"atomic bomb" commit. Reorganized OpenCV directory structure

samples/python/numpy_array.py

@@ -0,0 +1,65 @@
+#!/usr/bin/python
+import urllib2
+import sys
+import cv
+import numpy
+
+# SRGB-linear conversions using NumPy - see http://en.wikipedia.org/wiki/SRGB
+
+def srgb2lin(x):
+    a = 0.055
+    return numpy.where(x <= 0.04045,
+                       x * (1.0 / 12.92),
+                       numpy.power((x + a) * (1.0 / (1 + a)), 2.4))
+
+def lin2srgb(x):
+    a = 0.055
+    return numpy.where(x <= 0.0031308,
+                       x * 12.92,
+                       (1 + a) * numpy.power(x, 1 / 2.4) - a)
+
+if __name__ == "__main__":
+    if len(sys.argv) > 1:
+        img0 = cv.LoadImageM( sys.argv[1], cv.CV_LOAD_IMAGE_COLOR)
+    else:
+        url = 'https://code.ros.org/svn/opencv/trunk/opencv/samples/c/lena.jpg'
+        filedata = urllib2.urlopen(url).read()
+        imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
+        cv.SetData(imagefiledata, filedata, len(filedata))
+        img0 = cv.DecodeImageM(imagefiledata, cv.CV_LOAD_IMAGE_COLOR)
+
+    cv.NamedWindow("original", 1)
+    cv.ShowImage("original", img0)
+
+    # Image was originally bytes in range 0-255.  Turn it into an array of floats in range 0.0 - 1.0
+    n = numpy.asarray(img0) / 255.0
+
+    # Use NumPy to do some transformations on the image
+
+    # Negate the image by subtracting it from 1.0
+    cv.NamedWindow("negative")
+    cv.ShowImage("negative", cv.fromarray(1.0 - n))
+
+    # Assume the image was sRGB, and compute the linear version.
+    cv.NamedWindow("linear")
+    cv.ShowImage("linear", cv.fromarray(srgb2lin(n)))
+
+    # Look at a subwindow
+    cv.NamedWindow("subwindow")
+    cv.ShowImage("subwindow", cv.fromarray(n[200:300,200:400]))
+
+    # Compute the grayscale image
+    cv.NamedWindow("monochrome")
+    ln = srgb2lin(n)
+    red = ln[:,:,0]
+    grn = ln[:,:,1]
+    blu = ln[:,:,2]
+    linear_mono = 0.3 * red + 0.59 * grn + 0.11 * blu
+    cv.ShowImage("monochrome", cv.fromarray(lin2srgb(linear_mono)))
+
+    # Apply a blur to the NumPy array using OpenCV
+    cv.NamedWindow("gaussian")
+    cv.Smooth(n, n, cv.CV_GAUSSIAN, 15, 15)
+    cv.ShowImage("gaussian", cv.fromarray(n))
+
+    cv.WaitKey(0)