Merge pull request #1 from ildarkhasanshin/master

* edited comments

ClenchRex.py

@@ -3,42 +3,42 @@
 import math
 import pyautogui
 
+# pass source as 0 (zero) for inbuilt webcam, 1 or -1 for external camera
 cap = cv2.VideoCapture(0)
 
-while (1):
+while (True):
 
     try:
+        # an error comes if it does not find anything in window as it cannot find contour of max area
+        # therefore this try error statement
 
+        # obtain frame and kernel matrix
         ret, frame = cap.read()
         frame = cv2.flip(frame, 1)
         kernel = np.ones((3, 3), np.uint8)
 
-        # defining region of interest
+        # define region of interest
         roi = frame[100:300, 100:300]
 
-        # Making a rectangle around the region of interest
+        # convert to HSV
         cv2.rectangle(frame, (100, 100), (300, 300), (0, 255, 0), 0)
         hsv = cv2.cvtColor(roi, cv2.COLOR_BGR2HSV)
 
-        # defining skin range for HSV
+        # define range of skin color in HSV
         lower_skin = np.array([0, 20, 70], dtype=np.uint8)
         upper_skin = np.array([20, 255, 255], dtype=np.uint8)
 
-        # Green glove skin : Doesn't work
-        #lower_skin = np.array([66, 75, 82], dtype=np.uint8)
-        #upper_skin = np.array([96, 75, 82], dtype=np.uint8)
-
-        # extracting skin color image
+        # extract skin colur image
         mask = cv2.inRange(hsv, lower_skin, upper_skin)
 
-        # Dilating
+        # extrapolate the hand to fill dark spots within
         mask = cv2.dilate(mask, kernel, iterations=4)
 
-        # blurring the image
+        # blur the image
         mask = cv2.GaussianBlur(mask, (5, 5), 100)
 
         # find contours
-        contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
+        _, contours, hierarchy = cv2.findContours(mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
 
         # find contour of max area(hand)
         cnt = max(contours, key=lambda x: cv2.contourArea(x))
@@ -47,7 +47,7 @@
         epsilon = 0.0005 * cv2.arcLength(cnt, True)
         approx = cv2.approxPolyDP(cnt, epsilon, True)
 
-        # making convex hull
+        # make convex hull around hand
         hull = cv2.convexHull(cnt)
 
         # define area of hull and area of hand
@@ -61,10 +61,8 @@
         hull = cv2.convexHull(approx, returnPoints=False)
         defects = cv2.convexityDefects(approx, hull)
 
-        # l = no. of defects
+        # finding number of defects due to fingers (= l)
         l = 0
-
-        # code for finding no. of defects due to fingers
         for i in range(defects.shape[0]):
             s, e, f, d = defects[i, 0]
             start = tuple(approx[s][0])
@@ -85,14 +83,15 @@
             # apply cosine rule here
             angle = math.acos((b ** 2 + c ** 2 - a ** 2) / (2 * b * c)) * 57
 
-            # ignore angles > 90 and ignore points very close to convex hull(they generally come due to noise)
+            # ignore angles > 90 and ignore points very close to convex hull (generally noise induced points)
             if angle <= 90 and d > 30:
                 l += 1
                 cv2.circle(roi, far, 3, [255, 0, 0], -1)
 
             # draw lines around hand
             cv2.line(roi, start, end, [0, 255, 0], 2)
 
+        # minimum one defect for hand
         l += 1
 
         # print corresponding gestures which are in their ranges
@@ -103,22 +102,19 @@
             else:
                 if arearatio < 12:
                     cv2.putText(frame, 'Running', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
-                    #pyautogui.keyDown('down')
-
-
         elif l > 1:
             cv2.putText(frame, 'Jump', (0, 50), font, 2, (0, 0, 255), 3, cv2.LINE_AA)
             pyautogui.press('space')
 
-
         # show the windows
         cv2.imshow('mask', mask)
         cv2.imshow('frame', frame)
+
     except:
         pass
 
-    k = cv2.waitKey(5) & 0xFF
-    if k == 27:
+    if cv2.waitKey(5) & 0xFF == 27:
         break
 
 cv2.destroyAllWindows()
+cap.release()

README.md

@@ -13,6 +13,9 @@ How to play:
 3. Put your clenched fist in the Green Box, and start the game.
 4. Open your fist to Jump, clench back again to stop Jumping. 
 
+Install on Linux:
+
+`pip3 install opencv-python`
 
 References used: 
 https://github.com/Sadaival/Hand-Gestures/blob/master/gesture.py