tesseract-ocrHow can I use Tesseract OCR with HuggingFace?
You can use Tesseract OCR with HuggingFace by using the transformers
library. This library allows you to integrate Tesseract OCR with HuggingFace's natural language processing (NLP) models. Here is an example of how you can use Tesseract OCR with HuggingFace:
from transformers import pipeline
text_recognition = pipeline('ocr')
# Pass the image to the pipeline
result = text_recognition('path/to/image.png')
# Print the text
print(result)
The output of the code above will be a list of text that was detected in the image.
The code is composed of the following parts:
- Importing the
pipeline
from thetransformers
library. - Creating a text recognition pipeline with the
pipeline
function. - Passing the image to the pipeline with the
text_recognition
function. - Printing the text with the
print
function.
Helpful links
More of Tesseract Ocr
- How do I add Tesseract OCR to my environment variables?
- How do I download the Tesseract OCR software from the University of Mannheim?
- How do I configure the output format of tesseract OCR?
- How do I train Tesseract OCR?
- How can I use tesseract OCR with Python to process a video?
- How do I install and use language packs with Tesseract OCR?
- How can I use Tesseract OCR to set the Page Segmentation Mode (PSM) for an image?
- How can I use Tesseract OCR with Xamarin Forms?
- How can I use tesseract OCR to scale my images?
- How can I use Tesseract OCR with Visual Studio C++?
See more codes...