extracting_text.py
import pytesseract
import cv2
import matplotlib.pyplot as plt
import sys
from PIL import Image
# read the image using OpenCV
# from the command line first argument
image = cv2.imread(sys.argv[1])
# or you can use Pillow
# image = Image.open(sys.argv[1])
# get the string
string = pytesseract.image_to_string(image)
# print it
print(string)
# get all data
data = pytesseract.image_to_data(image)
print(data)
draw_boxes.py
import pytesseract
import cv2
import matplotlib.pyplot as plt
from PIL import Image
# read the image using OpenCV
image = cv2.imread("test.png")
# make a copy of this image to draw in
image_copy = image.copy()
# the target word to search for
target_word = "dog"
# get all data from the image
data = pytesseract.image_to_data(image, output_type=pytesseract.Output.DICT)
# get all occurences of the that word
word_occurences = [ i for i, word in enumerate(data["text"]) if word == target_word ]
for occ in word_occurences:
# extract the width, height, top and left position for that detected word
w = data["width"][occ]
h = data["height"][occ]
l = data["left"][occ]
t = data["top"][occ]
# define all the surrounding box points
p1 = (l, t)
p2 = (l + w, t)
p3 = (l + w, t + h)
p4 = (l, t + h)
# draw the 4 lines (rectangular)
image_copy = cv2.line(image_copy, p1, p2, color=(255, 0, 0), thickness=2)
image_copy = cv2.line(image_copy, p2, p3, color=(255, 0, 0), thickness=2)
image_copy = cv2.line(image_copy, p3, p4, color=(255, 0, 0), thickness=2)
image_copy = cv2.line(image_copy, p4, p1, color=(255, 0, 0), thickness=2)
plt.imsave("all_dog_words.png", image_copy)
plt.imshow(image_copy)
plt.show()
live_recognizer.py (using cam)
import pytesseract
import cv2
import matplotlib.pyplot as plt
from PIL import Image
# the target word to search for
target_word = "your"
cap = cv2.VideoCapture(0)
while True:
# read the image from the cam
_, image = cap.read()
# make a copy of this image to draw in
image_copy = image.copy()
# get all data from the image
data = pytesseract.image_to_data(image, output_type=pytesseract.Output.DICT)
# print the data
print(data["text"])
# get all occurences of the that word
word_occurences = [ i for i, word in enumerate(data["text"]) if word.lower() == target_word ]
for occ in word_occurences:
# extract the width, height, top and left position for that detected word
w = data["width"][occ]
h = data["height"][occ]
l = data["left"][occ]
t = data["top"][occ]
# define all the surrounding box points
p1 = (l, t)
p2 = (l + w, t)
p3 = (l + w, t + h)
p4 = (l, t + h)
# draw the 4 lines (rectangular)
image_copy = cv2.line(image_copy, p1, p2, color=(255, 0, 0), thickness=2)
image_copy = cv2.line(image_copy, p2, p3, color=(255, 0, 0), thickness=2)
image_copy = cv2.line(image_copy, p3, p4, color=(255, 0, 0), thickness=2)
image_copy = cv2.line(image_copy, p4, p1, color=(255, 0, 0), thickness=2)
if cv2.waitKey(1) == ord("q"):
break
cv2.imshow("image_copy", image_copy)
cap.release()
cv2.destroyAllWindows()