.. _ID_Card :

ID Card Agent 
==============

The ID Card Agent is smart AI-powered solution that extracts important key-value information from an image. The agent is also capable of computing bounding box coordinates for important information like Photo of the cardholder, signature of the cardholder etc. Currently a single version of the agent is available. More Agent Versions coming soon.

1. Agents Input Dictionary
---------------------------

Firstly an Agents-input Dictionary has to be defined. For a ID card agent, the agent input dictionary is of the format :

.. code-block:: console

    inputs_dict = {
        "base64_image" : img_processed,
    }

2. Agent's Process Functionality 
---------------------------------

After setting an inputs dictionary, Set up the agent name and process the query. 

.. code-block:: console

    agent_name = latentforce/id_card_agent
    res = agent.process(agent_name = agent_name, agent_inputs = inputs_dict)
    print(res)

.. note::

    Only one id_card_agent is available currently. More agent versions coming soon.

3. Plotting Bounding Boxes
---------------------------

To plot an extracted bounding box on the image : 

.. code-block:: console

    from PIL import Image
    from matplotlib import pyplot as plt

    def plot_bbox_check(image, data):
    # Create a figure and axes
        fig, ax = plt.subplots()

        # Display the image
        ax.imshow(image)
        cropped_regions = []
        # Plot each bounding box
        for label, bbox in data.items():
            # Unpack the bounding box coordinates
            x1, y1, x2, y2 = bbox
            # Create a Rectangle patch
            rect = patches.Rectangle(
                (x1, y1), 
                x2 - x1, 
                y2 - y1, 
                linewidth = 1, 
                edgecolor = 'r', 
                facecolor = 'none'
                )

            # Add the rectangle to the Axes
            ax.add_patch(rect)

            # Annotate the label
            plt.text(
                x1, 
                y1, 
                label, 
                color = 'white', 
                fontsize = 8, 
                bbox = dict(facecolor = 'red', alpha = 0.5)
                )

            cropped_region = image.crop((x1, y1, x2, y2))
            cropped_regions.append(cropped_region)

        # Remove the axis ticks and labels
        ax.axis('off')

        # Show the plot
        plt.show()
        return cropped_regions

    image = Image.open(image_path)
    plot_bbox_check(image, res['results']['bbox'])