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utlis.py
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utlis.py
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import serial
import numpy as np
import cv2
import math
global ser
def empty(a):
pass
def initializeTrackBar():
cv2.namedWindow("HSV Value")
cv2.resizeWindow("HSV Value", 640, 240)
cv2.createTrackbar("HUE MIN", "HSV Value", 0, 179, empty)
cv2.createTrackbar("HUE MAX", "HSV Value", 26, 179, empty)
cv2.createTrackbar("SAT MIN", "HSV Value", 50, 255, empty)
cv2.createTrackbar("SAT MAX", "HSV Value", 255, 255, empty)
cv2.createTrackbar("VALUE MIN", "HSV Value", 0, 255, empty)
cv2.createTrackbar("VALUE MAX", "HSV Value", 255, 255, empty)
def getTrackbarValues():
h_min = cv2.getTrackbarPos("HUE MIN", "HSV Value")
h_max = cv2.getTrackbarPos("HUE MAX", "HSV Value")
s_min = cv2.getTrackbarPos("SAT MIN", "HSV Value")
s_max = cv2.getTrackbarPos("SAT MAX", "HSV Value")
v_min = cv2.getTrackbarPos("VALUE MIN", "HSV Value")
v_max = cv2.getTrackbarPos("VALUE MAX", "HSV Value")
vals = h_min, s_min, v_min, h_max, s_max, v_max
return vals
def connectToRobot(portNo):
global ser
try:
ser = serial.Serial(portNo, 9600)
print("Robot Connected ")
except:
print("Not Connected To Robot ")
pass
def colorFilter(img, vals):
lower_blue = np.array([vals[0], vals[1], vals[2]])
upper_blue = np.array([vals[3], vals[4], vals[5]])
mask = cv2.inRange(img, lower_blue, upper_blue)
imgColorFilter = cv2.bitwise_and(img, img, mask=mask)
ret, imgMask = cv2.threshold(mask, 127, 255, 0)
return imgMask, imgColorFilter
def sendData(fingers):
string = "$" + str(int(fingers[0])) + str(int(fingers[1])) + str(int(fingers[2])) + str(int(fingers[3])) + str(
int(fingers[4]))
try:
ser.write(string.encode())
print(string)
except:
pass
def getContours(imgCon, imgMatch):
contours, hierarchy = cv2.findContours(imgCon, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
imgCon = cv2.cvtColor(imgCon, cv2.COLOR_GRAY2BGR)
bigCon = 0
myCounter = 0
myPos = np.zeros(4)
for cnt in contours:
area = cv2.contourArea(cnt)
if (area > 1000):
cv2.drawContours(imgCon, cnt, -1, (255, 0, 255), 3)
cv2.drawContours(imgMatch, cnt, -1, (255, 0, 255), 3)
peri = cv2.arcLength(cnt, True)
approx = cv2.approxPolyDP(cnt, 0.02 * peri, True)
# APPROXIMATED BOUNDING BOX
x, y, w, h = cv2.boundingRect(approx)
ex = 10
cv2.rectangle(imgCon, (x - ex, y - ex), (x + w + ex, y + h + ex), (0, 255, 0), 5);
# CONVEX HULL & CONVEXITY DEFECTS OF THE HULL
hull = cv2.convexHull(cnt, returnPoints=False)
defects = cv2.convexityDefects(cnt, hull)
bigCon += 1
for i in range(defects.shape[0]): # calculate the angle
s, e, f, d = defects[i][0]
start = tuple(cnt[s][0])
end = tuple(cnt[e][0])
far = tuple(cnt[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 // 1.7: # angle less than degree, treat as fingers
myPos[myCounter] = far[0]
myCounter += 1
cv2.circle(imgCon, far, 5, [0, 255, 0], -1)
cv2.circle(imgMatch, far, 5, [0, 255, 0], -1)
## SENDING COMMANDS BASED ON FINGERS
if (myCounter == 4):
sendData([1, 1, 1, 1, 1]);FingerCount = "Five"
elif (myCounter == 3):
sendData([1, 1, 1, 1, 0]);FingerCount = "Four"
elif (myCounter == 2):
sendData([0, 1, 1, 1, 0]);FingerCount = "Three"
elif (myCounter == 1):
sendData([0, 0, 1, 1, 0]);FingerCount = "Two"
elif (myCounter == 0):
aspectRatio = w / h
if aspectRatio < 0.6:
sendData([0, 0, 0, 1, 0]);
FingerCount = "One"
else:
sendData([0, 0, 0, 0, 0]);FingerCount = "Zero"
cv2.putText(imgMatch, FingerCount, (50, 50), cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 255), 2)
return imgCon, imgMatch
def stackImages(scale, imgArray):
rows = len(imgArray)
cols = len(imgArray[0])
rowsAvailable = isinstance(imgArray[0], list)
width = imgArray[0][0].shape[1]
height = imgArray[0][0].shape[0]
if rowsAvailable:
for x in range(0, rows):
for y in range(0, cols):
if imgArray[x][y].shape[:2] == imgArray[0][0].shape[:2]:
imgArray[x][y] = cv2.resize(imgArray[x][y], (0, 0), None, scale, scale)
else:
imgArray[x][y] = cv2.resize(imgArray[x][y], (imgArray[0][0].shape[1], imgArray[0][0].shape[0]),
None, scale, scale)
if len(imgArray[x][y].shape) == 2: imgArray[x][y] = cv2.cvtColor(imgArray[x][y], cv2.COLOR_GRAY2BGR)
imageBlank = np.zeros((height, width, 3), np.uint8)
hor = [imageBlank] * rows
hor_con = [imageBlank] * rows
for x in range(0, rows):
hor[x] = np.hstack(imgArray[x])
ver = np.vstack(hor)
else:
for x in range(0, rows):
if imgArray[x].shape[:2] == imgArray[0].shape[:2]:
imgArray[x] = cv2.resize(imgArray[x], (0, 0), None, scale, scale)
else:
imgArray[x] = cv2.resize(imgArray[x], (imgArray[0].shape[1], imgArray[0].shape[0]), None, scale, scale)
if len(imgArray[x].shape) == 2: imgArray[x] = cv2.cvtColor(imgArray[x], cv2.COLOR_GRAY2BGR)
hor = np.hstack(imgArray)
ver = hor
return ver