kaira.models.image.compressors.BaseImageCompressor

Inheritance diagram for BaseImageCompressor

class kaira.models.image.compressors.BaseImageCompressor(max_bits_per_image: int | None = None, quality: int | float | None = None, collect_stats: bool = False, return_bits: bool = True, return_compressed_data: bool = False, *args: Any, **kwargs: Any)

Bases: BaseModel

Abstract base class for image compression methods.

This class provides a consistent interface for all image compression implementations in Kaira, including traditional methods (JPEG, PNG), modern standards (BPG), and neural network-based approaches.

All compressors support both quality-based and bit-constrained compression modes, batch processing capabilities, and optional compression statistics collection.

Methods

__init__	Initialize the image compressor.
forward	Process a batch of images through compression.
from_config	Create model instance from configuration.
from_hydra_config	Create model from Hydra DictConfig.
from_pretrained_config	Create model from Hugging Face PretrainedConfig.
get_compression_ratio	Calculate compression ratio.
get_stats	Get compression statistics from the last forward pass.

Examples using kaira.models.image.compressors.BaseImageCompressor

Original DeepJSCC Model (Bourtsoulatze 2019) with Training

Original DeepJSCC Model (Bourtsoulatze 2019) with Training

Image Compressors Comparison

Image Compressors Comparison

__init__(max_bits_per_image: int | None = None, quality: int | float | None = None, collect_stats: bool = False, return_bits: bool = True, return_compressed_data: bool = False, *args: Any, **kwargs: Any)

Initialize the image compressor.

Parameters:

• max_bits_per_image – Maximum bits allowed per compressed image. If provided without quality, the compressor will find the highest quality that produces files smaller than this limit.

• quality – Quality level for compression. Range and interpretation depend on the specific compressor implementation.

• collect_stats – Whether to collect and return compression statistics

• return_bits – Whether to return bits per image in forward pass

• return_compressed_data – Whether to return the compressed binary data

• *args – Variable positional arguments passed to the base class.

• **kwargs – Variable keyword arguments passed to the base class.

forward(x: Tensor, *args: Any, **kwargs: Any) → Tensor | Tuple[Tensor, List[int]] | Tuple[Tensor, List[bytes]] | Tuple[Tensor, List[int], List[bytes]]

Process a batch of images through compression.

Parameters:

• x – Tensor of shape [batch_size, channels, height, width] with values in [0, 1]

• *args – Additional positional arguments

• **kwargs – Additional keyword arguments

Returns:

Just the reconstructed image tensor If return_bits=True: Tuple of (tensor, bits per image) If return_compressed_data=True: Tuple of (tensor, compressed binary data) If both are True: Tuple of (tensor, bits per image, compressed binary data)

Return type:

If no additional returns

get_compression_ratio(original_size: int, compressed_size: int) → float

Calculate compression ratio.

Parameters:

• original_size – Size of original data in bits

• compressed_size – Size of compressed data in bits

Returns:

Compression ratio (original_size / compressed_size)

get_stats() → Dict[str, Any]

Get compression statistics from the last forward pass.

Returns:

Dictionary containing compression statistics

classmethod from_config(config, **kwargs)

Create model instance from configuration.

Parameters:

• config – Configuration object (PretrainedConfig, DictConfig, or dict)

• **kwargs – Additional parameters to override config

Returns:

Model instance

classmethod from_hydra_config(config: DictConfig, **kwargs)

Create model from Hydra DictConfig.

Parameters:

• config – Hydra configuration

• **kwargs – Additional parameters

Returns:

Model instance

classmethod from_pretrained_config(config: PretrainedConfig, **kwargs)

Create model from Hugging Face PretrainedConfig.

Parameters:

• config – PretrainedConfig instance

• **kwargs – Additional parameters

Returns:

Model instance