OCR function and performance evaluation of pytesseract library

Pytesseract library is a Python library for optical character recognition (OCR).It is realized by the encapsulation of the Tesseract-OCR engine with Google.This library makes it very simple to use the OCR function in the Python program. OCR is a technology that converts texts in images into editing and searchable texts.Using OCR, you can extract the text in digital images or scanned documents so that it can be automated and analyzed. Pytesseract library has the following characteristics and functions: 1. Multi -language support: Pytesseract library supports OCR recognition of more than 100 different languages, including Chinese. 2. Simple and easy to use: You can integrate the OCR function in the Python program with just a few lines of code.By calling the `pytesseract.image_to_string () function and pass the image path or image object, you can get text in the image. 3. Support image pre -processing: Pytesseract library allows pre -processing of images to improve the accuracy of OCR.For example, PIL libraries can be used to scaling, rotation, and dual -value of images with PIL libraries. 4. Custom configuration: By setting the configuration parameters of the TESSERACT engine, the behavior of OCR can be flexibly controlled.You can modify the OCR parameters by passing the `Config` parameter, such as language, page segmentation mode, and model of OCR engines. 5. Expansion: Since it is developed based on the TESSERACT-OCR engine, it can be used by other advanced functions provided by Tesseract-OCR, such as text direction detection and layout analysis. The following is a simple example code that demonstrates how to use the Pytesseract library for OCR recognition: python from PIL import Image import pytesseract # Open the image and processed pre -processing image = Image.open('example_image.jpg') Image = Image.Resize ((800, 600)) # i i i Image = Image.convert ('L') # turn to gray image # OCR recognition text = pytesseract.image_to_string(image, lang='chi_sim', config='--psm 6') print(text) In the above code, we first opened a image with the Pil library and made preparatory processing.Then, we use the `pytesseract.image_to_string () function to pass the pre -processed image and appropriate configuration parameters for OCR recognition.Finally, we print out the text recognized. It should be noted that to run the above code, you need to install the Pytesseract library in your Python environment and configure the Tesseract-OCR engine. Evaluate the performance of the Pytesseract library can be considered in the following aspects: 1. Accuracy: The accuracy of OCR is one of the key indicators to evaluate the performance of the library.The accuracy can be evaluated by comparing the differences between OCR results and real text. 2. Processing speed: The processing speed of OCR is also an important indicator.The timer can be used to measure the time required for the OCR processing image and compare it with other OCR libraries or software. 3. Multi -language support: For Chinese OCR recognition, multi -language support is an important consideration.The multi -language support of the Pytesseract library allows it to handle Chinese text well. 4. Scalability: Pytesseract library is in the Tesseract-OCR engine, so you can use other advanced features provided by the engine, such as layout analysis, text direction detection, etc. In summary, the Pytesseract library provides a simple and easy -to -use Python interface for OCR recognition.It has good multi -language support and scalability, and can customize OCR by setting configuration parameters.In terms of performance, it can be evaluated through indicators such as accuracy, processing speed.