local_image = open(local_image_path, "rb")
print("\nRecognizing printed text with OCR on a local image ...\n")
ocr_result = computervision_client.recognize_printed_text_in_stream(
local_image)
for region in ocr_result.regions:
for line in region.lines:
print("Bounding box: {}".format(line.bounding_box))
s = ""
for word in line.words:
s += word.text + " "
print(s + "\n")
# END - Recognize printed text with OCR in a local image
# Recognize printed text with OCR in a remote image by:
# 1. Calling the Computer Vision service's recognize_printed_text with the:
# - image
# 2. Displaying the lines of text and their bounding boxes.
remote_image_url = "https://raw.githubusercontent.com/Azure-Samples/cognitive-services-sample-data-files/master/ComputerVision/Images/printed_text.jpg"
print("\nRecognizing printed text with OCR on a remote image ...\n")
ocr_result = computervision_client.recognize_printed_text(remote_image_url)
for region in ocr_result.regions:
for line in region.lines:
print("Bounding box: {}".format(line.bounding_box))
s = ""
for word in line.words:
s += word.text + " "
print(s + "\n")
# END - Recognize printed text with OCR in a remote image
class ImageExtractor(BaseExtractor):
"""
This does Object Character Recognition (OCR) using Azure Computer Vision Service
"""
vision_client = None
def __init__(self):
try:
credentials = CognitiveServicesCredentials(key)
self.vision_client = ComputerVisionClient(
endpoint="https://" + region + ".api.cognitive.microsoft.com/",
credentials=credentials,
)
except Exception as e:
log.warning(
f"Can't init Azure ComputerVisionClient (make sure env vars are correct): {str(e)}"
)
self.vision_client = None
def _extract_text_from_image(self,
filename_or_url: str,
language: str = "en"):
# url = "https://upload.wikimedia.org/wikipedia/commons/thumb/1/12/Broadway_and_Times_Square_by_night.jpg/450px-Broadway_and_Times_Square_by_night.jpg"
# API docs: https://azuresdkdocs.blob.core.windows.net/$web/python/azure-cognitiveservices-vision-computervision/0.7.0/azure.cognitiveservices.vision.computervision.models.html#azure.cognitiveservices.vision.computervision.models.OcrResult
# Raw response from Azure Cognitive Service
ocr_result: OcrResult = None
if os.path.isfile(filename_or_url):
# Process a local file
local_image = open(filename_or_url, "rb")
ocr_result = self.vision_client.recognize_printed_text_in_stream(
local_image, detect_orientation=True, language="unk")
else:
# Process a public URL
ocr_result = self.vision_client.recognize_printed_text(
url=filename_or_url, detect_orientation=True, language="unk")
# Transfer all data into meta
meta = {
"language": ocr_result.language,
"text_angle": ocr_result.text_angle,
"orientation": ocr_result.orientation,
}
# TODO improve word list w. medical dictionary + more languages.
# FIXME: not very good results right now
spellcheck = Spellchecker(language=ocr_result.language)
# Now extract the text from all regions
fulltext = ""
for region in ocr_result.regions:
# print("Bounding box: {}".format(region.bounding_box))
for line in region.lines:
# print("Bounding box: {}".format(line.bounding_box))
for word in line.words:
corrected = spellcheck.correct_word(word.text)
if corrected != word.text:
log.debug(
f"auto-corrected word: {word.text} -> {corrected}")
fulltext += corrected + " "
fulltext += "\n"
fulltext += "\n\n"
# Return mutiple values
return fulltext, meta
def can_handle(self, request: ExtractorRequest) -> bool:
if not self.vision_client:
log.warn(
"Can't handle input, as the Azure Computer Vision Client hasn't been initialized"
)
return False
return (request.url and _is_supported_content_type(request.url)) or (
request.filename and _is_supported_content_type(request.filename))
def extract(self, request: ExtractorRequest) -> ExtractorResponse:
log.info(f"Extracting text from image (Azure Computer Vision OCR) ...")
try:
if request.url:
fulltext, meta = self._extract_text_from_image(request.url)
else:
fulltext, meta = self._extract_text_from_image(
request.filename)
# TODO get some meta data as well
meta = {**meta, **{"source": "image", "extractor": "az-vision"}}
return ExtractorResponse(text=fulltext, meta=meta)
except Exception as e:
msg = f"Error extracting text using Azure Computer Vision: '{str(e)}'"
log.error(msg)
return ExtractorResponse(error=msg)
