XnView Software

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from pathlib import Path
from PIL import Image
import numpy as np
from scipy.spatial import ConvexHull
from scipy.ndimage import label

# Define the folder containing PNG images
folder_path = Path(r"D:\test")

# Define the target color (R, G, B) - Strict match only
target_color = (255, 0, 0)  # Example: Pure red


def get_color_mask(image, target_color):
    """Returns a binary mask where pixels match the exact target color."""
    return (
        (image[:, :, 0] == target_color[0]) &
        (image[:, :, 1] == target_color[1]) &
        (image[:, :, 2] == target_color[2])
    )


def get_corner_coordinates(coords):
    """Returns the corner coordinates using ConvexHull if possible."""
    if len(coords) >= 3:
        hull = ConvexHull(coords)
        return coords[hull.vertices].tolist()
    return coords.tolist()


def process_image(image_path, target_color):
    """Processes a single image and returns formatted shape details."""
    image = np.array(Image.open(image_path).convert("RGB"))
    color_mask = get_color_mask(image, target_color)
    labeled_array, num_shapes = label(color_mask)

    shape_details = []
    for shape_num in range(1, num_shapes + 1):
        shape_coords = np.column_stack(np.where(labeled_array == shape_num))
        corner_points = get_corner_coordinates(shape_coords)
        shape_details.append(f"Shape {shape_num}: {corner_points}")

    return num_shapes, shape_details


# Process all PNG images in the folder
for image_path in folder_path.glob("*.png"):
    num_shapes, shape_details = process_image(image_path, target_color)
    if shape_details:
        print(f"File: {image_path.name} | Shapes: {num_shapes} | {' | '.join(shape_details)}")