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Python 为什么图像中的某些行无法正确转换为文本? 在图像中间的文本行没有被正确地转换成文本是否有明显的原因?此图像是从youtube视频捕获的帧 image = cv2.imread(file_loc) custom_config = r'--oem 3 --psm 6' details = pytesseract.image_to_data(image, config=custom_config, lang='eng')_Python_Image Processing_Computer Vision_Ocr_Text Extraction - Fatal编程技术网

Python 为什么图像中的某些行无法正确转换为文本? 在图像中间的文本行没有被正确地转换成文本是否有明显的原因?此图像是从youtube视频捕获的帧 image = cv2.imread(file_loc) custom_config = r'--oem 3 --psm 6' details = pytesseract.image_to_data(image, config=custom_config, lang='eng')

Python 为什么图像中的某些行无法正确转换为文本? 在图像中间的文本行没有被正确地转换成文本是否有明显的原因?此图像是从youtube视频捕获的帧 image = cv2.imread(file_loc) custom_config = r'--oem 3 --psm 6' details = pytesseract.image_to_data(image, config=custom_config, lang='eng'),python,image-processing,computer-vision,ocr,text-extraction,Python,Image Processing,Computer Vision,Ocr,Text Extraction,输出: level page_num block_num par_num line_num word_num left top width height conf text 1 1 0 0 0 0 0 0 1280 580 -1 2 1 1 0 0 0 21 11 1256 556 -1 3 1 1 1 0 0 21 11 1256 556

输出:

level   page_num    block_num   par_num line_num    word_num    left    top width   height  conf    text
1   1   0   0   0   0   0   0   1280    580 -1  
2   1   1   0   0   0   21  11  1256    556 -1  
3   1   1   1   0   0   21  11  1256    556 -1  
4   1   1   1   1   0   277 11  744 66  -1  
5   1   1   1   1   1   277 11  91  50  95  Oh
5   1   1   1   1   2   390 11  127 66  95  they
5   1   1   1   1   3   538 28  91  49  96  say
5   1   1   1   1   4   648 11  195 65  96  people
5   1   1   1   1   5   865 28  156 33  96  come
4   1   1   1   2   0   365 109 566 66  -1  
5   1   1   1   2   1   365 109 149 66  23  Uo
5   1   1   1   2   2   535 109 305 66  0   hao
5   1   1   1   2   3   863 126 68  49  41  ee
4   1   1   1   3   0   21  207 1256    65  -1  
5   1   1   1   3   1   21  207 130 50  0   SUC
5   1   1   1   3   2   146 203 26  74  0   e
5   1   1   1   3   3   226 210 87  62  11  tas
5   1   1   1   3   4   343 207 416 50  0   UCMOCHIO
5   1   1   1   3   5   701 203 149 74  0   CMe
5   1   1   1   3   6   849 215 208 42  0   Rede
5   1   1   1   3   7   1079    207 198 65  12  moar
4   1   1   1   4   0   178 305 941 66  -1  
5   1   1   1   4   1   178 305 128 50  0   PWM
5   1   1   1   4   2   327 305 212 66  0   Ue
5   1   1   1   4   3   559 322 110 49  0   mum
5   1   1   1   4   4   691 305 265 66  0   vem
5   1   1   1   4   5   978 322 141 49  0   xeite
4   1   1   1   5   0   207 403 885 66  -1  
5   1   1   1   5   1   207 403 128 50  96  And
5   1   1   1   5   2   356 403 92  50  96  the
5   1   1   1   5   3   468 403 173 50  96  world
5   1   1   1   5   4   663 420 126 49  96  may
5   1   1   1   5   5   808 411 100 42  96  not
5   1   1   1   5   6   928 403 164 50  96  know
4   1   1   1   6   0   321 501 657 66  -1  
5   1   1   1   6   1   321 501 117 50  96  Still
5   1   1   1   6   2   460 504 22  46  96  I
5   1   1   1   6   3   507 518 85  33  96  see
5   1   1   1   6   4   611 518 110 49  96  you
5   1   1   1   6   5   743 501 235 50  96  celestial


无法在Windows 10上使用Tesseract 5.0.0.0-alpha进行复制,我得到了正确的输出。