Optical Character Recognition (OCR) with OpenVINO™

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Google ColabGithub

This tutorial demonstrates how to perform optical character recognition (OCR) with OpenVINO models. It is a continuation of the 004-hello-detection tutorial, which shows only text detection.

The horizontal-text-detection-0001 and text-recognition-resnet models are used together for text detection and then text recognition.

In this tutorial, Open Model Zoo tools including Model Downloader, Model Converter and Info Dumper are used to download and convert the models from Open Model Zoo. For more information, refer to the 104-model-tools tutorial.

Table of contents:

# Install openvino-dev package
%pip install -q "openvino-dev>=2023.1.0"  onnx
Note: you may need to restart the kernel to use updated packages.

Imports

from pathlib import Path

import cv2
import matplotlib.pyplot as plt
import numpy as np
import openvino as ov
from IPython.display import Markdown, display
from PIL import Image

# Fetch `notebook_utils` module
import urllib.request
urllib.request.urlretrieve(
    url='https://raw.githubusercontent.com/openvinotoolkit/openvino_notebooks/main/notebooks/utils/notebook_utils.py',
    filename='notebook_utils.py'
)
from notebook_utils import load_image

Settings

core = ov.Core()

model_dir = Path("model")
precision = "FP16"
detection_model = "horizontal-text-detection-0001"
recognition_model = "text-recognition-resnet-fc"

model_dir.mkdir(exist_ok=True)

Download Models

The next cells will run Model Downloader to download the detection and recognition models. If the models have been downloaded before, they will not be downloaded again.

download_command = f"omz_downloader --name {detection_model},{recognition_model} --output_dir {model_dir} --cache_dir {model_dir} --precision {precision}  --num_attempts 5"
display(Markdown(f"Download command: `{download_command}`"))
display(Markdown(f"Downloading {detection_model}, {recognition_model}..."))
!$download_command
display(Markdown(f"Finished downloading {detection_model}, {recognition_model}."))

detection_model_path = (model_dir / "intel/horizontal-text-detection-0001" / precision / detection_model).with_suffix(".xml")
recognition_model_path = (model_dir / "public/text-recognition-resnet-fc" / precision / recognition_model).with_suffix(".xml")

Download command: omz_downloader --name horizontal-text-detection-0001,text-recognition-resnet-fc --output_dir model --cache_dir model --precision FP16  --num_attempts 5

Downloading horizontal-text-detection-0001, text-recognition-resnet-fc…

################|| Downloading horizontal-text-detection-0001 ||################

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