//! Contains the compression attribute definition //! and methods to compress and decompress data. // private modules make non-breaking changes easier mod zip; mod rle; mod piz; mod pxr24; mod b44; use std::convert::TryInto; use std::mem::size_of; use half::f16; use crate::meta::attribute::{IntegerBounds, SampleType, ChannelList}; use crate::error::{Result, Error, usize_to_i32}; use crate::meta::header::Header; /// A byte vector. pub type ByteVec = Vec; /// A byte slice. pub type Bytes<'s> = &'s [u8]; /// Specifies which compression method to use. /// Use uncompressed data for fastest loading and writing speeds. /// Use RLE compression for fast loading and writing with slight memory savings. /// Use ZIP compression for slow processing with large memory savings. #[derive(Debug, Clone, Copy, PartialEq)] pub enum Compression { /// Store uncompressed values. /// Produces large files that can be read and written very quickly. /// Consider using RLE instead, as it provides some compression with almost equivalent speed. Uncompressed, /// Produces slightly smaller files /// that can still be read and written rather quickly. /// The compressed file size is usually between 60 and 75 percent of the uncompressed size. /// Works best for images with large flat areas, such as masks and abstract graphics. /// This compression method is lossless. RLE, /// Uses ZIP compression to compress each line. Slowly produces small images /// which can be read with moderate speed. This compression method is lossless. /// Might be slightly faster but larger than `ZIP16´. ZIP1, // TODO ZIP { individual_lines: bool, compression_level: Option } // TODO specify zip compression level? /// Uses ZIP compression to compress blocks of 16 lines. Slowly produces small images /// which can be read with moderate speed. This compression method is lossless. /// Might be slightly slower but smaller than `ZIP1´. ZIP16, // TODO collapse with ZIP1 /// PIZ compression works well for noisy and natural images. Works better with larger tiles. /// Only supported for flat images, but not for deep data. /// This compression method is lossless. // A wavelet transform is applied to the pixel data, and the result is Huffman- // encoded. This scheme tends to provide the best compression ratio for the types of // images that are typically processed at Industrial Light & Magic. Files are // compressed and decompressed at roughly the same speed. For photographic // images with film grain, the files are reduced to between 35 and 55 percent of their // uncompressed size. // PIZ compression works well for scan-line based files, and also for tiled files with // large tiles, but small tiles do not shrink much. (PIZ-compressed data start with a // relatively long header; if the input to the compressor is short, adding the header // tends to offset any size reduction of the input.) PIZ, /// Like `ZIP1`, but reduces precision of `f32` images to `f24`. /// Therefore, this is lossless compression for `f16` and `u32` data, lossy compression for `f32` data. /// This compression method works well for depth /// buffers and similar images, where the possible range of values is very large, but /// where full 32-bit floating-point accuracy is not necessary. Rounding improves /// compression significantly by eliminating the pixels' 8 least significant bits, which /// tend to be very noisy, and therefore difficult to compress. /// This produces really small image files. Only supported for flat images, not for deep data. // After reducing 32-bit floating-point data to 24 bits by rounding (while leaving 16-bit // floating-point data unchanged), differences between horizontally adjacent pixels // are compressed with zlib, similar to ZIP. PXR24 compression preserves image // channels of type HALF and UINT exactly, but the relative error of FLOAT data // increases to about ???. PXR24, // TODO specify zip compression level? /// This is a lossy compression method for f16 images. /// It's the predecessor of the `B44A` compression, /// which has improved compression rates for uniformly colored areas. /// You should probably use `B44A` instead of the plain `B44`. /// /// Only supported for flat images, not for deep data. // lossy 4-by-4 pixel block compression, // flat fields are compressed more // Channels of type HALF are split into blocks of four by four pixels or 32 bytes. Each // block is then packed into 14 bytes, reducing the data to 44 percent of their // uncompressed size. When B44 compression is applied to RGB images in // combination with luminance/chroma encoding (see below), the size of the // compressed pixels is about 22 percent of the size of the original RGB data. // Channels of type UINT or FLOAT are not compressed. // Decoding is fast enough to allow real-time playback of B44-compressed OpenEXR // image sequences on commodity hardware. // The size of a B44-compressed file depends on the number of pixels in the image, // but not on the data in the pixels. All images with the same resolution and the same // set of channels have the same size. This can be advantageous for systems that // support real-time playback of image sequences; the predictable file size makes it // easier to allocate space on storage media efficiently. // B44 compression is only supported for flat images. B44, // TODO B44 { optimize_uniform_areas: bool } /// This is a lossy compression method for f16 images. /// All f32 and u32 channels will be stored without compression. /// All the f16 pixels are divided into 4x4 blocks. /// Each block is then compressed as a whole. /// /// The 32 bytes of a block will require only ~14 bytes after compression, /// independent of the actual pixel contents. With chroma subsampling, /// a block will be compressed to ~7 bytes. /// Uniformly colored blocks will be compressed to ~3 bytes. /// /// The 512 bytes of an f32 block will not be compressed at all. /// /// Should be fast enough for realtime playback. /// Only supported for flat images, not for deep data. B44A, // TODO collapse with B44 /// __This lossy compression is not yet supported by this implementation.__ // lossy DCT based compression, in blocks // of 32 scanlines. More efficient for partial buffer access. DWAA(Option), // TODO does this have a default value? make this non optional? default Compression Level setting is 45.0 /// __This lossy compression is not yet supported by this implementation.__ // lossy DCT based compression, in blocks // of 256 scanlines. More efficient space // wise and faster to decode full frames // than DWAA_COMPRESSION. DWAB(Option), // TODO collapse with B44. default Compression Level setting is 45.0 } impl std::fmt::Display for Compression { fn fmt(&self, formatter: &mut std::fmt::Formatter<'_>) -> std::fmt::Result { write!(formatter, "{} compression", match self { Compression::Uncompressed => "no", Compression::RLE => "rle", Compression::ZIP1 => "zip line", Compression::ZIP16 => "zip block", Compression::B44 => "b44", Compression::B44A => "b44a", Compression::DWAA(_) => "dwaa", Compression::DWAB(_) => "dwab", Compression::PIZ => "piz", Compression::PXR24 => "pxr24", }) } } impl Compression { /// Compress the image section of bytes. pub fn compress_image_section(self, header: &Header, uncompressed_native_endian: ByteVec, pixel_section: IntegerBounds) -> Result { let max_tile_size = header.max_block_pixel_size(); assert!(pixel_section.validate(Some(max_tile_size)).is_ok(), "decompress tile coordinate bug"); if header.deep { assert!(self.supports_deep_data()) } use self::Compression::*; let compressed_little_endian = match self { Uncompressed => { return Ok(convert_current_to_little_endian( uncompressed_native_endian, &header.channels, pixel_section )) }, // we need to clone here, because we might have to fallback to the uncompressed data later (when compressed data is larger than raw data) ZIP16 => zip::compress_bytes(&header.channels, uncompressed_native_endian.clone(), pixel_section), ZIP1 => zip::compress_bytes(&header.channels, uncompressed_native_endian.clone(), pixel_section), RLE => rle::compress_bytes(&header.channels, uncompressed_native_endian.clone(), pixel_section), PIZ => piz::compress(&header.channels, uncompressed_native_endian.clone(), pixel_section), PXR24 => pxr24::compress(&header.channels, uncompressed_native_endian.clone(), pixel_section), B44 => b44::compress(&header.channels, uncompressed_native_endian.clone(), pixel_section, false), B44A => b44::compress(&header.channels, uncompressed_native_endian.clone(), pixel_section, true), _ => return Err(Error::unsupported(format!("yet unimplemented compression method: {}", self))) }; let compressed_little_endian = compressed_little_endian.map_err(|_| Error::invalid(format!("pixels cannot be compressed ({})", self)) )?; if self == Uncompressed || compressed_little_endian.len() < uncompressed_native_endian.len() { // only write compressed if it actually is smaller than raw Ok(compressed_little_endian) } else { // if we do not use compression, manually convert uncompressed data Ok(convert_current_to_little_endian(uncompressed_native_endian, &header.channels, pixel_section)) } } /// Decompress the image section of bytes. pub fn decompress_image_section(self, header: &Header, compressed: ByteVec, pixel_section: IntegerBounds, pedantic: bool) -> Result { let max_tile_size = header.max_block_pixel_size(); assert!(pixel_section.validate(Some(max_tile_size)).is_ok(), "decompress tile coordinate bug"); if header.deep { assert!(self.supports_deep_data()) } let expected_byte_size = pixel_section.size.area() * header.channels.bytes_per_pixel; // FIXME this needs to account for subsampling anywhere // note: always true where self == Uncompressed if compressed.len() == expected_byte_size { // the compressed data was larger than the raw data, so the small raw data has been written Ok(convert_little_endian_to_current(compressed, &header.channels, pixel_section)) } else { use self::Compression::*; let bytes = match self { Uncompressed => Ok(convert_little_endian_to_current(compressed, &header.channels, pixel_section)), ZIP16 => zip::decompress_bytes(&header.channels, compressed, pixel_section, expected_byte_size, pedantic), ZIP1 => zip::decompress_bytes(&header.channels, compressed, pixel_section, expected_byte_size, pedantic), RLE => rle::decompress_bytes(&header.channels, compressed, pixel_section, expected_byte_size, pedantic), PIZ => piz::decompress(&header.channels, compressed, pixel_section, expected_byte_size, pedantic), PXR24 => pxr24::decompress(&header.channels, compressed, pixel_section, expected_byte_size, pedantic), B44 | B44A => b44::decompress(&header.channels, compressed, pixel_section, expected_byte_size, pedantic), _ => return Err(Error::unsupported(format!("yet unimplemented compression method: {}", self))) }; // map all errors to compression errors let bytes = bytes .map_err(|decompression_error| match decompression_error { Error::NotSupported(message) => Error::unsupported(format!("yet unimplemented compression special case ({})", message)), error => Error::invalid(format!( "compressed {:?} data ({})", self, error.to_string() )), })?; if bytes.len() != expected_byte_size { Err(Error::invalid("decompressed data")) } else { Ok(bytes) } } } /// For scan line images and deep scan line images, one or more scan lines may be /// stored together as a scan line block. The number of scan lines per block /// depends on how the pixel data are compressed. pub fn scan_lines_per_block(self) -> usize { use self::Compression::*; match self { Uncompressed | RLE | ZIP1 => 1, ZIP16 | PXR24 => 16, PIZ | B44 | B44A | DWAA(_) => 32, DWAB(_) => 256, } } /// Deep data can only be compressed using RLE or ZIP compression. pub fn supports_deep_data(self) -> bool { use self::Compression::*; match self { Uncompressed | RLE | ZIP1 => true, _ => false, } } /// Most compression methods will reconstruct the exact pixel bytes, /// but some might throw away unimportant data for specific types of samples. pub fn is_lossless_for(self, sample_type: SampleType) -> bool { use self::Compression::*; match self { PXR24 => sample_type != SampleType::F32, // pxr reduces f32 to f24 B44 | B44A => sample_type != SampleType::F16, // b44 only compresses f16 values, others are left uncompressed Uncompressed | RLE | ZIP1 | ZIP16 | PIZ => true, DWAB(_) | DWAA(_) => false, } } /// Most compression methods will reconstruct the exact pixel bytes, /// but some might throw away unimportant data in some cases. pub fn may_loose_data(self) -> bool { use self::Compression::*; match self { Uncompressed | RLE | ZIP1 | ZIP16 | PIZ => false, PXR24 | B44 | B44A | DWAB(_) | DWAA(_) => true, } } /// Most compression methods will reconstruct the exact pixel bytes, /// but some might replace NaN with zeroes. pub fn supports_nan(self) -> bool { use self::Compression::*; match self { B44 | B44A | DWAB(_) | DWAA(_) => false, // TODO dwa might support it? _ => true } } } // see https://github.com/AcademySoftwareFoundation/openexr/blob/6a9f8af6e89547bcd370ae3cec2b12849eee0b54/OpenEXR/IlmImf/ImfMisc.cpp#L1456-L1541 #[allow(unused)] // allows the extra parameters to be unused fn convert_current_to_little_endian(mut bytes: ByteVec, channels: &ChannelList, rectangle: IntegerBounds) -> ByteVec { #[cfg(target = "big_endian")] reverse_block_endianness(&mut byte_vec, channels, rectangle); bytes } #[allow(unused)] // allows the extra parameters to be unused fn convert_little_endian_to_current(mut bytes: ByteVec, channels: &ChannelList, rectangle: IntegerBounds) -> ByteVec { #[cfg(target = "big_endian")] reverse_block_endianness(&mut bytes, channels, rectangle); bytes } #[allow(unused)] // unused when on little endian system fn reverse_block_endianness(bytes: &mut [u8], channels: &ChannelList, rectangle: IntegerBounds){ let mut remaining_bytes: &mut [u8] = bytes; for y in rectangle.position.y() .. rectangle.end().y() { for channel in &channels.list { let line_is_subsampled = mod_p(y, usize_to_i32(channel.sampling.y())) != 0; if line_is_subsampled { continue; } let sample_count = rectangle.size.width() / channel.sampling.x(); match channel.sample_type { SampleType::F16 => remaining_bytes = chomp_convert_n::(reverse_2_bytes, remaining_bytes, sample_count), SampleType::F32 => remaining_bytes = chomp_convert_n::(reverse_4_bytes, remaining_bytes, sample_count), SampleType::U32 => remaining_bytes = chomp_convert_n::(reverse_4_bytes, remaining_bytes, sample_count), } } } #[inline] fn chomp_convert_n(convert_single_value: fn(&mut[u8]), mut bytes: &mut [u8], count: usize) -> &mut [u8] { let type_size = size_of::(); let (line_bytes, rest) = bytes.split_at_mut(count * type_size); let value_byte_chunks = line_bytes.chunks_exact_mut(type_size); for value_bytes in value_byte_chunks { convert_single_value(value_bytes); } rest } debug_assert!(remaining_bytes.is_empty(), "not all bytes were converted to little endian"); } #[inline] fn reverse_2_bytes(bytes: &mut [u8]){ // this code seems like it could be optimized easily by the compiler let two_bytes: [u8; 2] = bytes.try_into().expect("invalid byte count"); bytes.copy_from_slice(&[two_bytes[1], two_bytes[0]]); } #[inline] fn reverse_4_bytes(bytes: &mut [u8]){ let four_bytes: [u8; 4] = bytes.try_into().expect("invalid byte count"); bytes.copy_from_slice(&[four_bytes[3], four_bytes[2], four_bytes[1], four_bytes[0]]); } #[inline] fn div_p (x: i32, y: i32) -> i32 { if x >= 0 { if y >= 0 { x / y } else { -(x / -y) } } else { if y >= 0 { -((y-1-x) / y) } else { (-y-1-x) / -y } } } #[inline] fn mod_p(x: i32, y: i32) -> i32 { x - y * div_p(x, y) } /// A collection of functions used to prepare data for compression. mod optimize_bytes { /// Integrate over all differences to the previous value in order to reconstruct sample values. pub fn differences_to_samples(buffer: &mut [u8]) { // The naive implementation is very simple: // // for index in 1..buffer.len() { // buffer[index] = (buffer[index - 1] as i32 + buffer[index] as i32 - 128) as u8; // } // // But we process elements in pairs to take advantage of instruction-level parallelism. // When computations within a pair do not depend on each other, they can be processed in parallel. // Since this function is responsible for a very large chunk of execution time, // this tweak alone improves decoding performance of RLE images by 20%. if let Some(first) = buffer.get(0) { let mut previous = *first as i16; for chunk in &mut buffer[1..].chunks_exact_mut(2) { // no bounds checks here due to indices and chunk size being constant let diff0 = chunk[0] as i16; let diff1 = chunk[1] as i16; // these two computations do not depend on each other, unlike in the naive version, // so they can be executed by the CPU in parallel via instruction-level parallelism let sample0 = (previous + diff0 - 128) as u8; let sample1 = (previous + diff0 + diff1 - 128 * 2) as u8; chunk[0] = sample0; chunk[1] = sample1; previous = sample1 as i16; } // handle the remaining element at the end not processed by the loop over pairs, if present for elem in &mut buffer[1..].chunks_exact_mut(2).into_remainder().iter_mut() { let sample = (previous + *elem as i16 - 128) as u8; *elem = sample; previous = sample as i16; } } } /// Derive over all values in order to produce differences to the previous value. pub fn samples_to_differences(buffer: &mut [u8]){ // naive version: // for index in (1..buffer.len()).rev() { // buffer[index] = (buffer[index] as i32 - buffer[index - 1] as i32 + 128) as u8; // } // // But we process elements in batches to take advantage of autovectorization. // If the target platform has no vector instructions (e.g. 32-bit ARM without `-C target-cpu=native`) // this will instead take advantage of instruction-level parallelism. if let Some(first) = buffer.get(0) { let mut previous = *first as i16; // Chunk size is 16 because we process bytes (8 bits), // and 8*16 = 128 bits is the size of a typical SIMD register. // Even WASM has 128-bit SIMD registers. for chunk in &mut buffer[1..].chunks_exact_mut(16) { // no bounds checks here due to indices and chunk size being constant let sample0 = chunk[0] as i16; let sample1 = chunk[1] as i16; let sample2 = chunk[2] as i16; let sample3 = chunk[3] as i16; let sample4 = chunk[4] as i16; let sample5 = chunk[5] as i16; let sample6 = chunk[6] as i16; let sample7 = chunk[7] as i16; let sample8 = chunk[8] as i16; let sample9 = chunk[9] as i16; let sample10 = chunk[10] as i16; let sample11 = chunk[11] as i16; let sample12 = chunk[12] as i16; let sample13 = chunk[13] as i16; let sample14 = chunk[14] as i16; let sample15 = chunk[15] as i16; // Unlike in decoding, computations in here are truly independent from each other, // which enables the compiler to vectorize this loop. // Even if the target platform has no vector instructions, // so using more parallelism doesn't imply doing more work, // and we're not really limited in how wide we can go. chunk[0] = (sample0 - previous + 128) as u8; chunk[1] = (sample1 - sample0 + 128) as u8; chunk[2] = (sample2 - sample1 + 128) as u8; chunk[3] = (sample3 - sample2 + 128) as u8; chunk[4] = (sample4 - sample3 + 128) as u8; chunk[5] = (sample5 - sample4 + 128) as u8; chunk[6] = (sample6 - sample5 + 128) as u8; chunk[7] = (sample7 - sample6 + 128) as u8; chunk[8] = (sample8 - sample7 + 128) as u8; chunk[9] = (sample9 - sample8 + 128) as u8; chunk[10] = (sample10 - sample9 + 128) as u8; chunk[11] = (sample11 - sample10 + 128) as u8; chunk[12] = (sample12 - sample11 + 128) as u8; chunk[13] = (sample13 - sample12 + 128) as u8; chunk[14] = (sample14 - sample13 + 128) as u8; chunk[15] = (sample15 - sample14 + 128) as u8; previous = sample15; } // Handle the remaining element at the end not processed by the loop over batches, if present // This is what the iterator-based version of this function would look like without vectorization for elem in &mut buffer[1..].chunks_exact_mut(16).into_remainder().iter_mut() { let diff = (*elem as i16 - previous + 128) as u8; previous = *elem as i16; *elem = diff; } } } use std::cell::Cell; thread_local! { // A buffer for reusing between invocations of interleaving and deinterleaving. // Allocating memory is cheap, but zeroing or otherwise initializing it is not. // Doing it hundreds of times (once per block) would be expensive. // This optimization brings down the time spent in interleaving from 15% to 5%. static SCRATCH_SPACE: Cell> = Cell::new(Vec::new()); } fn with_reused_buffer(length: usize, mut func: F) where F: FnMut(&mut [u8]) { SCRATCH_SPACE.with(|scratch_space| { // reuse a buffer if we've already initialized one let mut buffer = scratch_space.take(); if buffer.len() < length { // Efficiently create a zeroed Vec by requesting zeroed memory from the OS. // This is slightly faster than a `memcpy()` plus `memset()` that would happen otherwise, // but is not a big deal either way since it's not a hot codepath. buffer = vec![0u8; length]; } // call the function func(&mut buffer[..length]); // save the internal buffer for reuse scratch_space.set(buffer); }); } /// Interleave the bytes such that the second half of the array is every other byte. pub fn interleave_byte_blocks(separated: &mut [u8]) { with_reused_buffer(separated.len(), |interleaved| { // Split the two halves that we are going to interleave. let (first_half, second_half) = separated.split_at((separated.len() + 1) / 2); // The first half can be 1 byte longer than the second if the length of the input is odd, // but the loop below only processes numbers in pairs. // To handle it, preserve the last element of the first slice, to be handled after the loop. let first_half_last = first_half.last(); // Truncate the first half to match the lenght of the second one; more optimizer-friendly let first_half_iter = &first_half[..second_half.len()]; // Main loop that performs the interleaving for ((first, second), interleaved) in first_half_iter.iter().zip(second_half.iter()) .zip(interleaved.chunks_exact_mut(2)) { // The length of each chunk is known to be 2 at compile time, // and each index is also a constant. // This allows the compiler to remove the bounds checks. interleaved[0] = *first; interleaved[1] = *second; } // If the length of the slice was odd, restore the last element of the first half that we saved if interleaved.len() % 2 == 1 { if let Some(value) = first_half_last { // we can unwrap() here because we just checked that the lenght is non-zero: // `% 2 == 1` will fail for zero *interleaved.last_mut().unwrap() = *value; } } // write out the results separated.copy_from_slice(&interleaved); }); } /// Separate the bytes such that the second half contains every other byte. /// This performs deinterleaving - the inverse of interleaving. pub fn separate_bytes_fragments(source: &mut [u8]) { with_reused_buffer(source.len(), |separated| { // Split the two halves that we are going to interleave. let (first_half, second_half) = separated.split_at_mut((source.len() + 1) / 2); // The first half can be 1 byte longer than the second if the length of the input is odd, // but the loop below only processes numbers in pairs. // To handle it, preserve the last element of the input, to be handled after the loop. let last = source.last(); let first_half_iter = &mut first_half[..second_half.len()]; // Main loop that performs the deinterleaving for ((first, second), interleaved) in first_half_iter.iter_mut().zip(second_half.iter_mut()) .zip(source.chunks_exact(2)) { // The length of each chunk is known to be 2 at compile time, // and each index is also a constant. // This allows the compiler to remove the bounds checks. *first = interleaved[0]; *second = interleaved[1]; } // If the length of the slice was odd, restore the last element of the input that we saved if source.len() % 2 == 1 { if let Some(value) = last { // we can unwrap() here because we just checked that the lenght is non-zero: // `% 2 == 1` will fail for zero *first_half.last_mut().unwrap() = *value; } } // write out the results source.copy_from_slice(&separated); }); } #[cfg(test)] pub mod test { #[test] fn roundtrip_interleave(){ let source = vec![ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 ]; let mut modified = source.clone(); super::separate_bytes_fragments(&mut modified); super::interleave_byte_blocks(&mut modified); assert_eq!(source, modified); } #[test] fn roundtrip_derive(){ let source = vec![ 0, 1, 2, 7, 4, 5, 6, 7, 13, 9, 10 ]; let mut modified = source.clone(); super::samples_to_differences(&mut modified); super::differences_to_samples(&mut modified); assert_eq!(source, modified); } } } #[cfg(test)] pub mod test { use super::*; use crate::meta::attribute::ChannelDescription; use crate::block::samples::IntoNativeSample; #[test] fn roundtrip_endianness_mixed_channels(){ let a32 = ChannelDescription::new("A", SampleType::F32, true); let y16 = ChannelDescription::new("Y", SampleType::F16, true); let channels = ChannelList::new(smallvec![ a32, y16 ]); let data = vec![ 23582740683_f32.to_ne_bytes().as_slice(), 35827420683_f32.to_ne_bytes().as_slice(), 27406832358_f32.to_f16().to_ne_bytes().as_slice(), 74062358283_f32.to_f16().to_ne_bytes().as_slice(), 52582740683_f32.to_ne_bytes().as_slice(), 45827420683_f32.to_ne_bytes().as_slice(), 15406832358_f32.to_f16().to_ne_bytes().as_slice(), 65062358283_f32.to_f16().to_ne_bytes().as_slice(), ].into_iter().flatten().map(|x| *x).collect(); roundtrip_convert_endianness( data, &channels, IntegerBounds::from_dimensions((2, 2)) ); } fn roundtrip_convert_endianness( current_endian: ByteVec, channels: &ChannelList, rectangle: IntegerBounds ){ let little_endian = convert_current_to_little_endian( current_endian.clone(), channels, rectangle ); let current_endian_decoded = convert_little_endian_to_current( little_endian.clone(), channels, rectangle ); assert_eq!(current_endian, current_endian_decoded, "endianness conversion failed"); } }