I am using python-tesseract to extract words from an image. This is a python wrapper for tesseract which is an OCR code.
我使用python-tesseract从图像中提取单词。这是tesseract的python包装器,它是OCR代码。
I am using the following code for getting the words:
我使用以下代码来获取单词:
import tesseract
api = tesseract.TessBaseAPI()
api.Init(".","eng",tesseract.OEM_DEFAULT)
api.SetVariable("tessedit_char_whitelist", "0123456789abcdefghijklmnopqrstuvwxyz")
api.SetPageSegMode(tesseract.PSM_AUTO)
mImgFile = "test.jpg"
mBuffer=open(mImgFile,"rb").read()
result = tesseract.ProcessPagesBuffer(mBuffer,len(mBuffer),api)
print "result(ProcessPagesBuffer)=",result
This returns only the words and not their location/size/orientation (or in other words a bounding box containing them) in the image. I was wondering if there is any way to get that as well
这只返回图像中的单词,而不返回它们的位置/大小/方向(或包含它们的边框)。我想知道是否有什么方法可以达到这个目的
3 个解决方案
#1
11
tesseract.GetBoxText()
method returns the exact position of each character in an array.
getboxtext()方法返回数组中每个字符的确切位置。
Besides, there is a command line option tesseract test.jpg result hocr
that will generate a result.html
file with each recognized word's coordinates in it. But I'm not sure whether it can be called through python script.
此外,还有一个命令行选项tesseract test.jpg result hocr,它将生成一个结果。html文件,其中包含每个可识别单词的坐标。但是我不确定是否可以通过python脚本调用它。
#2
7
Using the below code you can get the bounding box corresponding to each character.
使用下面的代码,您可以得到对应于每个字符的边框。
import csv
import cv2
from pytesseract import pytesseract as pt
pt.run_tesseract('bw.png', 'output', lang=None, boxes=True, config="hocr")
# To read the coordinates
boxes = []
with open('output.box', 'rb') as f:
reader = csv.reader(f, delimiter = ' ')
for row in reader:
if(len(row)==6):
boxes.append(row)
# Draw the bounding box
img = cv2.imread('bw.png')
h, w, _ = img.shape
for b in boxes:
img = cv2.rectangle(img,(int(b[1]),h-int(b[2])),(int(b[3]),h-int(b[4])),(255,0,0),2)
cv2.imshow('output',img)
#3
1
Python tesseract can do this without writing to file, using the image_to_boxes
function:
Python tesseract可以通过使用image_to_boxes函数而不编写文件:
import cv2
import pytesseract
filename = 'image.png'
# read the image and get the dimensions
img = cv2.imread(filename)
h, w, _ = img.shape # assumes color image
# run tesseract, returning the bounding boxes
boxes = pytesseract.image_to_boxes(img) # also include any config options you use
# draw the bounding boxes on the image
for b in boxes.splitlines():
b = b.split(' ')
img = cv2.rectangle(img, (int(b[1]), h - int(b[2])), (int(b[3]), h - int(b[4])), (0, 255, 0), 2)
# show annotated image and wait for keypress
cv2.imshow(filename, img)
cv2.waitKey(0)
#1
11
tesseract.GetBoxText()
method returns the exact position of each character in an array.
getboxtext()方法返回数组中每个字符的确切位置。
Besides, there is a command line option tesseract test.jpg result hocr
that will generate a result.html
file with each recognized word's coordinates in it. But I'm not sure whether it can be called through python script.
此外,还有一个命令行选项tesseract test.jpg result hocr,它将生成一个结果。html文件,其中包含每个可识别单词的坐标。但是我不确定是否可以通过python脚本调用它。
#2
7
Using the below code you can get the bounding box corresponding to each character.
使用下面的代码,您可以得到对应于每个字符的边框。
import csv
import cv2
from pytesseract import pytesseract as pt
pt.run_tesseract('bw.png', 'output', lang=None, boxes=True, config="hocr")
# To read the coordinates
boxes = []
with open('output.box', 'rb') as f:
reader = csv.reader(f, delimiter = ' ')
for row in reader:
if(len(row)==6):
boxes.append(row)
# Draw the bounding box
img = cv2.imread('bw.png')
h, w, _ = img.shape
for b in boxes:
img = cv2.rectangle(img,(int(b[1]),h-int(b[2])),(int(b[3]),h-int(b[4])),(255,0,0),2)
cv2.imshow('output',img)
#3
1
Python tesseract can do this without writing to file, using the image_to_boxes
function:
Python tesseract可以通过使用image_to_boxes函数而不编写文件:
import cv2
import pytesseract
filename = 'image.png'
# read the image and get the dimensions
img = cv2.imread(filename)
h, w, _ = img.shape # assumes color image
# run tesseract, returning the bounding boxes
boxes = pytesseract.image_to_boxes(img) # also include any config options you use
# draw the bounding boxes on the image
for b in boxes.splitlines():
b = b.split(' ')
img = cv2.rectangle(img, (int(b[1]), h - int(b[2])), (int(b[3]), h - int(b[4])), (0, 255, 0), 2)
# show annotated image and wait for keypress
cv2.imshow(filename, img)
cv2.waitKey(0)