DETR Document Table Detection
It is a model trained to detect both Bordered and Borderless tables in documents
Experience the model with the demo screen.
Computer vision models are essential for automating tasks that require the interpretation of visual data. One such task is the detection of tables in images. The ability to detect tables in images is important for many applications, such as document scanning and processing, invoice processing, data entry automation, and more.
To detect tables in an image, a computer vision model uses image processing techniques to identify regions of the image that contain horizontal and vertical lines. Once these regions are identified, the model then analyzes them to determine if they form a table structure. This can involve identifying the number of rows and columns and any merged cells or table headers.
The model may use various techniques to accomplish this, including edge detection, corner detection, and line detection. Machine learning algorithms may also be used to train the model to recognize different types of tables and improve its accuracy.
Overall, the ability to detect tables in images is an important task for many industries and can greatly improve the efficiency and accuracy of data processing and analysis.