# TableCV
**TableCV** is a Python package designed to extract tables from images. It offers two approaches for extracting tables, allowing you to choose the one that best suits your needs.
## Installation
You can easily install **TableCV** using pip:
```bash
pip install tablecv
```
## Usage
### Approach 1 (using PaddleOCR)
**TableCV** offers a straightforward method to extract tables using PaddleOCR. This approach returns a pandas DataFrame object:
```python
from tablecv import extract_table
# Replace "image_path" with the path to your image
print(extract_table(image_path="your_image.png"))
```
### Approach 2 (OCR with Your Preferred Tool)
If you prefer using a different OCR tool like EasyOCR, KerasOCR, or any other OCR solution, you can still use **TableCV**. First, perform OCR on your image using your chosen tool. The OCR results should be structured as a list of tuples, each containing a bounding box and corresponding text:
```python
# List of tuples: (bounding box as (x, y, w, h), text)
ocr_results = [
((1, 2, 3, 4), "a"),
((4, 5, 6, 7), "b"),
# Add more tuples as needed
]
```
After obtaining your OCR results, you can extract tables from them using **TableCV**:
```python
from tablecv import extract_table_from_ocr
# Replace "ocr_results" with your OCR results list
print(extract_table_from_ocr(ocr_results))
```
With these two approaches, **TableCV** provides flexibility for table extraction from images, whether you prefer using PaddleOCR or another OCR tool of your choice.
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