decryptomatte 1.0.1

Extract Cryptomatte data from EXR image files

Decryptomatte

This package works with Cryptomatte images, extracting and manipulating individual layers and their coverage information. It incorporates elements from the original cryptomatte_arnold unit tests, licensed under BSD-3 https://github.com/Psyop/CryptomatteArnold.

Artwork by dj3dim

Installation

Install via pip

While you can install this package from PyPi via pip pip install decryptomatte You'll most likely miss the required binary OpenImageIO wheel for your platform.

Install in virtual environment

On Windows, you can however clone this repository and install a binary OpenImageIO wheel from my private package index:

1. Get Python version > 3.9, tested with 3.11
2. git clone https://github.com/tappi287/decryptomatte.git
3. Install poetry
4. Navigate to the repository directory cd decryptomatte
5. Run poetry install

You should now be able to import and use this package inside your poetry/virtual environment.

Example

The package contains a convenience script to extract all masks to individual image files. Usage is show below.

from pathlib import Path

from decryptomatte import cryptomatte_to_images

if __name__ == '__main__':
    input_dir = Path('test/data/input')
    output_dir = input_dir / 'out'
    
    sample_matte_img = input_dir / 'BlenderExample.exr'
    sample_beauty_img = input_dir / 'BlenderExample.exr'

    cryptomatte_to_images(sample_matte_img, sample_beauty_img, output_dir=output_dir)

Usage

1. Importing the Class:

from decryptomatte import Decrypt

2. Creating an Instance:

• Basic Instance:

my_object = Decrypt("path/to/your/cryptomatte_image.exr")

• Instance with Arguments:

my_object = Decrypt("path/to/your/cryptomatte_image.exr", alpha_over_compositing=True)

• alpha_over_compositing (optional, default False) specifies handling alpha over compositing during certain operations.

Accessing Attributes:

While the class defines internal attributes, use the provided methods to interact with the object.

Methods:

• list_layers(): Returns available Cryptomatte layer names (IDs).
• crypto_metadata(): Returns extracted Cryptomatte metadata.
• sorted_crypto_metadata(): Returns sorted Cryptomatte metadata with ID coverage information.
• get_cryptomatte_channels(): Returns a NumPy array containing all Cryptomatte image channels.
• get_mattes_by_names(layer_names: List[str]) -> dict: Retrieves coverage mattes for specified layer names (IDs).
• _get_mattes_by_ids(target_ids: List[float]) -> Dict[float, np.ndarray]: (internal) Gets individual alpha coverage mattes for IDs.
• get_masks_for_ids(target_ids: List[float]) -> Generator[Tuple[float, np.ndarray], None, None]: (internal) Generates individual masks (anti-aliased) for each object ID.
• get_mask_for_id(float_id: float, channels_arr: np.ndarray, level: int = 6, as_8bit=False) -> np.ndarray: (internal) Extracts the mask for a specific ID from Cryptomatte layers.
• _iterate_image(width: int, height: int, target_ids: list) -> Dict[float, np.ndarray]: (internal) Iterates through all image pixels, collecting coverage values for specified IDs.
• id_to_name(self, id_float: float) -> str: Returns the human-readable layer name for the provided ID.
• create_layer_object_name(self, id_float: float) -> str: Creates a human-readable name combining the layer, ID, and object name.
• get_id_from_readable_layer_name(self, readable_layer_name: str) -> Optional[float]: Attempts to extract the ID from a human-readable layer name.
• merge_matte_and_id_color(self, matte: np.ndarray, id_float: Optional[float] = None, layer_name: Optional[str] = None) -> np.ndarray: Creates an RGBA image by combining the provided matte with its corresponding ID color.
• merge_matte_and_rgb(matte: np.ndarray, rgb_img: np.ndarray = None) -> np.ndarray: (static) Merges a matte with an optional RGB image, creating an RGBA image.
• shutdown(): Releases OpenImageIO resources