# Performs a very fast OCR on a list of images (file path, url, base64, bytes, numpy, PIL ...) using Tesseract and returns the recognized text, its coordinates, and line-based word grouping in a DataFrame.
## Tested against Windows 10 / Python 3.11 / Anaconda
### pip install multitessiocr
```python
from multitessiocr import tesser_ocr
piclist = [
r"C:\screeeni\35.png",
r"C:\Users\hansc\Downloads\2023-11-12 00_48_43-.png",
r"C:\Users\hansc\Downloads\WhatsApp Image 2023-09-19 at 12.03.41 PM.jpeg",
r"C:\Users\hansc\Downloads\WhatsApp Image 2023-09-19 at 11.06.46 AM.jpeg",
r"C:\Users\hansc\Downloads\WhatsApp Image 2023-09-19 at 11.06.33 AM.jpeg",
r"C:\Users\hansc\Downloads\WhatsApp Image 2023-09-19 at 11.06.22 AM.jpeg",
r"C:\Users\hansc\Downloads\WhatsApp Image 2023-09-19 at 12.03.42 PM.jpeg",
]
df = tesser_ocr(
piclist=piclist,
tesser_path=r"C:\Program Files\Tesseract-OCR\tesseract.exe",
add_after_tesseract_path="",
add_at_the_end="-l eng+por --psm 3",
processes=5,
chunks=5,
print_stdout=False,
print_stderr=True,
)
# aa_text aa_start_x aa_start_y aa_end_x aa_end_y aa_object aa_type aa_element_index aa_page aa_index aa_language aa_parents aa_all_children aa_direct_children aa_tag aa_x_size aa_x_descenders aa_x_ascenders aa_x_wconf aa_baseline_1 aa_baseline_2 aa_document_index aa_width aa_height aa_area aa_center_x aa_center_y
# 7 Ameta-markup 802 318 922 335 word word 1 1 3 <NA> (4, 5) () () span <NA> <NA> <NA> 77.0 <NA> <NA> 0 120 17 2040 862 326
# 8 language, 933 321 1001 335 word word 1 1 4 <NA> (4, 5) () () span <NA> <NA> <NA> 96.0 <NA> <NA> 0 68 14 952 967 328
# 9 used 1014 318 1050 331 word word 1 1 5 <NA> (4, 5) () () span <NA> <NA> <NA> 96.0 <NA> <NA> 0 36 13 468 1032 324
Perform OCR on a list of images using Tesseract.
Parameters:
- piclist (list): List of image file paths.
- tesser_path (str): Path to the Tesseract executable.
- add_after_tesseract_path (str): Additional parameters to add after the Tesseract path.
- add_at_the_end (str): Additional parameters to add at the end of Tesseract command.
- processes (int): Number of parallel processes for image processing.
- chunks (int): Number of chunks to divide the image list for parallel processing.
- print_stdout (bool): Whether to print standard output during execution.
- print_stderr (bool): Whether to print standard error during execution.
Returns:
- pd.DataFrame: A DataFrame containing parsed OCR results.
```
Raw data
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"description": "\r\n# Performs a very fast OCR on a list of images (file path, url, base64, bytes, numpy, PIL ...) using Tesseract and returns the recognized text, its coordinates, and line-based word grouping in a DataFrame.\r\n\r\n## Tested against Windows 10 / Python 3.11 / Anaconda\r\n\r\n### pip install multitessiocr\r\n\r\n\r\n```python\r\nfrom multitessiocr import tesser_ocr\r\n\r\npiclist = [\r\n r\"C:\\screeeni\\35.png\",\r\n r\"C:\\Users\\hansc\\Downloads\\2023-11-12 00_48_43-.png\",\r\n r\"C:\\Users\\hansc\\Downloads\\WhatsApp Image 2023-09-19 at 12.03.41 PM.jpeg\",\r\n r\"C:\\Users\\hansc\\Downloads\\WhatsApp Image 2023-09-19 at 11.06.46 AM.jpeg\",\r\n r\"C:\\Users\\hansc\\Downloads\\WhatsApp Image 2023-09-19 at 11.06.33 AM.jpeg\",\r\n r\"C:\\Users\\hansc\\Downloads\\WhatsApp Image 2023-09-19 at 11.06.22 AM.jpeg\",\r\n r\"C:\\Users\\hansc\\Downloads\\WhatsApp Image 2023-09-19 at 12.03.42 PM.jpeg\",\r\n]\r\n\r\ndf = tesser_ocr(\r\n piclist=piclist,\r\n tesser_path=r\"C:\\Program Files\\Tesseract-OCR\\tesseract.exe\",\r\n add_after_tesseract_path=\"\",\r\n add_at_the_end=\"-l eng+por --psm 3\",\r\n processes=5,\r\n chunks=5,\r\n print_stdout=False,\r\n print_stderr=True,\r\n)\r\n\r\n# aa_text aa_start_x aa_start_y aa_end_x aa_end_y aa_object aa_type aa_element_index aa_page aa_index aa_language aa_parents aa_all_children aa_direct_children aa_tag aa_x_size aa_x_descenders aa_x_ascenders aa_x_wconf aa_baseline_1 aa_baseline_2 aa_document_index aa_width aa_height aa_area aa_center_x aa_center_y\r\n# 7 Ameta-markup 802 318 922 335 word word 1 1 3 <NA> (4, 5) () () span <NA> <NA> <NA> 77.0 <NA> <NA> 0 120 17 2040 862 326\r\n# 8 language, 933 321 1001 335 word word 1 1 4 <NA> (4, 5) () () span <NA> <NA> <NA> 96.0 <NA> <NA> 0 68 14 952 967 328\r\n# 9 used 1014 318 1050 331 word word 1 1 5 <NA> (4, 5) () () span <NA> <NA> <NA> 96.0 <NA> <NA> 0 36 13 468 1032 324\r\n\r\n\r\n Perform OCR on a list of images using Tesseract.\r\n\r\n Parameters:\r\n - piclist (list): List of image file paths.\r\n - tesser_path (str): Path to the Tesseract executable.\r\n - add_after_tesseract_path (str): Additional parameters to add after the Tesseract path.\r\n - add_at_the_end (str): Additional parameters to add at the end of Tesseract command.\r\n - processes (int): Number of parallel processes for image processing.\r\n - chunks (int): Number of chunks to divide the image list for parallel processing.\r\n - print_stdout (bool): Whether to print standard output during execution.\r\n - print_stderr (bool): Whether to print standard error during execution.\r\n\r\n Returns:\r\n - pd.DataFrame: A DataFrame containing parsed OCR results.\r\n\r\n```\r\n",
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