rename samples/{python2 -> python}

samples/python/camshift.py

@@ -0,0 +1,134 @@
+#!/usr/bin/env python
+
+'''
+Camshift tracker
+================
+
+This is a demo that shows mean-shift based tracking
+You select a color objects such as your face and it tracks it.
+This reads from video camera (0 by default, or the camera number the user enters)
+
+http://www.robinhewitt.com/research/track/camshift.html
+
+Usage:
+------
+    camshift.py [<video source>]
+
+    To initialize tracking, select the object with mouse
+
+Keys:
+-----
+    ESC   - exit
+    b     - toggle back-projected probability visualization
+'''
+
+# Python 2/3 compatibility
+from __future__ import print_function
+import sys
+PY3 = sys.version_info[0] == 3
+
+if PY3:
+    xrange = range
+
+import numpy as np
+import cv2
+
+# local module
+import video
+
+
+class App(object):
+    def __init__(self, video_src):
+        self.cam = video.create_capture(video_src)
+        ret, self.frame = self.cam.read()
+        cv2.namedWindow('camshift')
+        cv2.setMouseCallback('camshift', self.onmouse)
+
+        self.selection = None
+        self.drag_start = None
+        self.tracking_state = 0
+        self.show_backproj = False
+
+    def onmouse(self, event, x, y, flags, param):
+        x, y = np.int16([x, y]) # BUG
+        if event == cv2.EVENT_LBUTTONDOWN:
+            self.drag_start = (x, y)
+            self.tracking_state = 0
+            return
+        if self.drag_start:
+            if flags & cv2.EVENT_FLAG_LBUTTON:
+                h, w = self.frame.shape[:2]
+                xo, yo = self.drag_start
+                x0, y0 = np.maximum(0, np.minimum([xo, yo], [x, y]))
+                x1, y1 = np.minimum([w, h], np.maximum([xo, yo], [x, y]))
+                self.selection = None
+                if x1-x0 > 0 and y1-y0 > 0:
+                    self.selection = (x0, y0, x1, y1)
+            else:
+                self.drag_start = None
+                if self.selection is not None:
+                    self.tracking_state = 1
+
+    def show_hist(self):
+        bin_count = self.hist.shape[0]
+        bin_w = 24
+        img = np.zeros((256, bin_count*bin_w, 3), np.uint8)
+        for i in xrange(bin_count):
+            h = int(self.hist[i])
+            cv2.rectangle(img, (i*bin_w+2, 255), ((i+1)*bin_w-2, 255-h), (int(180.0*i/bin_count), 255, 255), -1)
+        img = cv2.cvtColor(img, cv2.COLOR_HSV2BGR)
+        cv2.imshow('hist', img)
+
+    def run(self):
+        while True:
+            ret, self.frame = self.cam.read()
+            vis = self.frame.copy()
+            hsv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2HSV)
+            mask = cv2.inRange(hsv, np.array((0., 60., 32.)), np.array((180., 255., 255.)))
+
+            if self.selection:
+                x0, y0, x1, y1 = self.selection
+                self.track_window = (x0, y0, x1-x0, y1-y0)
+                hsv_roi = hsv[y0:y1, x0:x1]
+                mask_roi = mask[y0:y1, x0:x1]
+                hist = cv2.calcHist( [hsv_roi], [0], mask_roi, [16], [0, 180] )
+                cv2.normalize(hist, hist, 0, 255, cv2.NORM_MINMAX)
+                self.hist = hist.reshape(-1)
+                self.show_hist()
+
+                vis_roi = vis[y0:y1, x0:x1]
+                cv2.bitwise_not(vis_roi, vis_roi)
+                vis[mask == 0] = 0
+
+            if self.tracking_state == 1:
+                self.selection = None
+                prob = cv2.calcBackProject([hsv], [0], self.hist, [0, 180], 1)
+                prob &= mask
+                term_crit = ( cv2.TERM_CRITERIA_EPS | cv2.TERM_CRITERIA_COUNT, 10, 1 )
+                track_box, self.track_window = cv2.CamShift(prob, self.track_window, term_crit)
+
+                if self.show_backproj:
+                    vis[:] = prob[...,np.newaxis]
+                try:
+                    cv2.ellipse(vis, track_box, (0, 0, 255), 2)
+                except:
+                    print(track_box)
+
+            cv2.imshow('camshift', vis)
+
+            ch = 0xFF & cv2.waitKey(5)
+            if ch == 27:
+                break
+            if ch == ord('b'):
+                self.show_backproj = not self.show_backproj
+        cv2.destroyAllWindows()
+
+
+if __name__ == '__main__':
+    import sys
+    try:
+        video_src = sys.argv[1]
+    except:
+        video_src = 0
+    print(__doc__)
+    App(video_src).run()