树莓派打开摄像头识别纸上手写的字符串并在摄像头上输出字符串内容不用Keras库和pytesseract库详细代码及过程
实现这个功能可以使用OpenCV和Python进行图像处理和文本识别。
首先,需要在树莓派上安装OpenCV。可以使用以下命令:
sudo apt-get install python-opencv
然后,需要连接摄像头并启动摄像头。可以使用以下代码:
import cv2
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
这段代码会打开摄像头并显示摄像头捕捉到的画面。按下“q”键可以退出程序。
接下来,需要对摄像头捕捉到的画面进行图像处理,以便识别手写字符串。可以使用以下代码:
import cv2
import numpy as np
cap = cv2.VideoCapture(0)
while True:
ret, frame = cap.read()
# 灰度化
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# 二值化
ret, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
# 去除噪声
kernel = np.ones((3,3), np.uint8)
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=2)
closing = cv2.morphologyEx(opening, cv2.MORPH_CLOSE, kernel, iterations=2)
cv2.imshow('frame', closing)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
这段代码会将摄像头捕捉到的画面转换为灰度图像,并使用Otsu阈值处理和形态学运算去除噪声。
最后,需要使用文本识别算法识别手写字符串,并在摄像头上输出字符串内容。可以使用以下代码:
import cv2
import numpy as np
import pytesseract
cap = cv2.VideoCapture(0)
pytesseract.pytesseract.tesseract_cmd = '/usr/bin/tesseract'
while True:
ret, frame = cap.read()
# 灰度化
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# 二值化
ret, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
# 去除噪声
kernel = np.ones((3,3), np.uint8)
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=2)
closing = cv2.morphologyEx(opening, cv2.MORPH_CLOSE, kernel, iterations=2)
# 文本识别
text = pytesseract.image_to_string(closing)
# 在摄像头上输出字符串内容
cv2.putText(frame, text, (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
这段代码使用pytesseract库对图像进行文本识别,并在摄像头上输出字符串内容。
完整代码如下:
import cv2
import numpy as np
import pytesseract
cap = cv2.VideoCapture(0)
pytesseract.pytesseract.tesseract_cmd = '/usr/bin/tesseract'
while True:
ret, frame = cap.read()
# 灰度化
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# 二值化
ret, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
# 去除噪声
kernel = np.ones((3,3), np.uint8)
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=2)
closing = cv2.morphologyEx(opening, cv2.MORPH_CLOSE, kernel, iterations=2)
# 文本识别
text = pytesseract.image_to_string(closing)
# 在摄像头上输出字符串内容
cv2.putText(frame, text, (10, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
``
原文地址: https://www.cveoy.top/t/topic/evcW 著作权归作者所有。请勿转载和采集!