Merge pull request #5802 from bastelflp:py3samples_docstr

samples/python2/.gitignore

+# python binary files
+*.pyc
+__pycache__
+
+# tmp files from examples
+/output
+*.dat
+out.ply
+svm_scores.npz
+unused_api.txt

samples/python2/_doc.py

@@ -5,12 +5,23 @@ Scans current directory for *.py files and reports
 ones with missing __doc__ string.
 '''
 
+# Python 2/3 compatibility
+from __future__ import print_function
+import sys
+PY3 = sys.version_info[0] == 3
+
 from glob import glob
 
 if __name__ == '__main__':
-    print '--- undocumented files:'
+    print('--- undocumented files:')
     for fn in glob('*.py'):
         loc = {}
-        execfile(fn, loc)
+        try:
+            if PY3:
+                exec(open(fn).read(), loc)
+            else:
+                execfile(fn, loc)
+        except:
+            pass
         if '__doc__' not in loc:
-            print fn
+            print(fn)

samples/python2/calibrate.py

 #!/usr/bin/env python
 
+'''
+camera calibration for distorted images with chess board samples
+reads distorted images, calculates the calibration and write undistorted images
+
+usage:
+    calibrate.py [--debug <output path>] [--square_size] [<image mask>]
+
+default values:
+    --debug:    ./output/
+    --square_size: 1.0
+    <image mask> defaults to ../data/left*.jpg
+'''
+
 # Python 2/3 compatibility
 from __future__ import print_function
 
@@ -12,64 +25,88 @@ from common import splitfn
 # built-in modules
 import os
 
-
-USAGE = '''
-USAGE: calib.py [--save <filename>] [--debug <output path>] [--square_size] [<image mask>]
-'''
-
-
-
 if __name__ == '__main__':
     import sys
     import getopt
     from glob import glob
 
-    args, img_mask = getopt.getopt(sys.argv[1:], '', ['save=', 'debug=', 'square_size='])
+    args, img_mask = getopt.getopt(sys.argv[1:], '', ['debug=', 'square_size='])
     args = dict(args)
-    try:
+    args.setdefault('--debug', './output/')
+    args.setdefault('--square_size', 1.0)
+    if not img_mask:
+        img_mask = '../data/left*.jpg'  # default
+    else:
         img_mask = img_mask[0]
-    except:
-        img_mask = '../data/left*.jpg'
 
     img_names = glob(img_mask)
     debug_dir = args.get('--debug')
-    square_size = float(args.get('--square_size', 1.0))
+    if not os.path.isdir(debug_dir):
+        os.mkdir(debug_dir)
+    square_size = float(args.get('--square_size'))
 
     pattern_size = (9, 6)
-    pattern_points = np.zeros( (np.prod(pattern_size), 3), np.float32 )
-    pattern_points[:,:2] = np.indices(pattern_size).T.reshape(-1, 2)
+    pattern_points = np.zeros((np.prod(pattern_size), 3), np.float32)
+    pattern_points[:, :2] = np.indices(pattern_size).T.reshape(-1, 2)
     pattern_points *= square_size
 
     obj_points = []
     img_points = []
     h, w = 0, 0
+    img_names_undistort = []
     for fn in img_names:
-        print('processing %s...' % fn,)
+        print('processing %s... ' % fn, end='')
         img = cv2.imread(fn, 0)
         if img is None:
-          print("Failed to load", fn)
-          continue
+            print("Failed to load", fn)
+            continue
 
         h, w = img.shape[:2]
         found, corners = cv2.findChessboardCorners(img, pattern_size)
         if found:
-            term = ( cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_COUNT, 30, 0.1 )
+            term = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_COUNT, 30, 0.1)
             cv2.cornerSubPix(img, corners, (5, 5), (-1, -1), term)
+
         if debug_dir:
             vis = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
             cv2.drawChessboardCorners(vis, pattern_size, corners, found)
             path, name, ext = splitfn(fn)
-            cv2.imwrite('%s/%s_chess.bmp' % (debug_dir, name), vis)
+            outfile = debug_dir + name + '_chess.png'
+            cv2.imwrite(outfile, vis)
+            if found:
+                img_names_undistort.append(outfile)
+
         if not found:
             print('chessboard not found')
             continue
+
         img_points.append(corners.reshape(-1, 2))
         obj_points.append(pattern_points)
 
         print('ok')
 
+    # calculate camera distortion
     rms, camera_matrix, dist_coefs, rvecs, tvecs = cv2.calibrateCamera(obj_points, img_points, (w, h), None, None)
-    print("RMS:", rms)
+
+    print("\nRMS:", rms)
     print("camera matrix:\n", camera_matrix)
     print("distortion coefficients: ", dist_coefs.ravel())
+
+    # undistort the image with the calibration
+    print('')
+    for img_found in img_names_undistort:
+        img = cv2.imread(img_found)
+
+        h,  w = img.shape[:2]
+        newcameramtx, roi = cv2.getOptimalNewCameraMatrix(camera_matrix, dist_coefs, (w, h), 1, (w, h))
+
+        dst = cv2.undistort(img, camera_matrix, dist_coefs, None, newcameramtx)
+
+        # crop and save the image
+        x, y, w, h = roi
+        dst = dst[y:y+h, x:x+w]
+        outfile = img_found + '_undistorted.png'
+        print('Undistorted image written to: %s' % outfile)
+        cv2.imwrite(outfile, dst)
+
     cv2.destroyAllWindows()

samples/python2/color_histogram.py

 #!/usr/bin/env python
 
+'''
+Video histogram sample to show live histogram of video
+
+Keys:
+    ESC    - exit
+
+'''
+
 import numpy as np
 import cv2
 
 # built-in modules
 import sys
-from time import clock
 
 # local modules
 import video
@@ -22,6 +29,7 @@ if __name__ == '__main__':
 
     cv2.namedWindow('hist', 0)
     hist_scale = 10
+
     def set_scale(val):
         global hist_scale
         hist_scale = val
@@ -42,8 +50,7 @@ if __name__ == '__main__':
         hsv = cv2.cvtColor(small, cv2.COLOR_BGR2HSV)
         dark = hsv[...,2] < 32
         hsv[dark] = 0
-        h = cv2.calcHist( [hsv], [0, 1], None, [180, 256], [0, 180, 0, 256] )
-
+        h = cv2.calcHist([hsv], [0, 1], None, [180, 256], [0, 180, 0, 256])
 
         h = np.clip(h*0.005*hist_scale, 0, 1)
         vis = hsv_map*h[:,:,np.newaxis] / 255.0

samples/python2/dft.py

 #!/usr/bin/env python
 
+'''
+sample for disctrete fourier transform (dft)
+
+USAGE:
+    dft.py <image_file>
+'''
+
+
 # Python 2/3 compatibility
 from __future__ import print_function
 
@@ -56,9 +64,9 @@ def shift_dft(src, dst=None):
 
 if __name__ == "__main__":
 
-    if len(sys.argv)>1:
+    if len(sys.argv) > 1:
         im = cv2.imread(sys.argv[1])
-    else :
+    else:
         im = cv2.imread('../data/baboon.jpg')
         print("usage : python dft.py <image_file>")
 

samples/python2/facedetect.py

 #!/usr/bin/env python
 
+'''
+face detection using haar cascades
+
+USAGE:
+    facedetect.py [--cascade <cascade_fn>] [--nested-cascade <cascade_fn>] [<video_source>]
+'''
+
 # Python 2/3 compatibility
 from __future__ import print_function
 
@@ -10,12 +17,10 @@ import cv2
 from video import create_capture
 from common import clock, draw_str
 
-help_message = '''
-USAGE: facedetect.py [--cascade <cascade_fn>] [--nested-cascade <cascade_fn>] [<video_source>]
-'''
 
 def detect(img, cascade):
-    rects = cascade.detectMultiScale(img, scaleFactor=1.3, minNeighbors=4, minSize=(30, 30), flags = cv2.CASCADE_SCALE_IMAGE)
+    rects = cascade.detectMultiScale(img, scaleFactor=1.3, minNeighbors=4, minSize=(30, 30),
+                                     flags=cv2.CASCADE_SCALE_IMAGE)
     if len(rects) == 0:
         return []
     rects[:,2:] += rects[:,:2]
@@ -27,7 +32,7 @@ def draw_rects(img, rects, color):
 
 if __name__ == '__main__':
     import sys, getopt
-    print(help_message)
+    print(__doc__)
 
     args, video_src = getopt.getopt(sys.argv[1:], '', ['cascade=', 'nested-cascade='])
     try:

samples/python2/houghcircles.py

@@ -2,8 +2,10 @@
 
 '''
 This example illustrates how to use cv2.HoughCircles() function.
-Usage: ./houghcircles.py [<image_name>]
-image argument defaults to ../data/board.jpg
+
+Usage:
+    houghcircles.py [<image_name>]
+    image argument defaults to ../data/board.jpg
 '''
 
 # Python 2/3 compatibility
@@ -14,11 +16,11 @@ import numpy as np
 import sys
 
 if __name__ == '__main__':
-
     print(__doc__)
+
     try:
         fn = sys.argv[1]
-    except:
+    except IndexError:
         fn = "../data/board.jpg"
 
     src = cv2.imread(fn, 1)
@@ -30,7 +32,7 @@ if __name__ == '__main__':
     a, b, c = circles.shape
     for i in range(b):
         cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), circles[0][i][2], (0, 0, 255), 3, cv2.LINE_AA)
-        cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), 2, (0, 255, 0), 3, cv2.LINE_AA) # draw center of circle
+        cv2.circle(cimg, (circles[0][i][0], circles[0][i][1]), 2, (0, 255, 0), 3, cv2.LINE_AA)  # draw center of circle
 
     cv2.imshow("source", src)
     cv2.imshow("detected circles", cimg)

samples/python2/houghlines.py

 #!/usr/bin/python
+
 '''
 This example illustrates how to use Hough Transform to find lines
-Usage: ./houghlines.py [<image_name>]
-image argument defaults to ../data/pic1.png
+
+Usage:
+    houghlines.py [<image_name>]
+    image argument defaults to ../data/pic1.png
 '''
+
 # Python 2/3 compatibility
 from __future__ import print_function
 
@@ -13,12 +17,13 @@ import sys
 import math
 
 if __name__ == '__main__':
+    print(__doc__)
 
     try:
         fn = sys.argv[1]
-    except:
+    except IndexError:
         fn = "../data/pic1.png"
-    print(__doc__)
+
     src = cv2.imread(fn)
     dst = cv2.Canny(src, 50, 200)
     cdst = cv2.cvtColor(dst, cv2.COLOR_GRAY2BGR)
@@ -42,7 +47,6 @@ if __name__ == '__main__':
             pt2 = ( int(x0-1000*(-b)), int(y0-1000*(a)) )
             cv2.line(cdst, pt1, pt2, (0, 0, 255), 3, cv2.LINE_AA)
 
-
     cv2.imshow("source", src)
     cv2.imshow("detected lines", cdst)
     cv2.waitKey(0)

samples/python2/logpolar.py

 #!/usr/bin/env python
 
+'''
+plots image as logPolar and linearPolar
+
+Usage:
+    logpolar.py
+
+Keys:
+    ESC    - exit
+'''
+
 # Python 2/3 compatibility
 from __future__ import print_function
 
 import cv2
 
 if __name__ == '__main__':
+    print(__doc__)
+
     import sys
     try:
         fn = sys.argv[1]
-    except:
+    except IndexError:
         fn = '../data/fruits.jpg'
 
     img = cv2.imread(fn)

samples/python2/opencv_version.py

 #!/usr/bin/env python
 
+'''
+prints OpenCV version
+
+Usage:
+    opencv_version.py [<params>]
+    params:
+        --build: print complete build info
+        --help:  print this help
+'''
+
 # Python 2/3 compatibility
 from __future__ import print_function
 
@@ -7,14 +17,16 @@ import cv2
 
 if __name__ == '__main__':
     import sys
+    print(__doc__)
+
     try:
         param = sys.argv[1]
-    except:
+    except IndexError:
         param = ""
 
-    if ("--build" == param):
+    if "--build" == param:
         print(cv2.getBuildInformation())
-    elif ("--help" == param):
+    elif "--help" == param:
         print("\t--build\n\t\tprint complete build info")
         print("\t--help\n\t\tprint this help")
     else:

samples/python2/opt_flow.py

 #!/usr/bin/env python
 
-# Python 2/3 compatibility
-from __future__ import print_function
-
-import numpy as np
-import cv2
-import video
+'''
+example to show optical flow
 
-help_message = '''
 USAGE: opt_flow.py [<video_source>]
 
 Keys:
  1 - toggle HSV flow visualization
  2 - toggle glitch
 
+Keys:
+    ESC    - exit
 '''
 
+# Python 2/3 compatibility
+from __future__ import print_function
+
+import numpy as np
+import cv2
+import video
+
+
 def draw_flow(img, flow, step=16):
     h, w = img.shape[:2]
     y, x = np.mgrid[step/2:h:step, step/2:w:step].reshape(2,-1).astype(int)
@@ -28,6 +33,7 @@ def draw_flow(img, flow, step=16):
         cv2.circle(vis, (x1, y1), 1, (0, 255, 0), -1)
     return vis
 
+
 def draw_hsv(flow):
     h, w = flow.shape[:2]
     fx, fy = flow[:,:,0], flow[:,:,1]
@@ -40,6 +46,7 @@ def draw_hsv(flow):
     bgr = cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
     return bgr
 
+
 def warp_flow(img, flow):
     h, w = flow.shape[:2]
     flow = -flow
@@ -50,10 +57,10 @@ def warp_flow(img, flow):
 
 if __name__ == '__main__':
     import sys
-    print(help_message)
+    print(__doc__)
     try:
         fn = sys.argv[1]
-    except:
+    except IndexError:
         fn = 0
 
     cam = video.create_capture(fn)

samples/python2/peopledetect.py

 #!/usr/bin/env python
 
+'''
+example to detect upright people in images using HOG features
+
+Usage:
+    peopledetect.py <image_names>
+
+Press any key to continue, ESC to stop.
+'''
+
 # Python 2/3 compatibility
 from __future__ import print_function
 
 import numpy as np
 import cv2
 
-help_message = '''
-USAGE: peopledetect.py <image_names> ...
-
-Press any key to continue, ESC to stop.
-'''
 
 def inside(r, q):
     rx, ry, rw, rh = r
     qx, qy, qw, qh = q
     return rx > qx and ry > qy and rx + rw < qx + qw and ry + rh < qy + qh
 
+
 def draw_detections(img, rects, thickness = 1):
     for x, y, w, h in rects:
         # the HOG detector returns slightly larger rectangles than the real objects.
@@ -30,13 +35,13 @@ if __name__ == '__main__':
     from glob import glob
     import itertools as it
 
-    print(help_message)
+    print(__doc__)
 
     hog = cv2.HOGDescriptor()
     hog.setSVMDetector( cv2.HOGDescriptor_getDefaultPeopleDetector() )
 
-
     default = ['../data/basketball2.png '] if len(sys.argv[1:]) == 0 else []
+
     for fn in it.chain(*map(glob, default + sys.argv[1:])):
         print(fn, ' - ',)
         try: