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ColorPicker.py
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import cv2
import numpy as np
############################################
cap = cv2.VideoCapture(1)
path = "test.png"
############################################
def empty(a):
pass
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
cv2.namedWindow("TrackBars")
cv2.resizeWindow("TrackBars", 640, 240)
cv2.createTrackbar("Hue Min", "TrackBars", 0, 179, empty)
cv2.createTrackbar("Hue Max", "TrackBars", 179, 179, empty)
cv2.createTrackbar("Sat Min", "TrackBars", 0, 255, empty)
cv2.createTrackbar("Sat Max", "TrackBars", 255, 255, empty)
cv2.createTrackbar("Val Min", "TrackBars", 0, 255, empty)
cv2.createTrackbar("Val Max", "TrackBars", 255, 255, empty)
while True:
# img = cv2.imread(path) #for image
_, img = cap.read() # for Video
imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
h_min = cv2.getTrackbarPos("Hue Min", "TrackBars")
h_max = cv2.getTrackbarPos("Hue Max", "TrackBars")
s_min = cv2.getTrackbarPos("Sat Min", "TrackBars")
s_max = cv2.getTrackbarPos("Sat Max", "TrackBars")
v_min = cv2.getTrackbarPos("Val Min", "TrackBars")
v_max = cv2.getTrackbarPos("Val Max", "TrackBars")
print(f"{h_min},{h_max},{s_min},{s_max},{v_min},{v_max}")
lower = np.array([h_min, s_min, v_min])
upper = np.array([h_max, s_max, v_max])
mask = cv2.inRange(imgHSV, lower, upper)
imgResult = cv2.bitwise_and(img, img, mask=mask)
# cv2.imshow("Original",img)
# cv2.imshow("HSV",imgHSV)
# cv2.imshow("Mask", mask)
# cv2.imshow("Result", imgResult)
imgStack = stackImages(0.6, ([img, imgHSV], [mask, imgResult]))
cv2.imshow("Stacked Images", imgStack)
cv2.waitKey(1)