Python introduction

git-svn-id: https://code.ros.org/svn/opencv/trunk@2719 73c94f0f-984f-4a5f-82bc-2d8db8d8ee08

diff --git a/opencv/doc/plastex/go b/opencv/doc/plastex/go
index 25ecac9f0d0595e1ba0e621a9ae81f441f59ee9e..1c3d5a7f4c24b4d613d4db5f97e787858905bc22 100644 (file)
--- a/opencv/doc/plastex/go
+++ b/opencv/doc/plastex/go
@@ -6,7 +6,7 @@ tput clear
 mkdir -p _build/html/python
 mkdir -p _build/html/cpp
 
-if true
+if false
 then
   rm -f *.rst
   svn up
@@ -16,13 +16,13 @@ fi
 
 if true
 then
-  rm -f *.rst
-  svn up
-  TEXINPUTS=../: python renderer.py py > a || exit
+  #rm -f *.rst
+  #svn up
+  #TEXINPUTS=../: python renderer.py py > a || exit
   TEXINPUTS=$PWD: sphinx-build -b html -D 'highlight_language=python' -D 'html_title=OpenCV 2.0 Python Reference' -d _build/doctrees . _build/html/python
 fi
 
-if true
+if false
 then
   rm -f *.rst
   svn up

diff --git a/opencv/doc/plastex/introduction.rst b/opencv/doc/plastex/introduction.rst
new file mode 100644 (file)
index 0000000..8dd53ef
--- /dev/null
+++ b/opencv/doc/plastex/introduction.rst
@@ -0,0 +1,125 @@
+Introduction
+------------
+
+Convert an image from png to jpg
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+::
+
+    import cv
+    cv.SaveImage("foo.png", cv.LoadImage("foo.jpg"))
+
+Compute the Laplacian
+^^^^^^^^^^^^^^^^^^^^^
+
+::
+
+    im = cv.LoadImage("foo.png", 1)
+    dst = cv.CreateImage(cv.GetSize(im), cv.IPL_DEPTH_16S, 3);
+    laplace = cv.Laplace(im, dst)
+    cv.SaveImage("foo-laplace.png", dst)
+
+
+Using cvGoodFeaturesToTrack
+^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+::
+
+    img = cv.LoadImage("foo.jpg")
+    eig_image = cv.CreateImage(cv.GetSize(img), cv.IPL_DEPTH_32F, 1)
+    temp_image = cv.CreateImage(cv.GetSize(img), cv.IPL_DEPTH_32F, 1)
+    # Find up to 300 corners using Harris
+    for (x,y) in cv.GoodFeaturesToTrack(img, eig_image, temp_image, 300, None, 1.0, use_harris = True):
+        print "good feature at", x,y
+
+Using GetSubRect
+^^^^^^^^^^^^^^^^
+
+GetSubRect returns a rectangular part of another image.  It does this without copying any data.
+
+::
+
+    img = cv.LoadImage("foo.jpg")
+    sub = cv.GetSubRect(img, (0, 0, 32, 32))  # sub is 32x32 patch from img top-left
+    cv.SetZero(sub)                           # clear sub to zero, which also clears 32x32 pixels in img
+
+Using CreateMat, and accessing an element
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+::
+
+    mat = cv.CreateMat(5, 5, cv.CV_32FC1)
+    mat[3,2] += 0.787
+
+
+ROS image message to OpenCV
+^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+See this tutorial: http://www.ros.org/wiki/opencv_latest/Tutorials/UsingCvBridgeToConvertBetweenROSImagesAndOpenCVImages
+
+PIL Image to OpenCV
+^^^^^^^^^^^^^^^^^^^
+
+(For details on PIL see the `PIL manual <http://www.pythonware.com/library/pil/handbook/image.htm>`_).
+
+::
+
+    import Image
+    import cv
+    pi = Image.open('foo.png')       # PIL image
+    cv_im = cv.CreateImageHeader(pi.size, cv.IPL_DEPTH_8U, 1)
+    cv.SetData(cv_im, pi.tostring())
+
+OpenCV to PIL Image
+^^^^^^^^^^^^^^^^^^^
+
+::
+
+    cv_im = cv.CreateImage((320,200), cv.IPL_DEPTH_8U, 1)
+    pi = Image.fromstring("L", cv.GetSize(cv_im), cv_im.tostring())
+
+numpy and OpenCV
+^^^^^^^^^^^^^^^^
+
+Numpy and OpenCV have different orderings for dimensions, hence the tuple reversals here::
+
+    def cv2array(im):
+      depth2dtype = {
+            cv.IPL_DEPTH_8U: 'uint8',
+            cv.IPL_DEPTH_8S: 'int8',
+            cv.IPL_DEPTH_16U: 'uint16',
+            cv.IPL_DEPTH_16S: 'int16',
+            cv.IPL_DEPTH_32S: 'int32',
+            cv.IPL_DEPTH_32F: 'float32',
+            cv.IPL_DEPTH_64F: 'float64',
+        }
+      
+      arrdtype=im.depth
+      a = np.fromstring(
+             im.tostring(),
+             dtype=depth2dtype[im.depth],
+             count=im.width*im.height*im.nChannels)
+      a.shape = (im.height,im.width,im.nChannels)
+      return a
+        
+    def array2cv(a):
+      dtype2depth = {
+            'uint8':   cv.IPL_DEPTH_8U,
+            'int8':    cv.IPL_DEPTH_8S,
+            'uint16':  cv.IPL_DEPTH_16U,
+            'int16':   cv.IPL_DEPTH_16S,
+            'int32':   cv.IPL_DEPTH_32S,
+            'float32': cv.IPL_DEPTH_32F,
+            'float64': cv.IPL_DEPTH_64F,
+        }
+      try:
+        nChannels = a.shape[2]
+      except:
+        nChannels = 1
+      cv_im = cv.CreateImageHeader((a.shape[1],a.shape[0]), 
+              dtype2depth[str(a.dtype)],
+              nChannels)
+      cv.SetData(cv_im, a.tostring(), 
+                 a.dtype.itemsize*nChannels*a.shape[1])
+      return cv_im
+