Table-Detection-using-Deep-Learning-on-Google-Colab

Table Detection using Deep Learning in a pdf.

Table detection part is followed by this paper Table Detection using Deep Learning , kindly site it if you are using it.

Image_preprocessing:

min_size: 600
max_size: 1024

Data_augmentation:

- flip:
    left_right: True
    up_down: True
    prob: 0.5

Model:

type: fasterrcnn
network:
  # Total number of classes to predict.
  num_classes: 1

Procedure:

Training:

- Run the code "1_Table_Detection_Training.ipynb" on colab python 3
- Upload the data.zip in colab directory
- Save the model(checkpoint) .tar File in google drive for Testing Purpose.

Testing:

- Run the code "2_Table_Detection_Testing.ipynb" in colab python 3
- Import the model(checkpoint) from google Drive **use same name of checkpoint**/
- Upload the "test_sample.png" image for testing from image.
- For testing From Pdf first run the code "Pdf_To_images.ipynb" in local directory <it will save the pdf to jpg images>
- Upload the zip of images on colab and run the next section pDF table detection
- The end product will be saved as Pdf file check the file for accuracy of given model detector.