vis.py

from PIL import Image, ImageDraw, ImageFont
from PIL import ImageColor
additional_colors = [colorname for (colorname, colorcode) in ImageColor.colormap.items()]


def plot_bounding_boxes(im, bounding_boxes):
    """
    Plots bounding boxes on an image with markers for each a name, using PIL, normalized coordinates, and different colors.

    Args:
        img_path: The path to the image file.
        bounding_boxes: A list of bounding boxes containing the name of the object
         and their positions in normalized [y1 x1 y2 x2] format.
    """

    # Load the image
    img = im
    width, height = img.size
    # Create a drawing object
    draw = ImageDraw.Draw(img)

    # Define a list of colors
    colors = [
    'red',
    'green',
    'blue',
    'yellow',
    'orange',
    'pink',
    'purple',
    'brown',
    'gray',
    'beige',
    'turquoise',
    'cyan',
    'magenta',
    'lime',
    'navy',
    'maroon',
    'teal',
    'olive',
    'coral',
    'lavender',
    'violet',
    'gold',
    'silver',
    ] + additional_colors

    # Iterate over the bounding boxes
    for i, bounding_box in enumerate(bounding_boxes):
        # Select a color from the list
        color = colors[i % len(colors)]

        # Convert normalized coordinates to absolute coordinates
        abs_y1 = int(bounding_box[1])
        abs_x1 = int(bounding_box[0])
        abs_y2 = int(bounding_box[3])
        abs_x2 = int(bounding_box[2])

        if abs_x1 > abs_x2:
            abs_x1, abs_x2 = abs_x2, abs_x1

        if abs_y1 > abs_y2:
            abs_y1, abs_y2 = abs_y2, abs_y1

        # Draw the bounding box
        draw.rectangle(
            ((abs_x1, abs_y1), (abs_x2, abs_y2)), outline=color, width=4
        )

    # Display the image
    return img