mirror of
https://github.com/opencv/opencv.git
synced 2024-11-25 03:30:34 +08:00
67 lines
2.1 KiB
Python
67 lines
2.1 KiB
Python
#!/usr/bin/python
|
|
import urllib2
|
|
import sys
|
|
import cv2.cv as 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 = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/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)
|
|
cv.DestroyAllWindows()
|