Merge pull request #802 from SpecLad:shebang

This commit is contained in:
Andrey Kamaev
2013-04-12 15:00:28 +04:00
committed by OpenCV Buildbot
82 changed files with 81 additions and 83 deletions
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#/usr/bin/env python
#!/usr/bin/env python
'''
Utility for measuring python opencv API coverage by samples.
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#/usr/bin/env python
#!/usr/bin/env python
'''
Scans current directory for *.py files and reports
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#/usr/bin/env python
#!/usr/bin/env python
'''
Affine invariant feature-based image matching sample.
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#/usr/bin/env python
#!/usr/bin/env python
'''
browse.py
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#/usr/bin/env python
#!/usr/bin/env python
import numpy as np
import cv2
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#/usr/bin/env python
#!/usr/bin/env python
'''
Camshift tracker
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#/usr/bin/env python
#!/usr/bin/env python
'''
Coherence-enhancing filtering example
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#/usr/bin/env python
#!/usr/bin/env python
import numpy as np
import cv2
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#/usr/bin/env python
#!/usr/bin/env python
'''
This module contais some common routines used by other samples.
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#/usr/bin/env python
#!/usr/bin/env python
'''
This program illustrates the use of findContours and drawContours.
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#/usr/bin/env python
#!/usr/bin/env python
'''
Wiener deconvolution.
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#/usr/bin/env python
#!/usr/bin/env python
'''
Sample-launcher application.
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#/usr/bin/env python
#!/usr/bin/env python
import cv2
import numpy as np
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#/usr/bin/env python
#!/usr/bin/env python
'''
SVM and KNearest digit recognition.
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#/usr/bin/env python
#!/usr/bin/env python
'''
Digit recognition adjustment.
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#/usr/bin/env python
#!/usr/bin/env python
import numpy as np
import cv2
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#/usr/bin/env python
#!/usr/bin/env python
'''
Distance transform sample.
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#/usr/bin/env python
#!/usr/bin/env python
'''
This sample demonstrates Canny edge detection.
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#/usr/bin/env python
#!/usr/bin/env python
import numpy as np
import cv2
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#/usr/bin/env python
#!/usr/bin/env python
'''
Feature homography
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#/usr/bin/env python
#!/usr/bin/env python
'''
Feature-based image matching sample.
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#/usr/bin/env python
#!/usr/bin/env python
'''
Robust line fitting.
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#/usr/bin/env python
#!/usr/bin/env python
'''
Floodfill sample.
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#/usr/bin/env python
#!/usr/bin/env python
'''
gabor_threads.py
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#/usr/bin/env python
#!/usr/bin/env python
import numpy as np
from numpy import random
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#/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
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#/usr/bin/env python
#!/usr/bin/env python
'''
Inpainting sample.
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#/usr/bin/env python
#!/usr/bin/env python
'''
K-means clusterization sample.
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#/usr/bin/env python
#!/usr/bin/env python
''' An example of Laplacian Pyramid construction and merging.
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#/usr/bin/env python
#!/usr/bin/env python
'''
The sample demonstrates how to train Random Trees classifier
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#/usr/bin/env python
#!/usr/bin/env python
'''
Lucas-Kanade homography tracker
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#/usr/bin/env python
#!/usr/bin/env python
'''
Lucas-Kanade tracker
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#/usr/bin/env python
#!/usr/bin/env python
'''
Morphology operations.
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#/usr/bin/env python
#!/usr/bin/env python
'''
MOSSE tracking sample
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#/usr/bin/env python
#!/usr/bin/env python
import numpy as np
import cv2
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#/usr/bin/env python
#!/usr/bin/env python
#!/usr/bin/env python
'''
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#/usr/bin/env python
#!/usr/bin/env python
'''
MSER detector demo
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#/usr/bin/env python
#!/usr/bin/env python
import numpy as np
import cv2
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#/usr/bin/env python
#!/usr/bin/env python
import numpy as np
import cv2
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#/usr/bin/env python
#!/usr/bin/env python
'''
Planar augmented reality
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#/usr/bin/env python
#!/usr/bin/env python
'''
Multitarget planar tracking
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#/usr/bin/env python
#!/usr/bin/env python
'''
Simple "Square Detector" program.
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#/usr/bin/env python
#!/usr/bin/env python
'''
Simple example of stereo image matching and point cloud generation.
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#/usr/bin/env python
#!/usr/bin/env python
'''
Texture flow direction estimation.
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#/usr/bin/env python
#!/usr/bin/env python
'''
Multiscale Turing Patterns generator
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#/usr/bin/env python
#!/usr/bin/env python
'''
Video capture sample.
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#/usr/bin/env python
#!/usr/bin/env python
'''
Data matrix detector sample.
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#/usr/bin/env python
#!/usr/bin/env python
'''
Multithreaded video processing sample.
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#/usr/bin/env python
#!/usr/bin/env python
'''
Watershed segmentation