def DocScanner():
global widthImg
global heightImg
widthImg = 540
heightImg = 640
cap = cv2.VideoCapture(0)
cap.set(3, widthImg) # setting width
cap.set(4, heightImg) # setting height
cap.set(10, 150) # set brightness
while True:
_, img = cap.read()
if img is None:
continue
cv2.resize(img, (widthImg, heightImg))
imgContour = img.copy()
imgThres = preProcessing(img)
biggest = getContours(imgThres, imgContour)
if biggest.size != 0:
imgWarped = getWarp(img, biggest)
# imageArray = ([img,imgThres],
# [imgContour,imgWarped])
imageArray = ([imgContour, imgWarped])
cv2.imshow("ImageWarped", imgWarped)
else:
# imageArray = ([img, imgThres],
# [img, img])
imageArray = ([imgContour, img])
stackedImages = stackImages(0.6, imageArray)
cv2.imshow("WorkFlow", stackedImages)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
def detect_color(path):
# add track bar
def empty(x):
pass
cv2.namedWindow('TrackBar')
cv2.resizeWindow('TrackBar', 640, 240)
cv2.createTrackbar('Hue min', 'TrackBar', 0, 179, empty)
cv2.createTrackbar('Hue max', 'TrackBar', 179, 179, empty)
cv2.createTrackbar('Saturation min', 'TrackBar', 0, 255, empty)
cv2.createTrackbar('Saturation max', 'TrackBar', 255, 255, empty)
cv2.createTrackbar('Val min', 'TrackBar', 0, 255, empty)
cv2.createTrackbar('Val max', 'TrackBar', 255, 255, empty)
while True:
img = cv2.imread(path)
imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
# get the values from track bar
h_min = cv2.getTrackbarPos('Hue min', 'TrackBar')
h_max = cv2.getTrackbarPos('Hue max', 'TrackBar')
s_min = cv2.getTrackbarPos('Saturation min', 'TrackBar')
s_max = cv2.getTrackbarPos('Saturation max', 'TrackBar')
v_min = cv2.getTrackbarPos('Val min', 'TrackBar')
v_max = cv2.getTrackbarPos('Val max', 'TrackBar')
lower = np.array([h_min, s_min, v_min])
upper = np.array([h_max, s_max, v_max])
mask = cv2.inRange(imgHSV, lower, upper)
imgMasked = cv2.bitwise_and(img, img, mask=mask)
# cv2.imshow('Original image', img)
# cv2.imshow('HSV image', imgHSV)
# cv2.imshow('Mask image', mask)
# cv2.imshow('Masked image', imgMasked)
imgStack = stackImages(0.6, ([img, imgHSV], [mask, imgMasked]))
cv2.imshow('Stacked Images', imgStack)
cv2.waitKey(1)
def shape_contour(path):
img = cv2.imread(path)
imgContour = img.copy()
imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # convert to gray scale
imgBlur = cv2.GaussianBlur(imgGray, (5, 5), 1) # blur image
imgCanny = cv2.Canny(img, 50, 50) # detecting edges
imgBlank = np.zeros_like(img)
getContours(imgCanny, imgContour)
# cv2.imshow('Original Imge', img)
# cv2.imshow('Gray Imge', imgGray)
# cv2.imshow('Blur Imge', imgBlur)
imgStack = stackImages(
0.6, ([img, imgGray, imgBlur], [imgCanny, imgContour, imgBlank]))
cv2.imshow('Stacked Images', imgStack)
cv2.waitKey(0)
# shape_contour(path2)
elif ver > 4: o_type = "circle"
else: o_type = "nonetype"
cv.putText(res_img,
o_type,
(x+(w//2)-10,y+(h//2)-10),
cv.FONT_HERSHEY_COMPLEX,
0.7,
(0,0,240),
1)
path = "resources/shapes.jpg"
image = cv.imread(path)
image = zeroPadding(image)
res_img = image.copy()
binary = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
blur = cv.GaussianBlur(binary, (7, 7), 1.5)
canny = cv.Canny(blur, 150, 200)
getContour(canny)
stc_image = stackImages(1, [image, res_img])
cv.imshow("winname", stc_image)
cv.waitKey(0)
import cv2
import numpy as np
from helper import stackImages
#WARP PERSPECTIVE EXAMPLE
image = cv2.imread("resources/card.jpg")
width = 200
height = 300
source = np.float32([[668, 722], [1819, 22], [2035, 2173], [3203, 1304]])
dst = np.float32([[0, 0], [width, 0], [0, height], [width, height]])
p_matrix = cv2.getPerspectiveTransform(source, dst)
output = cv2.warpPerspective(image, p_matrix, (width, height))
s_img = stackImages(2, [output, image])
cv2.imshow("stack image", s_img)
cv2.waitKey(0)
cv2.createTrackbar("min_sat", "Trackbars", 0, 255, empty)
cv2.createTrackbar("max_sat", "Trackbars", 100, 255, empty)
cv2.createTrackbar("min_val", "Trackbars", 0, 255, empty)
cv2.createTrackbar("max_val", "Trackbars", 110, 255, empty)
cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)
while True:
# image = cv2.imread("resources/shapes.jpg")
# image = cv2.resize(image, (620, 480))
ret, image = cap.read()
img_hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
h_min = cv2.getTrackbarPos("min_hue", "Trackbars")
h_max = cv2.getTrackbarPos("max_hue", "Trackbars")
s_min = cv2.getTrackbarPos("min_sat", "Trackbars")
s_max = cv2.getTrackbarPos("max_sat", "Trackbars")
v_min = cv2.getTrackbarPos("min_val", "Trackbars")
v_max = cv2.getTrackbarPos("max_val", "Trackbars")
lower = np.array([h_min, s_min, v_min])
upper = np.array([h_max, s_max, v_max])
print(lower)
print(upper)
mask = cv2.inRange(img_hsv, lower, upper)
img_res = cv2.bitwise_and(image, image, mask=mask)
stacked_images = stackImages(0.5, ([mask, img_res], [image, img_hsv]))
cv2.imshow("res", stacked_images)
cv2.waitKey(1)