easyocr-example.py

import easyocr 
import argparse
import cv2

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-i", "--image", required=True,
	help="path to input image to be OCR'd")
ap.add_argument("-l", "--langs", type=str, default="en",
	help="comma separated list of languages to OCR")
ap.add_argument("-g", "--gpu", type=int, default=-1,
	help="whether or not GPU should be used")
args = vars(ap.parse_args())

def cleanup_text(text):
	# strip out non-ASCII text so we can draw the text on the image
	# using OpenCV
	return "".join([c if ord(c) < 128 else "" for c in text]).strip()

# break the input languages into a comma separated list
langs = args["langs"].split(",")
print("[INFO] OCR'ing with the following languages: {}".format(langs))
# load the input image from disk
image = cv2.imread(args["image"])
# OCR the input image using EasyOCR
print("[INFO] OCR'ing input image...")
reader = easyocr.Reader(langs, gpu=args["gpu"] > 0)
results = reader.readtext(image)

# loop over the results
for (bbox, text, prob) in results:
	# display the OCR'd text and associated probability
	print("[INFO] {:.4f}: {}".format(prob, text))
	# unpack the bounding box
	(tl, tr, br, bl) = bbox
	tl = (int(tl[0]), int(tl[1]))
	tr = (int(tr[0]), int(tr[1]))
	br = (int(br[0]), int(br[1]))
	bl = (int(bl[0]), int(bl[1]))
	# cleanup the text and draw the box surrounding the text along
	# with the OCR'd text itself
	text = cleanup_text(text)
	cv2.rectangle(image, tl, br, (0, 255, 0), 2)
	cv2.putText(image, text, (tl[0], tl[1] - 10),
		cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 255, 0), 2)
# show the output image
cv2.imshow("Image", image)
cv2.waitKey(0)