#!/usr/bin/env python

# Derived from http://sundararajana.blogspot.com/2007/05/motion-detection-using-opencv.html

import cv
import time

class Target:
    def __init__(self):
        self.capture = cv.CaptureFromCAM(0)
        cv.NamedWindow("Target", 1)

    def run(self):
        # Capture first frame to get size
        frame = cv.QueryFrame(self.capture)
        frame_size = cv.GetSize(frame)
        grey_image = cv.CreateImage(cv.GetSize(frame), cv.IPL_DEPTH_8U, 1)
        moving_average = cv.CreateImage(cv.GetSize(frame), cv.IPL_DEPTH_32F, 3)
        difference = None
        
        while True:
            #time.sleep(0.2)
            # Capture frame from webcam
            color_image = cv.QueryFrame(self.capture)
            
            # Smooth to get rid of false positives
            cv.Smooth(color_image, color_image, cv.CV_GAUSSIAN, 3, 0)
            
            if not difference:
                # Initialize
                difference = cv.CloneImage(color_image)
                temp = cv.CloneImage(color_image)
                cv.ConvertScale(color_image, moving_average, 1.0, 0.0)
            else:
                cv.RunningAvg(color_image, moving_average, 0.020, None)
            
            # Convert the scale of the moving average.
            cv.ConvertScale(moving_average, temp, 1.0, 0.0)
            
            # Minus the current frame from the moving average.
            cv.AbsDiff(color_image, temp, difference)
            
            # Convert the image to grayscale.
            cv.CvtColor(difference, grey_image, cv.CV_RGB2GRAY)
            
            # Convert the image to black and white.
            cv.Threshold(grey_image, grey_image, 70, 255, cv.CV_THRESH_BINARY)
            
            # Dilate and erode to get object blobs
            cv.Dilate(grey_image, grey_image, None, 18)
            cv.Erode(grey_image, grey_image, None, 10)
            
            # Calculate movements
            storage = cv.CreateMemStorage(0)
            contour = cv.FindContours(grey_image, storage, cv.CV_RETR_CCOMP, cv.CV_CHAIN_APPROX_SIMPLE)
            points = []
            
            while contour:
                # Draw rectangles
                bound_rect = cv.BoundingRect(list(contour))
                contour = contour.h_next()
                
                pt1 = (bound_rect[0], bound_rect[1])
                pt2 = (bound_rect[0] + bound_rect[2], bound_rect[1] + bound_rect[3])
                points.append(pt1)
                points.append(pt2)
                cv.Rectangle(color_image, pt1, pt2, cv.CV_RGB(255,0,0), 1)
                
            num_points = len(points)
            """
            if num_points:
                # Draw bullseye in midpoint of all movements
                x = y = 0
                for point in points:
                    x += point[0]
                    y += point[1]
                x /= num_points
                y /= num_points
                center_point = (x, y)
                cv.Circle(color_image, center_point, 40, cv.CV_RGB(255, 255, 255), 1)
                cv.Circle(color_image, center_point, 30, cv.CV_RGB(255, 100, 0), 1)
                cv.Circle(color_image, center_point, 20, cv.CV_RGB(255, 255, 255), 1)
                cv.Circle(color_image, center_point, 10, cv.CV_RGB(255, 100, 0), 5)
            """
            # Display frame to user
            cv.ShowImage("Target", color_image)
            
            # Listen for ESC or ENTER key
            c = cv.WaitKey(7) % 0x100
            if c == 27 or c == 10:
                break

if __name__=="__main__":
    t = Target()
    t.run()
