CUR (Read Only) Format Reference

The CUR file format variant is an internal binary container standard engineered specifically for storing static user interface mouse cursors within Windows environments. Structurally nearly identical to standard Windows icon directories (.ICO parameters), a CUR asset contains a designated header denoting individual graphic resolutions alongside unique data layers detailing hot-spot mouse coordinate targets.

Decoding Constraints & Behaviors

The internal image decoder handles reading parameters cleanly but treats the files strictly under specific functional behaviors:

• Resolution Selection Strategy: When parsing a multi-resolution container block containing diverse dimension tiers, the image wrapper isolates and initializes the largest available resolution layer stored within the directory automatically.
• Read-Only Lifecycle: The pipeline engine does not feature encoder serialization matrices for this file standard. It can unpack data into system frames for processing workflows, but saving a modified layer directly using format="CUR" is unsupported.

Interpreting Cursor Coordinates (Hot-Spots)

Unlike conventional icons, CUR structures include pixel offsets indicating the precise pixel focal coordinate handling active click triggers. When parsing a cursor image frame, PIL isolates these header settings and binds them to the active context attributes layer:

from PIL import Image

def inspect_system_cursor(cursor_file_path):
    # Load the target pointer resource safely
    with Image.open(cursor_file_path) as cursor_asset:
        print(f"Decoder Active Mode: {cursor_asset.mode}")
        print(f"Target Resolution:   {cursor_asset.size[0]}x{cursor_asset.size[1]} pixels")
        
        # Pull format configurations from the container layer
        info_packet = cursor_asset.info
        if "hotspot" in info_packet:
            x_offset, y_offset = info_packet["hotspot"]
            print(f"Interception Hot-Spot: X={x_offset}, Y={y_offset}")
        else:
            print("No static interaction hot-spot offset specified in header.")

# Trigger inspection trace
# inspect_system_cursor("arrow.cur")

Conversion Pipeline Guide

To write image modifications back to disk, extract the primary canvas pixel payload directly out of the read-only file map, standardizing the resulting stream into an uncompressed format target like PNG or BMP:

with Image.open("pointer.cur") as cursor_src:
    # Cast the underlying layer into clean true color space layers
    canvas_output = cursor_src.convert("RGBA")
    # Export cleanly to an accessible web layout destination frame
    canvas_output.save("pointer_preview.png", format="PNG")