Xdf To Kp _best_

# Convert to KP by writing a simple header + raw pixel data # (This is a simplified KP v1 writer; real KP might require specific magic bytes) with open(kp_path, 'wb') as kp_file: # Write KP header: 4 bytes version, 4 bytes width, 4 bytes height, 1 byte compression kp_file.write(struct.pack('<IIIB', 1, width, height, 0)) # version 1, no compression kp_file.write(pixel_grid.tobytes())

import xml.etree.ElementTree as ET import numpy as np from PIL import Image import struct def xdf_to_kp_raster(xdf_path, kp_path, data_field="Value", width=1920, height=1080): """ Convert an XML-based XDF file to a raster KP (Knockout Power) mask. Assumes XDF contains a 2D grid or sequential data that can be mapped to pixels. """ tree = ET.parse(xdf_path) root = tree.getroot() xdf to kp

pixel_grid = normalized.reshape((height, width)).astype(np.uint8) # Convert to KP by writing a simple

# Reshape to 2D (assumes width*height matches data length; otherwise crop/pad) expected_size = width * height if len(normalized) > expected_size: normalized = normalized[:expected_size] elif len(normalized) < expected_size: normalized = np.pad(normalized, (0, expected_size - len(normalized)), 'constant') 4 bytes width