Getting the bounding box of the recognized words using python-tesseract

Use pytesseract.image_to_data()

import pytesseract
from pytesseract import Output
import cv2
img = cv2.imread('image.jpg')

d = pytesseract.image_to_data(img, output_type=Output.DICT)
n_boxes = len(d['level'])
for i in range(n_boxes):
    (x, y, w, h) = (d['left'][i], d['top'][i], d['width'][i], d['height'][i])
    cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)

cv2.imshow('img', img)
cv2.waitKey(0)

Among the data returned by pytesseract.image_to_data():

• left is the distance from the upper-left corner of the bounding box, to the left border of the image.
• top is the distance from the upper-left corner of the bounding box, to the top border of the image.
• width and height are the width and height of the bounding box.
• conf is the model's confidence for the prediction for the word within that bounding box. If conf is -1, that means that the corresponding bounding box contains a block of text, rather than just a single word.

The bounding boxes returned by pytesseract.image_to_boxes() enclose letters so I believe pytesseract.image_to_data() is what you're looking for.

Python tesseract can do this without writing to file, using the image_to_boxes function:

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)

Would comment under lennon310 but don't have enough reputation to comment...

To run his command line command tesseract test.jpg result hocr in a python script:

from subprocess import check_call

tesseractParams = ['tesseract', 'test.jpg', 'result', 'hocr']
check_call(tesseractParams)

To get bounding boxes over words:

import cv2
import pytesseract
img = cv2.imread('/home/gautam/Desktop/python/ocr/SEAGATE/SEAGATE-01.jpg')

from pytesseract import Output
d = pytesseract.image_to_data(img, output_type=Output.DICT)
n_boxes = len(d['level'])
for i in range(n_boxes):
    if(d['text'][i] != ""):
        (x, y, w, h) = (d['left'][i], d['top'][i], d['width'][i], d['height'][i])
        cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)

cv2.imwrite('result.png', img)

Some examples are answered aove which can be used with pytesseract, however to use tesserocr python library you can use code given below to find individual word and their bounding boxes:-

    with PyTessBaseAPI(psm=6, oem=1) as api:
            level = RIL.WORD
            api.SetImageFile(imagePath)
            api.Recognize()
            ri = api.GetIterator()
            while True::
                word = ri.GetUTF8Text(level)
                boxes = ri.BoundingBox(level)
                print(word,"word")
                print(boxes,"coords")
                if not ri.Next(level):
                     break

As already mentioned, you can use pytesseract's image_to_boxes. You can check my Docker Hub repo https://hub.docker.com/r/milanhlinak/tesseract-image-to-boxes - a simple Flask application with Tesseract 5.0.0.