速算作业智能批改 创建

import cv2
import pytesseract

def recognize_and_grade(image_path):
    # 读取图像
    image = cv2.imread(image_path)
    
    # 预处理图像（如灰度化、二值化等）
    processed_image = preprocess_image(image)
    
    # 使用OCR技术识别图像中的文字
    text = pytesseract.image_to_string(processed_image)
    
    # 解析并批改作业（此处需根据具体需求实现）
    grade = parse_and_grade(text)
    
    return grade

def preprocess_image(image):
    # 实现图像预处理逻辑
    gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    _, binary_image = cv2.threshold(gray_image, 128, 255, cv2.THRESH_BINARY)
    return binary_image

def parse_and_grade(text):
    # 实现作业解析和批改逻辑
    # 这里仅作示例，具体实现需根据作业格式和批改规则来定
    try:
        # 假设作业是简单的算术表达式，且正确答案为"42"
        if "42" in text:
            return "正确"
        else:
            return "错误"
    except Exception as e:
        return f"批改出错: {str(e)}"

# 使用示例
grade = recognize_and_grade("path_to_student_homework_image.jpg")
print(f"作业批改结果: {grade}")