1. Project display
Test result comparison chart
Crop the selected area.
Open our generated .csv file
2. Project introduction
Suppose we already have a text-highlighted image, and we want to extract the text so that we can quickly find the key points and store the content in a .csv file.
3. Project construction
For unknown reasons, my tesseract had a problem, and I downloaded it again later, you can go here
Download, I also used this in the previous project, you can check my project 1: (4 messages) Opencv project combat: 01 Text detection OCR (1)_Summer is the blog of iced tea - CSDN Blog
as well as
OK! Today's project is very simple, just calling some functions that have been written before.
4. Display and explain the project code
This code, which I have talked about before, can be found in my previous actual combat.
utlis.py
import cv2
import numpy as np
def detectColor(img, hsv):
imgHSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
# cv2.imshow("hsv",imgHSV)
lower = np.array([hsv[0], hsv[2], hsv[4]])
upper = np.array([hsv[1], hsv[3], hsv[5]])
mask = cv2.inRange(imgHSV, lower, upper)
# cv2.imshow("mask", mask)
imgResult = cv2.bitwise_and(img, img, mask=mask)
# cv2.imshow("imgResult", imgResult)
return imgResult
def getContours(img, imgDraw, cThr=[100, 100], showCanny=False, minArea=1000, filter=0, draw=False):
imgDraw = imgDraw.copy()
imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
imgBlur = cv2.GaussianBlur(imgGray, (5, 5), 1)
imgCanny = cv2.Canny(imgBlur, cThr[0], cThr[1])
kernel = np.array((10, 10))
imgDial = cv2.dilate(imgCanny, kernel, iterations=1)
imgClose = cv2.morphologyEx(imgDial, cv2.MORPH_CLOSE, kernel)
if showCanny: cv2.imshow('Canny', imgClose)
contours, hiearchy = cv2.findContours(imgClose, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
finalCountours = []
for i in contours:
area = cv2.contourArea(i)
if area > minArea:
peri = cv2.arcLength(i, True)
approx = cv2.approxPolyDP(i, 0.02 * peri, True)
bbox = cv2.boundingRect(approx)
if filter > 0:
if len(approx) == filter:
finalCountours.append([len(approx), area, approx, bbox, i])
else:
finalCountours.append([len(approx), area, approx, bbox, i])
finalCountours = sorted(finalCountours, key=lambda x: x[1], reverse=True)
if draw:
for con in finalCountours:
x, y, w, h = con[3]
cv2.rectangle(imgDraw, (x, y), (x + w, y + h), (255, 0, 255), 3)
# cv2.drawContours(imgDraw,con[4],-1,(0,0,255),2)
return imgDraw, finalCountours
def getRoi(img, contours):
roiList = []
for con in contours:
x, y, w, h = con[3]
roiList.append(img[y:y + h, x:x + w])
return roiList
def roiDisplay(roiList):
for x, roi in enumerate(roiList):
roi = cv2.resize(roi, (0, 0), None, 2, 2)
cv2.imshow(str(x),roi)
def saveText(highlightedText):
with open('HighlightedText.csv', 'w') as f:
for text in highlightedText:
f.writelines(f'\n{text}')
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 verIn the last actual combat project, I also used this track bar, and I don't talk much about it.
color.py
import cv2
import numpy as np
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
path = 'test.png'
cv2.namedWindow("TrackBars")
cv2.resizeWindow("TrackBars",640,240)
cv2.createTrackbar("Hue Min","TrackBars",0,179,empty)
cv2.createTrackbar("Hue Max","TrackBars",19,179,empty)
cv2.createTrackbar("Sat Min","TrackBars",110,255,empty)
cv2.createTrackbar("Sat Max","TrackBars",240,255,empty)
cv2.createTrackbar("Val Min","TrackBars",153,255,empty)
cv2.createTrackbar("Val Max","TrackBars",255,255,empty)
while True:
img = cv2.imread(path)
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(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(0.3,([img,imgHSV],[mask,imgResult]))
cv2.imshow("Stacked Images", imgStack)
if cv2.waitKey(1) & 0XFF == 27:
breakour main function
main.py
from utlis import *
import pytesseract
path = 'test.png'
hsv = [0, 65, 59, 255, 0, 255]
pytesseract.pytesseract.tesseract_cmd = 'E:\pythonProject\Github/tesseract-ocr//tesseract.exe'
#### Step 1 ####
img = cv2.imread(path)
# cv2.imshow("Original",img)
#### Step 2 ####
imgResult = detectColor(img, hsv)
#### Step 3 & 4 ####
imgContours, contours = getContours(imgResult, img, showCanny=True,
minArea=1000, filter=4,
cThr=[100, 150], draw=True)
cv2.imshow("imgContours",imgContours)
print(len(contours))
#### Step 5 ####
roiList = getRoi(img, contours)
# cv2.imshow("TestCrop",roiList[2])
roiDisplay(roiList)
#### Step 6 ####
highlightedText = []
for x, roi in enumerate(roiList):
# print(pytesseract.image_to_string(roi))
print(pytesseract.image_to_string(roi))
highlightedText.append(pytesseract.image_to_string(roi))
if cv2.waitKey(1) & 0xFF == 27:
break
saveText(highlightedText)
imgStack = stackImages(0.6, ([img, imgResult, imgContours]))
cv2.imshow("Stacked Images", imgStack)
Well, I feel that this project is really not difficult, so be it.
5. Project resources
6. Project summary
As you can see, in the .csv file we generated, the content is not complete. I suspect that it is still the problem of tesseract. I have complained about it in previous projects. Let's print the content.
There are a total of seven highlighted texts, which are correct, and should still be a problem that it cannot recognize by itself.
PS: One more thing, in order to better promote my column, I will do a quick entry level opencv series, please stay tuned!
Well, hope you have fun with this project, otherwise I'll see you in the next project! !
