答题卡识别判卷python实现代码

以下是一个基本的答题卡识别和判卷的 Python 实现代码，仅供参考：

import cv2
import numpy as np
import pytesseract

# 读取答题卡图像
img = cv2.imread('answer_sheet.jpg')

# 灰度化
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# 二值化
ret, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)

# 去噪
kernel = np.ones((3, 3), np.uint8)
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=2)
sure_bg = cv2.dilate(opening, kernel, iterations=3)

# 轮廓检测
contours, hierarchy = cv2.findContours(sure_bg, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

# 分割小格子
boxes = []
for cnt in contours:
    area = cv2.contourArea(cnt)
    if area > 100 and area < 5000:
        x, y, w, h = cv2.boundingRect(cnt)
        if w > 10 and h > 10:
            boxes.append((x, y, w, h))

# 对每个小格子进行 OCR 识别
answers = []
for box in boxes:
    x, y, w, h = box
    roi = thresh[y:y+h, x:x+w]
    text = pytesseract.image_to_string(roi, config='--psm 10')
    answers.append(text.strip())

# 比对正确答案，得出得分
score = 0
correct_answers = ['A', 'B', 'C', 'D']
for i, answer in enumerate(answers):
    if answer in correct_answers[i % 4]:
        score += 1

# 输出得分
print('Score:', score)

以上代码实现了对一张答题卡图像的识别和判卷，具体实现还需要根据实际情况进行调整和优化。