Recognizing SEMI OCR Font with Python and Dynamsoft Capture Vision SDK

Jul 03, 2025

 Capture Vision

•  PYTHON
•  OCR
•  SEMI
•  SEMICONDUCTOR
•  DCV
•  WINDOWS
•  LINUX
•  MACOS

SEMI (Semiconductor Equipment and Materials International) font is a special dot matrix font used for marking silicon wafers. In this tutorial, we’ll walk through building a Python application to recognize these specialized markings using Dynamsoft Capture Vision SDK.

Demo: Recognize SEMI Font with Python

Prerequisites

• Python 3.8 or later
• Dynamsoft Capture Vision Trial License: Get a 30-Day trial license key for the Dynamsoft Capture Vision SDK.

• Python Packages: Install the required Python packages using the following commands:

    pip install dynamsoft-capture-vision-bundle opencv-python
  

  • dynamsoft-capture-vision-bundle: Python binding for Dynamsoft Capture Vision SDK.
  • opencv-python: For displaying source images and overlaying recognition results.

Key Features

• Specialized SEMI Font Recognition: Uses a custom model trained for single-density dot matrix fonts (uppercase letters A-Z and digits 0-9).
• Visual Feedback: Draws bounding boxes around recognized text.
• Batch Processing: Processes single images or entire directories.
• Cross-Platform: Works on Windows, Linux, and macOS.

Step 1: Initialize the SDK

Create a new Python file and initialize the SDK with your license key:

from dynamsoft_capture_vision_bundle import *

err_code, err_str = LicenseManager.init_license("LICENSE-KEY")
if err_code != EnumErrorCode.EC_OK and err_code != EnumErrorCode.EC_LICENSE_CACHE_USED:
    print("License initialization failed: " + err_str)

Step 2: Load the SEMI OCR Model

A custom model trained by Dynamsoft enables the Capture Vision SDK to recognize SEMI fonts:

cvr = CaptureVisionRouter()

# Load the SEMI OCR model
with open('models/semi-ocr.data', 'rb') as f:
    model_data = f.read()
    
err_code, err_str = cvr.append_model_buffer('semi-ocr', model_data, 1)
if err_code != EnumErrorCode.EC_OK:
    print("Model loading failed: " + err_str)

For model-related questions, please contact Dynamsoft Support.

Step 3: Load Recognition Settings

Besides the model file, recognition settings must be loaded from a semi-ocr.json file.

err_code, err_str = cvr.init_settings_from_file("semi-ocr.json")
if err_code != EnumErrorCode.EC_OK:
    print("Configuration loading failed: " + err_str)

Step 4: Implement Image Processing

Here’s the core recognition logic that processes images and displays results:

import cv2
import numpy as np

def process_image(image_path, cvr):
    cv_image = cv2.imread(image_path)
                    
    result = cvr.capture(image_path, "recognize_semi_ocr")
    
    if result.get_error_code() != EnumErrorCode.EC_OK:
        print("Error: " + str(result.get_error_code())+ result.get_error_string())
    else:
        items = result.get_items()
        for item in items:
            if isinstance(item, TextLineResultItem):
                print(f"{RED}{item.get_text()}{RESET}")

                location = item.get_location()
                points = [(p.x, p.y) for p in location.points]
                cv2.drawContours(cv_image, [np.intp(points)], 0, (0, 255, 0), 2)

                cv2.putText(cv_image, item.get_text(), (points[0][0] + 10, points[0][1] + 20),
        
        cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 1)
    
        cv2.imshow(
            os.path.basename(image_path), cv_image)

Step 5: Create the Main Application Loop

Add a loop to handle single files or directories:

import os

def main():
    cvr = CaptureVisionRouter()
    # ... initialization code from previous steps ...
    
    while True:
        path = input("Enter image path or directory (Q to quit): ").strip()
        
        if path.lower() == "q":
            break
            
        if not os.path.exists(path):
            print("File not found: " + path)
            continue
        else:
            if os.path.isfile(path):
                process_image(path, cvr)
            elif os.path.isdir(path):
                files = os.listdir(path)
                for file in files:
                    if file.endswith(".jpg") or file.endswith(".jpeg") or file.endswith(".png"):
                        process_image(os.path.join(path, file), cvr)
                    
            cv2.waitKey(0)
            cv2.destroyAllWindows()

if __name__ == '__main__':
    main()

Step 6: Run the Python Script

python read_semi_ocr.py

Source Code

https://github.com/yushulx/python-barcode-qrcode-sdk/edit/main/examples/official/semi_font_ocr