"atomic bomb" commit. Reorganized OpenCV directory structure

samples/python/watershed.py

@@ -0,0 +1,107 @@
+#!/usr/bin/python
+import urllib2
+import sys
+import cv
+
+class Sketcher:
+    def __init__(self, windowname, dests):
+        self.prev_pt = None
+        self.windowname = windowname
+        self.dests = dests
+        cv.SetMouseCallback(self.windowname, self.on_mouse)
+
+    def on_mouse(self, event, x, y, flags, param):
+        pt = (x, y)
+        if event == cv.CV_EVENT_LBUTTONUP or not (flags & cv.CV_EVENT_FLAG_LBUTTON):
+            self.prev_pt = None
+        elif event == cv.CV_EVENT_LBUTTONDOWN:
+            self.prev_pt = pt
+        elif event == cv.CV_EVENT_MOUSEMOVE and (flags & cv.CV_EVENT_FLAG_LBUTTON) :
+            if self.prev_pt:
+                for dst in self.dests:
+                    cv.Line(dst, self.prev_pt, pt, cv.ScalarAll(255), 5, 8, 0)
+            self.prev_pt = pt
+            cv.ShowImage(self.windowname, img)
+
+if __name__ == "__main__":
+    if len(sys.argv) > 1:
+        img0 = cv.LoadImage( sys.argv[1], cv.CV_LOAD_IMAGE_COLOR)
+    else:
+        url = 'https://code.ros.org/svn/opencv/trunk/opencv/samples/c/fruits.jpg'
+        filedata = urllib2.urlopen(url).read()
+        imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1)
+        cv.SetData(imagefiledata, filedata, len(filedata))
+        img0 = cv.DecodeImage(imagefiledata, cv.CV_LOAD_IMAGE_COLOR)
+
+    rng = cv.RNG(-1)
+
+    print "Hot keys:"
+    print "\tESC - quit the program"
+    print "\tr - restore the original image"
+    print "\tw - run watershed algorithm"
+    print "\t  (before that, roughly outline several markers on the image)"
+
+    cv.NamedWindow("image", 1)
+    cv.NamedWindow("watershed transform", 1)
+
+    img = cv.CloneImage(img0)
+    img_gray = cv.CloneImage(img0)
+    wshed = cv.CloneImage(img0)
+    marker_mask = cv.CreateImage(cv.GetSize(img), 8, 1)
+    markers = cv.CreateImage(cv.GetSize(img), cv.IPL_DEPTH_32S, 1)
+
+    cv.CvtColor(img, marker_mask, cv.CV_BGR2GRAY)
+    cv.CvtColor(marker_mask, img_gray, cv.CV_GRAY2BGR)
+
+    cv.Zero(marker_mask)
+    cv.Zero(wshed)
+
+    cv.ShowImage("image", img)
+    cv.ShowImage("watershed transform", wshed)
+
+    sk = Sketcher("image", [img, marker_mask])
+
+    while True:
+        c = cv.WaitKey(0) % 0x100
+        if c == 27 or c == ord('q'):
+            break
+        if c == ord('r'):
+            cv.Zero(marker_mask)
+            cv.Copy(img0, img)
+            cv.ShowImage("image", img)
+        if c == ord('w'):
+            storage = cv.CreateMemStorage(0)
+            #cv.SaveImage("wshed_mask.png", marker_mask)
+            #marker_mask = cv.LoadImage("wshed_mask.png", 0)
+            contours = cv.FindContours(marker_mask, storage, cv.CV_RETR_CCOMP, cv.CV_CHAIN_APPROX_SIMPLE)
+            def contour_iterator(contour):
+                while contour:
+                    yield contour
+                    contour = contour.h_next()
+
+            cv.Zero(markers)
+            comp_count = 0
+            for c in contour_iterator(contours):
+                cv.DrawContours(markers,
+                                c,
+                                cv.ScalarAll(comp_count + 1),
+                                cv.ScalarAll(comp_count + 1),
+                                -1,
+                                -1,
+                                8)
+                comp_count += 1
+
+            cv.Watershed(img0, markers)
+
+            cv.Set(wshed, cv.ScalarAll(255))
+
+            # paint the watershed image
+            color_tab = [(cv.RandInt(rng) % 180 + 50, cv.RandInt(rng) % 180 + 50, cv.RandInt(rng) % 180 + 50) for i in range(comp_count)]
+            for j in range(markers.height):
+                for i in range(markers.width):
+                    idx = markers[j, i]
+                    if idx != -1:
+                        wshed[j, i] = color_tab[int(idx - 1)]
+
+            cv.AddWeighted(wshed, 0.5, img_gray, 0.5, 0, wshed)
+            cv.ShowImage("watershed transform", wshed)