Python 使用PyteSeract/OpenCV绘制边界框

我正在使用pytesseract（0.3.2）和openCV（4.1.2）来识别图像中的数字。当image_to_字符串工作时，image_to_数据和image_to_框不工作。我需要能够绘制图像上的边界框，这让我感到困惑。我尝试过不同的图像，pytesseract的旧版本，等等。我正在使用Windows和Jupyter笔记本电脑

import cv2 
import pytesseract

#erosion
def erode(image):
    kernel = np.ones((5,5),np.uint8)
    return cv2.erode(image, kernel, iterations = 1)

#grayscale
def get_grayscale(image):
    return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

#thresholding
def thresholding(image):
    #return cv2.adaptiveThreshold(image, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 31, 2)
    return cv2.threshold(image, 200, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

img = cv2.imread('my_image.jpg')
pytesseract.pytesseract.tesseract_cmd = r'C:\mypath\tesseract.exe'

gray = get_grayscale(img)
thresh = thresholding(gray)
erode = remove_noise(thresh)

custom_config = r'-c tessedit_char_whitelist=0123456789 --psm 6'
print(pytesseract.image_to_string(erode, config=custom_config))

cv2.imwrite("test.jpg", erode)

#these return nothing
print(pytesseract.image_to_boxes(Image.open('test.jpg')))
print(pytesseract.image_to_data(Image.open('test.jpg')))

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代替使用

图像到框

，另一种方法是简单地使用查找轮廓，获得边界矩形坐标，并使用绘制边界框

使用此示例输入图像

画框

光学字符识别结果

1234567890

代码

---

请尝试以下代码：

from pytesseract import Output
import pytesseract
import cv2
 
image = cv2.imread("my_image.jpg")

#swap color channel ordering from BGR (OpenCV’s default) to RGB (compatible with Tesseract and pytesseract).
# By default OpenCV stores images in BGR format and since pytesseract assumes RGB format,
# we need to convert from BGR to RGB format/mode:
rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
 
pytesseract.pytesseract.tesseract_cmd = r'C:\mypath\tesseract.exe'
custom_config = r'-c tessedit_char_whitelist=0123456789 --psm 6'
results = pytesseract.image_to_data(rgb, output_type=Output.DICT,lang='eng',config=custom_config)
boxresults = pytesseract.image_to_boxes(rgb,output_type=Output.DICT,lang='eng',config=custom_config)
print(results)
print(boxresults)

for i in range(0, len(results["text"])):
    # extract the bounding box coordinates of the text region from the current result
    tmp_tl_x = results["left"][i]
    tmp_tl_y = results["top"][i]
    tmp_br_x = tmp_tl_x + results["width"][i]
    tmp_br_y = tmp_tl_y + results["height"][i] 
    tmp_level = results["level"][i]
    conf = results["conf"][i]
    text = results["text"][i]
    
    if(tmp_level == 5):
        cv2.putText(image, text, (tmp_tl_x, tmp_tl_y - 10), cv2.FONT_HERSHEY_SIMPLEX,0.5, (0, 0, 255), 1)
        cv2.rectangle(image, (tmp_tl_x, tmp_tl_y), (tmp_br_x, tmp_br_y), (0, 0, 255), 1)
        
for j in range(0,len(boxresults["left"])):
    left = boxresults["left"][j]
    bottom = boxresults["bottom"][j]
    right = boxresults["right"][j]
    top = boxresults["top"][j] 
    cv2.rectangle(image, (left, top), (right, bottom), (255, 0, 0), 1)
       
    
cv2.imshow("image",image)
cv2.waitKey(0)

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有趣的是，10年后，同样的问题还是一次又一次地出现。不管怎样，你在帮助别人方面做得很好！我看不出用这种方法打印预测字符及其对应框的方法。我不明白，边界框不是你想要的吗？

from pytesseract import Output
import pytesseract
import cv2
 
image = cv2.imread("my_image.jpg")

#swap color channel ordering from BGR (OpenCV’s default) to RGB (compatible with Tesseract and pytesseract).
# By default OpenCV stores images in BGR format and since pytesseract assumes RGB format,
# we need to convert from BGR to RGB format/mode:
rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
 
pytesseract.pytesseract.tesseract_cmd = r'C:\mypath\tesseract.exe'
custom_config = r'-c tessedit_char_whitelist=0123456789 --psm 6'
results = pytesseract.image_to_data(rgb, output_type=Output.DICT,lang='eng',config=custom_config)
boxresults = pytesseract.image_to_boxes(rgb,output_type=Output.DICT,lang='eng',config=custom_config)
print(results)
print(boxresults)

for i in range(0, len(results["text"])):
    # extract the bounding box coordinates of the text region from the current result
    tmp_tl_x = results["left"][i]
    tmp_tl_y = results["top"][i]
    tmp_br_x = tmp_tl_x + results["width"][i]
    tmp_br_y = tmp_tl_y + results["height"][i] 
    tmp_level = results["level"][i]
    conf = results["conf"][i]
    text = results["text"][i]
    
    if(tmp_level == 5):
        cv2.putText(image, text, (tmp_tl_x, tmp_tl_y - 10), cv2.FONT_HERSHEY_SIMPLEX,0.5, (0, 0, 255), 1)
        cv2.rectangle(image, (tmp_tl_x, tmp_tl_y), (tmp_br_x, tmp_br_y), (0, 0, 255), 1)
        
for j in range(0,len(boxresults["left"])):
    left = boxresults["left"][j]
    bottom = boxresults["bottom"][j]
    right = boxresults["right"][j]
    top = boxresults["top"][j] 
    cv2.rectangle(image, (left, top), (right, bottom), (255, 0, 0), 1)
       
    
cv2.imshow("image",image)
cv2.waitKey(0)