8 +40,10 @@ if __name__ == '__main__':
     import sys
     print __doc__
 
-    try: fn = sys.argv[1]
-    except: fn = 0
+    try:
+        fn = sys.argv[1]
+    except:
+        fn = 0
     cap = video.create_capture(fn)
 
     leveln = 6

samples/python2/letter_recog.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 The sample demonstrates how to train Random Trees classifier

samples/python2/lk_homography.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Lucas-Kanade homography tracker
@@ -103,8 +103,10 @@ class App:
 
 def main():
     import sys
-    try: video_src = sys.argv[1]
-    except: video_src = 0
+    try:
+        video_src = sys.argv[1]
+    except:
+        video_src = 0
 
     print __doc__
     App(video_src).run()

samples/python2/lk_track.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Lucas-Kanade tracker
@@ -88,8 +88,10 @@ class App:
 
 def main():
     import sys
-    try: video_src = sys.argv[1]
-    except: video_src = 0
+    try:
+        video_src = sys.argv[1]
+    except:
+        video_src = 0
 
     print __doc__
     App(video_src).run()

samples/python2/morphology.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Morphology operations.
@@ -23,9 +23,17 @@ if __name__ == '__main__':
     from itertools import cycle
     from common import draw_str
 
-    try: fn = sys.argv[1]
-    except: fn = '../cpp/baboon.jpg'
+    try:
+        fn = sys.argv[1]
+    except:
+        fn = '../cpp/baboon.jpg'
+    
     img = cv2.imread(fn)
+    
+    if img is None:
+        print 'Failed to load image file:', fn
+        sys.exit(1)
+    
     cv2.imshow('original', img)
 
     modes = cycle(['erode/dilate', 'open/close', 'blackhat/tophat', 'gradient'])

samples/python2/mosse.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 MOSSE tracking sample
@@ -182,7 +182,9 @@ if __name__ == '__main__':
     import sys, getopt
     opts, args = getopt.getopt(sys.argv[1:], '', ['pause'])
     opts = dict(opts)
-    try: video_src = args[0]
-    except: video_src = '0'
+    try:
+        video_src = args[0]
+    except:
+        video_src = '0'
 
     App(video_src, paused = '--pause' in opts).run()

samples/python2/motempl.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 import numpy as np
 import cv2
@@ -20,8 +20,10 @@ def draw_motion_comp(vis, (x, y, w, h), angle, color):
 
 if __name__ == '__main__':
     import sys
-    try: video_src = sys.argv[1]
-    except: video_src = 0
+    try:
+        video_src = sys.argv[1]
+    except:
+        video_src = 0
 
     cv2.namedWindow('motempl')
     visuals = ['input', 'frame_diff', 'motion_hist', 'grad_orient']

samples/python2/mouse_and_match.py

-#/usr/bin/env python
-
 #!/usr/bin/env python
 '''
 mouse_and_match.py [-i path | --input path: default ./]
@@ -11,12 +9,15 @@ Demonstrate using a mouse to interact with an image:
  ESC to exit
 '''
 import numpy as np
-from math import *
-import sys
+import cv2 as cv
+
+# built-in modules
 import os
+import sys
 import glob
 import argparse
-import cv2 as cv
+from math import *
+
 
 drag_start = None
 sel = (0,0,0,0)

samples/python2/mser.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 MSER detector demo
@@ -20,8 +20,10 @@ import video
 
 if __name__ == '__main__':
     import sys
-    try: video_src = sys.argv[1]
-    except: video_src = 0
+    try:
+        video_src = sys.argv[1]
+    except:
+        video_src = 0
 
     cam = video.create_capture(video_src)
     mser = cv2.MSER()

samples/python2/opt_flow.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 import numpy as np
 import cv2
@@ -48,8 +48,10 @@ def warp_flow(img, flow):
 if __name__ == '__main__':
     import sys
     print help_message
-    try: fn = sys.argv[1]
-    except: fn = 0
+    try:
+        fn = sys.argv[1]
+    except:
+        fn = 0
 
     cam = video.create_capture(fn)
     ret, prev = cam.read()

samples/python2/peopledetect.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 import numpy as np
 import cv2
@@ -36,6 +36,9 @@ if __name__ == '__main__':
         print fn, ' - ',
         try:
             img = cv2.imread(fn)
+            if img is None:
+                print 'Failed to load image file:', fn
+                continue
         except:
             print 'loading error'
             continue

samples/python2/plane_ar.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Planar augmented reality
@@ -100,6 +100,8 @@ if __name__ == '__main__':
     print __doc__
 
     import sys
-    try: video_src = sys.argv[1]
-    except: video_src = 0
+    try:
+        video_src = sys.argv[1]
+    except:
+        video_src = 0
     App(video_src).run()

samples/python2/plane_tracker.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Multitarget planar tracking
@@ -23,7 +23,11 @@ Select a textured planar object to track by drawing a box with a mouse.
 
 import numpy as np
 import cv2
+
+# built-in modules
 from collections import namedtuple
+
+# local modules
 import video
 import common
 
@@ -168,6 +172,8 @@ if __name__ == '__main__':
     print __doc__
 
     import sys
-    try: video_src = sys.argv[1]
-    except: video_src = 0
+    try:
+        video_src = sys.argv[1]
+    except:
+        video_src = 0
     App(video_src).run()

samples/python2/squares.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Simple "Square Detector" program.

samples/python2/stereo_match.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Simple example of stereo image matching and point cloud generation.

samples/python2/texture_flow.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Texture flow direction estimation.
@@ -15,10 +15,16 @@ import cv2
 
 if __name__ == '__main__':
     import sys
-    try: fn = sys.argv[1]
-    except: fn = 'data/starry_night.jpg'
+    try:
+        fn = sys.argv[1]
+    except:
+        fn = 'data/starry_night.jpg'
 
     img = cv2.imread(fn)
+    if img is None:
+        print 'Failed to load image file:', fn
+        sys.exit(1)
+        
     gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
     h, w = img.shape[:2]
 

samples/python2/turing.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Multiscale Turing Patterns generator

samples/python2/video.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Video capture sample.
@@ -30,9 +30,14 @@ Keys:
 '''
 
 import numpy as np
+from numpy import pi, sin, cos
+
 import cv2
+
+# built-in modules
 from time import clock
-from numpy import pi, sin, cos
+
+# local modules
 import common
 
 class VideoSynthBase(object):

samples/python2/video_dmtx.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Data matrix detector sample.
@@ -18,6 +18,8 @@ Keyboard shortcuts:
 
 import cv2
 import numpy as np
+
+# built-in modules
 import sys
 
 def data_matrix_demo(cap):

samples/python2/video_threaded.py

-#/usr/bin/env python
+#!/usr/bin/env python
 
 '''
 Multithreaded video processing sample.
@@ -39,8 +39,10 @@ if __name__ == '__main__':
 
     print __doc__
 
-    try: fn = sys.argv[1]
-    except: fn = 0
+    try:
+        fn = sys.argv[1]
+    except:
+        fn = 0
     cap = video.create_capture(fn)
 
 

samples/python2/watershed.py

@@ -31,6 +31,9 @@ from common import Sketcher
 class App:
     def __init__(self, fn):
         self.img = cv2.imread(fn)
+        if self.img is None:
+            raise Exception('Failed to load image file: %s' % fn)
+
         h, w = self.img.shape[:2]
         self.markers = np.zeros((h, w), np.int32)
         self.markers_vis = self.img.copy()
@@ -73,7 +76,9 @@ class App:
 
 if __name__ == '__main__':
     import sys
-    try: fn = sys.argv[1]
-    except: fn = '../cpp/fruits.jpg'
+    try:
+        fn = sys.argv[1]
+    except:
+        fn = '../cpp/fruits.jpg'
     print __doc__
     App(fn).run()