How to Build a Python OCR & Image Converter with Baidu API and Pillow

1. Text Recognition (OCR)

First, open the Baidu AI platform and select the OCR service; note that the same Python SDK is used for speech synthesis and image recognition.

Initialize the client with your credentials:

from aip import AipOcr
APP_ID = 'your App ID'
API_KEY = 'your Api Key'
SECRET_KEY = 'your Secret Key'
client = AipOcr(APP_ID, API_KEY, SECRET_KEY)

Example of recognizing a local image:

# Assuming image_path is the path to the image file
with open(image_path, 'rb') as f:
    image = f.read()
result = client.basicGeneral(image)
print(result)

Key request parameters:

image (string, required): base64‑encoded image data, max 4 MB, size 15 px–4096 px, formats jpg/png/bmp.

url (string, required): image URL, same size limits; ignored if image is provided.

language_type (string, optional): language to recognize, default CHN_ENG; options include EN, POR, FRE, etc.

detect_direction (bool, optional): whether to detect image orientation, default false.

detect_language (bool, optional): whether to detect language, default false.

probability (bool, optional): whether to return confidence for each line.

Important response fields:

direction (number, optional): image orientation code.

log_id (number, required): unique log identifier.

words_result_num (number, required): number of recognized words.

words_result (array, required): array of recognized text objects.

probability (object, optional): confidence information per line.

2. Image Format Converter

Using Pillow to safely convert image files instead of merely changing file extensions.

Installation: pip install pillow Import the library: from PIL import Image Utility to check if an image file is corrupted:

def isbad(path):
    try:
        Image.open(path).verify()
        return True
    except:
        return False

Function to convert a file to PNG:

def translate(path):
    if isbad(path):
        try:
            base, _ = path.rsplit(".", 1)
            output_path = base + ".png"
            im = Image.open(path)
            im.save(output_path)
            return True
        except:
            return False
    else:
        return False

Running the converter produces a usable PNG file, as shown below:

This project demonstrates practical Python techniques for OCR and image conversion, useful for automating file uploads and processing.