gcp_ocr.py

import os
#from google.cloud import vision
CRED = "/mnt/c/Users/techn/code/gcloud/My First Project-752b5f9e522b.json"
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = CRED

PATH = "/mnt/e/Takeout/Drive"
l = [x[0] for x in os.walk(PATH)]
l = [x for x in l if "ipynb" not in x]
l = l[1:]

files_nested = [ list(os.walk(d)) for d in l ]
files_nested = [ x for x in files_nested if x[0][0][1]]

def process_files(fs) :
    books = {}
    with open('results.txt', 'w') as f:
        for notebook in fs :
            book = {}
            notebook = notebook[0]
            path = notebook[0]
            notebook = notebook[2:][0]
            notebookName = path.split("/")[-1]
            
            for img in notebook:
                book[img] = detect_text(path + "/" + img, f)
            
            books[notebookName] = book
    
    return books


def detect_text(path, f):
    """Detects text in the file."""
    from google.cloud import vision
    import io
    client = vision.ImageAnnotatorClient()
    
    with io.open(path, 'rb') as image_file:
        content = image_file.read()
    
    image = vision.Image(content=content)
    hint = {"language_hints": ["en-t-i0-handwrit"]}
    response = client.document_text_detection(image=image, \
                                              image_context=hint)
    texts = response.text_annotations
    if response.error.message:
        print(path)
    l = [text.description for text in texts]
    print(l)
    
    for item in l:
        f.write("%s\n" % item)
    
process_files(files_nested)