ocr mac

ocr mac.py

#!/Applications/Xcode.app/Contents/Developer/usr/bin/python3

import config,json,os,subprocess,ocr2json
from tqdm import tqdm
from joblib import Parallel, delayed

import Quartz,Vision
from Cocoa import NSURL
from Foundation import NSDictionary
from wurlitzer import pipes # needed to capture system-level stderr

def ocr(image_filename):
    input_url = NSURL.fileURLWithPath_(image_filename)
    with pipes() as (out, err):
        input_image = Quartz.CIImage.imageWithContentsOfURL_(input_url)
    (width,height) = input_image.extent().size
    vision_options = NSDictionary.dictionaryWithDictionary_({})
    vision_handler = Vision.VNImageRequestHandler.alloc().initWithCIImage_options_(
        input_image, vision_options
    )

    request = Vision.VNRecognizeTextRequest.alloc().init().autorelease()
    request.setRecognitionLevel_(Vision.VNRequestTextRecognitionLevelAccurate) #VNRequestTextRecognitionLevelFast
    request.setRecognitionLanguages_(["nl-NL"])
    error = vision_handler.performRequests_error_([request], None)

    results = []
    for item in request.results():
        bbox = item.boundingBox()
        w, h = bbox.size.width, bbox.size.height
        x, y = bbox.origin.x, bbox.origin.y
        results.append({
            "x":int(x*width),
            "y":int(height - y*height - h*height),
            "w":int(w*width),
            "h":int(h*height),
            "conf":item.confidence(),
            "text":item.text()
        })
    return results

def do_ocr(image_file_path, progress):
    file_id = config.get_id_from_path(image_file_path)
    json_file_path = config.make_path(base_folder=config.DEEDS_OCR_JSON_FOLDER, id=file_id, suffix=".json")

    if not os.path.exists(json_file_path):
        data = ocr(str(image_file_path))
        if data and len(data)>0:
            json.dump(data, open(json_file_path,"w"), indent=2)
        print(json_file_path,str(int(progress*1000)/10.)+"%")


def run():
    print("run ocr_per_akte")

    if not os.path.exists(config.DEEDS_OCR_JSON_FOLDER):
        os.mkdir(config.DEEDS_OCR_JSON_FOLDER)

    file_paths = config.get_deeds_image_file_paths()
    results = Parallel(n_jobs=1, prefer="threads")(
      delayed(do_ocr)(image_file_path,i/len(file_paths))
      for i,image_file_path in enumerate(file_paths)
    )


if __name__ == '__main__':
    run()