init

Author: lzane

new.py

@@ -0,0 +1,135 @@
+import cv2
+import numpy as np
+import copy
+import math
+from appscript import app
+
+# Environment:
+# OS    : Mac OS EL Capitan
+# python: 3.5
+# opencv: 2.4.13
+
+# parameters
+cap_region_x_begin=0.5  # start point/total width
+cap_region_y_end=0.8  # start point/total width
+threshold = 60  #  BINARY threshold
+blurValue = 41  # GaussianBlur parameter
+bgSubThreshold = 50
+
+# variables
+isBgCaptured = 0   # bool, whether the background captured
+triggerSwitch = False  # if true, keyborad simulator works
+
+def printThreshold(thr):
+    print("! Changed threshold to "+str(thr))
+
+
+def removeBG(frame):
+    fgmask = bgModel.apply(frame)
+    # kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
+    # res = cv2.morphologyEx(fgmask, cv2.MORPH_OPEN, kernel)
+
+    kernel = np.ones((3, 3), np.uint8)
+    fgmask = cv2.erode(fgmask, kernel, iterations=1)
+    res = cv2.bitwise_and(frame, frame, mask=fgmask)
+    return res
+
+
+def calculateFingers(res,drawing):  # -> finished bool, cnt: finger count
+    #  convexity defect
+    hull = cv2.convexHull(res, returnPoints=False)
+    if len(hull) > 3:
+        defects = cv2.convexityDefects(res, hull)
+        if type(defects) != type(None):  # avoid crashing.   (BUG not found)
+
+            cnt = 0
+            for i in range(defects.shape[0]):  # calculate the angle
+                s, e, f, d = defects[i][0]
+                start = tuple(res[s][0])
+                end = tuple(res[e][0])
+                far = tuple(res[f][0])
+                a = math.sqrt((end[0] - start[0]) ** 2 + (end[1] - start[1]) ** 2)
+                b = math.sqrt((far[0] - start[0]) ** 2 + (far[1] - start[1]) ** 2)
+                c = math.sqrt((end[0] - far[0]) ** 2 + (end[1] - far[1]) ** 2)
+                angle = math.acos((b ** 2 + c ** 2 - a ** 2) / (2 * b * c))  # cosine theorem
+                if angle <= math.pi / 2:  # angle less than 90 degree, treat as fingers
+                    cnt += 1
+                    cv2.circle(drawing, far, 8, [211, 84, 0], -1)
+            return True, cnt
+    return False, 0
+
+
+# Camera
+camera = cv2.VideoCapture(0)
+camera.set(10,200)
+cv2.namedWindow('trackbar')
+cv2.createTrackbar('trh1', 'trackbar', threshold, 100, printThreshold)
+
+
+while camera.isOpened():
+    ret, frame = camera.read()
+    threshold = cv2.getTrackbarPos('trh1', 'trackbar')
+    frame = cv2.bilateralFilter(frame, 5, 50, 100)  # smoothing filter
+    frame = cv2.flip(frame, 1)  # flip the frame horizontally
+    cv2.rectangle(frame, (int(cap_region_x_begin * frame.shape[1]), 0),
+                 (frame.shape[1], int(cap_region_y_end * frame.shape[0])), (255, 0, 0), 2)
+    cv2.imshow('original', frame)
+
+    #  Main operation
+    if isBgCaptured == 1:  # this part wont run until background captured
+        img = removeBG(frame)
+        img = img[0:int(cap_region_y_end * frame.shape[0]),
+                    int(cap_region_x_begin * frame.shape[1]):frame.shape[1]]  # clip the ROI
+        cv2.imshow('mask', img)
+
+        # convert the image into binary image
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
+        blur = cv2.GaussianBlur(gray, (blurValue, blurValue), 0)
+        cv2.imshow('blur', blur)
+        ret, thresh = cv2.threshold(blur, threshold, 255, cv2.THRESH_BINARY)
+        cv2.imshow('ori', thresh)
+
+
+        # get the coutours
+        thresh1 = copy.deepcopy(thresh)
+        contours, hierarchy = cv2.findContours(thresh1, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+        length = len(contours)
+        maxArea = -1
+        if length > 0:
+            for i in range(length):  # find the biggest contour (according to area)
+                temp = contours[i]
+                area = cv2.contourArea(temp)
+                if area > maxArea:
+                    maxArea = area
+                    ci = i
+
+            res = contours[ci]
+            hull = cv2.convexHull(res)
+            drawing = np.zeros(img.shape, np.uint8)
+            cv2.drawContours(drawing, [res], 0, (0, 255, 0), 2)
+            cv2.drawContours(drawing, [hull], 0, (0, 0, 255), 3)
+
+            isFinishCal,cnt = calculateFingers(res,drawing)
+            if triggerSwitch is True:
+                if isFinishCal is True and cnt <= 2:
+                    print cnt
+                    app('System Events').keystroke(' ')  # simulate pressing blank space
+
+        cv2.imshow('output', drawing)
+
+    # Keyboard OP
+    k = cv2.waitKey(10)
+    if k == 27:  # press ESC to exit
+        break
+    elif k == ord('b'):  # press 'b' to capture the background
+        bgModel = cv2.BackgroundSubtractorMOG2(0, bgSubThreshold)
+        isBgCaptured = 1
+        print '!!!Background Captured!!!'
+    elif k == ord('r'):  # press 'r' to reset the background
+        bgModel = None
+        triggerSwitch = False
+        isBgCaptured = 0
+        print '!!!Reset BackGround!!!'
+    elif k == ord('n'):
+        triggerSwitch = True
+        print '!!!Trigger On!!!'