from __future__ import annotations from typing import Literal, Optional, Union from .enum import ( ASTCConfigFlags, ASTCProfile, ASTCQualityPreset, ASTCSwizzleComponentSelector, ASTCType, ) class ASTCImage: """ An uncompressed 2D or 3D image. 3D image are passed in as an array of 2D slices. Each slice has identical size and color format. Attributes ---------- dim_x : int The X dimension of the image, in texels. dim_y : int The Y dimension of the image, in texels. dim_z : int The Z dimension of the image, in texels. data_type : ASTCType The data type per component. """ dim_x: int dim_y: int dim_z: int data_type: ASTCType data: Optional[bytes] def __init__( self, data_type: ASTCType, dim_x: int, dim_y: int, dim_z: int = 1, data: Optional[bytes] = None, ) -> None: ... class ASTCConfig: """ The config structure. This structure will initially be populated by the init, but power users may modify it afterwards. See astcenccli_toplevel_help.cpp for full user documentation of the power-user settings. Note for any settings which are associated with a specific color component, the value in the config applies to the component that exists after any compression data swizzle is applied. Legal block sizes are: - 2d - 4x4 - 5x4 - 5x5 - 6x5 - 6x6 - 8x5 - 8x6 - 8x8 - 10x5 - 10x6 - 10x8 - 10x10 - 12x10 - 12x12 - 3d - 3x3x3 - 4x3x3 - 4x4x3 - 4x4x4 - 5x4x4 - 5x5x4 - 5x5x5 - 6x5x5 - 6x6x5 - 6x6x6 Attributes ---------- profile : ASTCProfile The color profile. flags : int The set of set flags. block_x : int The ASTC block size X dimension. block_y : int The ASTC block size Y dimension. block_z : int The ASTC block size Z dimension. cw_r_weight : int The red component weight scale for error weighting (-cw). cw_g_weight : int The green component weight scale for error weighting (-cw). cw_b_weight : int The blue component weight scale for error weighting (-cw). cw_a_weight : int The alpha component weight scale for error weighting (-cw). a_scale_radius : int The radius for any alpha-weight scaling (-a). It is recommended that this is set to 1 when using FLG_USE_ALPHA_WEIGHT on a texture that will be sampled using linear texture filtering to minimize color bleed out of transparent texels that are adjacent to non-transparent texels. rgbm_m_scale : int The RGBM scale factor for the shared multiplier (-rgbm). tune_partition_count_limit : int The maximum number of partitions searched (-partitioncountlimit). Valid values are between 1 and 4. tune_2partition_index_limit : int The maximum number of partitions searched (-2partitionindexlimit). Valid values are between 1 and 1024. tune_3partition_index_limit : int The maximum number of partitions searched (-3partitionindexlimit). Valid values are between 1 and 1024. tune_4partition_index_limit : int The maximum number of partitions searched (-4partitionindexlimit). Valid values are between 1 and 1024. tune_block_mode_limit : int The maximum centile for block modes searched (-blockmodelimit). Valid values are between 1 and 100. tune_refinement_limit : int The maximum iterative refinements applied (-refinementlimit). Valid values are between 1 and N; there is no technical upper limit but little benefit is expected after N=4. tune_candidate_limit : int The number of trial candidates per mode search (-candidatelimit). Valid values are between 1 and TUNE_MAX_TRIAL_CANDIDATES. tune_2partitioning_candidate_limit : int The number of trial partitionings per search (-2partitioncandidatelimit). Valid values are between 1 and TUNE_MAX_PARTITIONING_CANDIDATES. tune_3partitioning_candidate_limit : int The number of trial partitionings per search (-3partitioncandidatelimit). Valid values are between 1 and TUNE_MAX_PARTITIONING_CANDIDATES. tune_4partitioning_candidate_limit : int The number of trial partitionings per search (-4partitioncandidatelimit). Valid values are between 1 and TUNE_MAX_PARTITIONING_CANDIDATES. tune_db_limit : float The dB threshold for stopping block search (-dblimit). This option is ineffective for HDR textures. tune_mse_overshoot : float The amount of MSE overshoot needed to early-out trials. The first early-out is for 1 partition, 1 plane trials, where we try a minimal encode using the high probability block modes. This can short-cut compression for simple blocks. The second early-out is for refinement trials, where we can exit refinement once quality is reached. tune_2partition_early_out_limit_factor : float The threshold for skipping 3.1/4.1 trials (-2partitionlimitfactor). This option is further scaled for normal maps, so it skips less often. tune_3partition_early_out_limit_factor : float The threshold for skipping 4.1 trials (-3partitionlimitfactor). This option is further scaled for normal maps, so it skips less often. tune_2plane_early_out_limit_correlation : float The threshold for skipping two weight planes (-2planelimitcorrelation). This option is ineffective for normal maps. tune_search_mode0_enable : float The config enable for the mode0 fast-path search. If this is set to TUNE_MIN_TEXELS_MODE0 or higher then the early-out fast mode0 search is enabled. This option is ineffective for 3D block sizes. """ profile: ASTCProfile flags: ASTCConfigFlags block_x: int block_y: int block_z: int cw_r_weight: int cw_g_weight: int cw_b_weight: int cw_a_weight: int a_scale_radius: int rgbm_m_scale: int tune_partition_count_limit: int tune_2partition_index_limit: int tune_3partition_index_limit: int tune_4partition_index_limit: int tune_block_mode_limit: int tune_refinement_limit: int tune_candidate_limit: int tune_2partitioning_candidate_limit: int tune_3partitioning_candidate_limit: int tune_4partitioning_candidate_limit: int tune_db_limit: float tune_mse_overshoot: float tune_2partition_early_out_limit_factor: float tune_3partition_early_out_limit_factor: float tune_2plane_early_out_limit_correlation: float tune_search_mode0_enable: float # progress_callback: Optional[Callable] def __init__( self, profile: ASTCProfile, block_x: int, block_y: int, block_z: int = 1, quality: Union[float, ASTCQualityPreset] = ASTCQualityPreset.MEDIUM, flags: int = 0, ) -> None: ... class ASTCSwizzle: """A texel component swizzle. Attributes ---------- r : ASTCSwizzleComponentSelector The red component selector. g : ASTCSwizzleComponentSelector The green component selector. b : ASTCSwizzleComponentSelector The blue component selector. a : ASTCSwizzleComponentSelector The alpha component selector. """ r: ASTCSwizzleComponentSelector g: ASTCSwizzleComponentSelector b: ASTCSwizzleComponentSelector a: ASTCSwizzleComponentSelector def __init__( self, r: ASTCSwizzleComponentSelector = ASTCSwizzleComponentSelector.R, g: ASTCSwizzleComponentSelector = ASTCSwizzleComponentSelector.G, b: ASTCSwizzleComponentSelector = ASTCSwizzleComponentSelector.B, a: ASTCSwizzleComponentSelector = ASTCSwizzleComponentSelector.A, ) -> None: ... @classmethod def from_str(cls, swizzle: str) -> ASTCSwizzle: """ Create a swizzle from a string. The string must be 4 characters long, with each character being one of: - r/R: Red component. - g/G: Green component. - b/B: Blue component. - a/A: Alpha component. - 0: always 0 - 1: always 1 - z/Z: Reconstructed normal vector Z component. """ ... class ASTCContext: config: ASTCConfig threads: int def __init__(self, config: ASTCConfig, threads: int = 1) -> None: ... def compress(self, image: ASTCImage, swizzle: ASTCSwizzle) -> bytes: ... def decompress( self, data: bytes, image: ASTCImage, swizzle: ASTCSwizzle ) -> ASTCImage: ... class ASTCError(Exception): pass def compute_error_metrics( compute_hdr_metrics: bool, compute_hdr_rg_metrics: bool, input_components: Literal[0, 1, 2, 3, 4], img1: ASTCImage, img2: ASTCImage, fstop_lo: int, fstop_hi: int, ) -> dict: """Compute error metrics comparing two images. Parameters ---------- compute_hdr_metrics : bool True if HDR metrics should be computed. compute_normal_metrics: bool True if normal map metrics should be computed. input_components : Literal[0, 1, 2, 3, 4] The number of color components in the input images. img1: ASTCImage The original image. img2: ASTCImage The compressed image. fstop_lo: int The low exposure fstop (HDR only). fstop_hi: int The high exposure fstop (HDR only). Returns ------- dict A dictionary with the following keys: - "psnr": The peak signal-to-noise ratio. - "psnr_rgb": The peak signal-to-noise ratio for RGB channels. - "psnr_alpha": The peak signal-to-noise ratio for the alpha channel. - "peak_rgb": The peak value for RGB channels. - "mspnr_rgb": The mean signal-to-noise ratio for RGB channels. (hdr metric) - "log_rgmse_rgb": The log root mean square error for RGB channels. (hdr metric) - "mean_angular_errorsum": The mean angular error. (normal map metric) - "worst_angular_errorsum": The worst angular error. (normal map metric) If a value is -1 it means that this metric was not computed. """ pass __all__ = ( "ASTCConfig", "ASTCContext", "ASTCImage", "ASTCSwizzle", "ASTCError", "compute_error_metrics", )