/* * Copyright 2018 Google Inc. * * Use of this source code is governed by a BSD-style license that can be * found in the LICENSE file. */ #include "skcms.h" #include "skcms_internal.h" #include #include #include #include #include #if defined(__ARM_NEON) #include #elif defined(__SSE__) #include #if defined(__clang__) // That #include is usually enough, but Clang's headers // "helpfully" skip including the whole kitchen sink when _MSC_VER is // defined, because lots of programs on Windows would include that and // it'd be a lot slower. But we want all those headers included so we // can use their features after runtime checks later. #include #include #include #include #include #endif #endif // sizeof(x) will return size_t, which is 32-bit on some machines and 64-bit on others. // We have better testing on 64-bit machines, so force 32-bit machines to behave like 64-bit. // // Please do not use sizeof() directly, and size_t only when required. // (We have no way of enforcing these requests...) #define SAFE_SIZEOF(x) ((uint64_t)sizeof(x)) // Same sort of thing for _Layout structs with a variable sized array at the end (named "variable"). #define SAFE_FIXED_SIZE(type) ((uint64_t)offsetof(type, variable)) static const union { uint32_t bits; float f; } inf_ = { 0x7f800000 }; #define INFINITY_ inf_.f #if defined(__clang__) || defined(__GNUC__) #define small_memcpy __builtin_memcpy #else #define small_memcpy memcpy #endif static float log2f_(float x) { // The first approximation of log2(x) is its exponent 'e', minus 127. int32_t bits; small_memcpy(&bits, &x, sizeof(bits)); float e = (float)bits * (1.0f / (1<<23)); // If we use the mantissa too we can refine the error signficantly. int32_t m_bits = (bits & 0x007fffff) | 0x3f000000; float m; small_memcpy(&m, &m_bits, sizeof(m)); return (e - 124.225514990f - 1.498030302f*m - 1.725879990f/(0.3520887068f + m)); } static float logf_(float x) { const float ln2 = 0.69314718f; return ln2*log2f_(x); } static float exp2f_(float x) { float fract = x - floorf_(x); float fbits = (1.0f * (1<<23)) * (x + 121.274057500f - 1.490129070f*fract + 27.728023300f/(4.84252568f - fract)); // Before we cast fbits to int32_t, check for out of range values to pacify UBSAN. // INT_MAX is not exactly representable as a float, so exclude it as effectively infinite. // INT_MIN is a power of 2 and exactly representable as a float, so it's fine. if (fbits >= (float)INT_MAX) { return INFINITY_; } else if (fbits < (float)INT_MIN) { return -INFINITY_; } int32_t bits = (int32_t)fbits; small_memcpy(&x, &bits, sizeof(x)); return x; } // Not static, as it's used by some test tools. float powf_(float x, float y) { assert (x >= 0); return (x == 0) || (x == 1) ? x : exp2f_(log2f_(x) * y); } static float expf_(float x) { const float log2_e = 1.4426950408889634074f; return exp2f_(log2_e * x); } static float fmaxf_(float x, float y) { return x > y ? x : y; } static float fminf_(float x, float y) { return x < y ? x : y; } static bool isfinitef_(float x) { return 0 == x*0; } static float minus_1_ulp(float x) { int32_t bits; memcpy(&bits, &x, sizeof(bits)); bits = bits - 1; memcpy(&x, &bits, sizeof(bits)); return x; } // Most transfer functions we work with are sRGBish. // For exotic HDR transfer functions, we encode them using a tf.g that makes no sense, // and repurpose the other fields to hold the parameters of the HDR functions. enum TFKind { Bad, sRGBish, PQish, HLGish, HLGinvish }; struct TF_PQish { float A,B,C,D,E,F; }; struct TF_HLGish { float R,G,a,b,c; }; static float TFKind_marker(TFKind kind) { // We'd use different NaNs, but those aren't guaranteed to be preserved by WASM. return -(float)kind; } static TFKind classify(const skcms_TransferFunction& tf, TF_PQish* pq = nullptr , TF_HLGish* hlg = nullptr) { if (tf.g < 0 && (int)tf.g == tf.g) { // TODO: sanity checks for PQ/HLG like we do for sRGBish. switch ((int)tf.g) { case -PQish: if (pq ) { memcpy(pq , &tf.a, sizeof(*pq )); } return PQish; case -HLGish: if (hlg) { memcpy(hlg, &tf.a, sizeof(*hlg)); } return HLGish; case -HLGinvish: if (hlg) { memcpy(hlg, &tf.a, sizeof(*hlg)); } return HLGinvish; } return Bad; } // Basic sanity checks for sRGBish transfer functions. if (isfinitef_(tf.a + tf.b + tf.c + tf.d + tf.e + tf.f + tf.g) // a,c,d,g should be non-negative to make any sense. && tf.a >= 0 && tf.c >= 0 && tf.d >= 0 && tf.g >= 0 // Raising a negative value to a fractional tf->g produces complex numbers. && tf.a * tf.d + tf.b >= 0) { return sRGBish; } return Bad; } bool skcms_TransferFunction_makePQish(skcms_TransferFunction* tf, float A, float B, float C, float D, float E, float F) { *tf = { TFKind_marker(PQish), A,B,C,D,E,F }; assert(classify(*tf) == PQish); return true; } bool skcms_TransferFunction_makeHLGish(skcms_TransferFunction* tf, float R, float G, float a, float b, float c) { *tf = { TFKind_marker(HLGish), R,G, a,b,c, 0 }; assert(classify(*tf) == HLGish); return true; } float skcms_TransferFunction_eval(const skcms_TransferFunction* tf, float x) { float sign = x < 0 ? -1.0f : 1.0f; x *= sign; TF_PQish pq; TF_HLGish hlg; switch (classify(*tf, &pq, &hlg)) { case Bad: break; case HLGish: return sign * (x*hlg.R <= 1 ? powf_(x*hlg.R, hlg.G) : expf_((x-hlg.c)*hlg.a) + hlg.b); // skcms_TransferFunction_invert() inverts R, G, and a for HLGinvish so this math is fast. case HLGinvish: return sign * (x <= 1 ? hlg.R * powf_(x, hlg.G) : hlg.a * logf_(x - hlg.b) + hlg.c); case sRGBish: return sign * (x < tf->d ? tf->c * x + tf->f : powf_(tf->a * x + tf->b, tf->g) + tf->e); case PQish: return sign * powf_(fmaxf_(pq.A + pq.B * powf_(x, pq.C), 0) / (pq.D + pq.E * powf_(x, pq.C)), pq.F); } return 0; } static float eval_curve(const skcms_Curve* curve, float x) { if (curve->table_entries == 0) { return skcms_TransferFunction_eval(&curve->parametric, x); } float ix = fmaxf_(0, fminf_(x, 1)) * (curve->table_entries - 1); int lo = (int) ix , hi = (int)(float)minus_1_ulp(ix + 1.0f); float t = ix - (float)lo; float l, h; if (curve->table_8) { l = curve->table_8[lo] * (1/255.0f); h = curve->table_8[hi] * (1/255.0f); } else { uint16_t be_l, be_h; memcpy(&be_l, curve->table_16 + 2*lo, 2); memcpy(&be_h, curve->table_16 + 2*hi, 2); uint16_t le_l = ((be_l << 8) | (be_l >> 8)) & 0xffff; uint16_t le_h = ((be_h << 8) | (be_h >> 8)) & 0xffff; l = le_l * (1/65535.0f); h = le_h * (1/65535.0f); } return l + (h-l)*t; } float skcms_MaxRoundtripError(const skcms_Curve* curve, const skcms_TransferFunction* inv_tf) { uint32_t N = curve->table_entries > 256 ? curve->table_entries : 256; const float dx = 1.0f / (N - 1); float err = 0; for (uint32_t i = 0; i < N; i++) { float x = i * dx, y = eval_curve(curve, x); err = fmaxf_(err, fabsf_(x - skcms_TransferFunction_eval(inv_tf, y))); } return err; } bool skcms_AreApproximateInverses(const skcms_Curve* curve, const skcms_TransferFunction* inv_tf) { return skcms_MaxRoundtripError(curve, inv_tf) < (1/512.0f); } // Additional ICC signature values that are only used internally enum { // File signature skcms_Signature_acsp = 0x61637370, // Tag signatures skcms_Signature_rTRC = 0x72545243, skcms_Signature_gTRC = 0x67545243, skcms_Signature_bTRC = 0x62545243, skcms_Signature_kTRC = 0x6B545243, skcms_Signature_rXYZ = 0x7258595A, skcms_Signature_gXYZ = 0x6758595A, skcms_Signature_bXYZ = 0x6258595A, skcms_Signature_A2B0 = 0x41324230, skcms_Signature_A2B1 = 0x41324231, skcms_Signature_mAB = 0x6D414220, skcms_Signature_CHAD = 0x63686164, skcms_Signature_WTPT = 0x77747074, // Type signatures skcms_Signature_curv = 0x63757276, skcms_Signature_mft1 = 0x6D667431, skcms_Signature_mft2 = 0x6D667432, skcms_Signature_para = 0x70617261, skcms_Signature_sf32 = 0x73663332, // XYZ is also a PCS signature, so it's defined in skcms.h // skcms_Signature_XYZ = 0x58595A20, }; static uint16_t read_big_u16(const uint8_t* ptr) { uint16_t be; memcpy(&be, ptr, sizeof(be)); #if defined(_MSC_VER) return _byteswap_ushort(be); #else return __builtin_bswap16(be); #endif } static uint32_t read_big_u32(const uint8_t* ptr) { uint32_t be; memcpy(&be, ptr, sizeof(be)); #if defined(_MSC_VER) return _byteswap_ulong(be); #else return __builtin_bswap32(be); #endif } static int32_t read_big_i32(const uint8_t* ptr) { return (int32_t)read_big_u32(ptr); } static float read_big_fixed(const uint8_t* ptr) { return read_big_i32(ptr) * (1.0f / 65536.0f); } // Maps to an in-memory profile so that fields line up to the locations specified // in ICC.1:2010, section 7.2 typedef struct { uint8_t size [ 4]; uint8_t cmm_type [ 4]; uint8_t version [ 4]; uint8_t profile_class [ 4]; uint8_t data_color_space [ 4]; uint8_t pcs [ 4]; uint8_t creation_date_time [12]; uint8_t signature [ 4]; uint8_t platform [ 4]; uint8_t flags [ 4]; uint8_t device_manufacturer [ 4]; uint8_t device_model [ 4]; uint8_t device_attributes [ 8]; uint8_t rendering_intent [ 4]; uint8_t illuminant_X [ 4]; uint8_t illuminant_Y [ 4]; uint8_t illuminant_Z [ 4]; uint8_t creator [ 4]; uint8_t profile_id [16]; uint8_t reserved [28]; uint8_t tag_count [ 4]; // Technically not part of header, but required } header_Layout; typedef struct { uint8_t signature [4]; uint8_t offset [4]; uint8_t size [4]; } tag_Layout; static const tag_Layout* get_tag_table(const skcms_ICCProfile* profile) { return (const tag_Layout*)(profile->buffer + SAFE_SIZEOF(header_Layout)); } // s15Fixed16ArrayType is technically variable sized, holding N values. However, the only valid // use of the type is for the CHAD tag that stores exactly nine values. typedef struct { uint8_t type [ 4]; uint8_t reserved [ 4]; uint8_t values [36]; } sf32_Layout; bool skcms_GetCHAD(const skcms_ICCProfile* profile, skcms_Matrix3x3* m) { skcms_ICCTag tag; if (!skcms_GetTagBySignature(profile, skcms_Signature_CHAD, &tag)) { return false; } if (tag.type != skcms_Signature_sf32 || tag.size < SAFE_SIZEOF(sf32_Layout)) { return false; } const sf32_Layout* sf32Tag = (const sf32_Layout*)tag.buf; const uint8_t* values = sf32Tag->values; for (int r = 0; r < 3; ++r) for (int c = 0; c < 3; ++c, values += 4) { m->vals[r][c] = read_big_fixed(values); } return true; } // XYZType is technically variable sized, holding N XYZ triples. However, the only valid uses of // the type are for tags/data that store exactly one triple. typedef struct { uint8_t type [4]; uint8_t reserved [4]; uint8_t X [4]; uint8_t Y [4]; uint8_t Z [4]; } XYZ_Layout; static bool read_tag_xyz(const skcms_ICCTag* tag, float* x, float* y, float* z) { if (tag->type != skcms_Signature_XYZ || tag->size < SAFE_SIZEOF(XYZ_Layout)) { return false; } const XYZ_Layout* xyzTag = (const XYZ_Layout*)tag->buf; *x = read_big_fixed(xyzTag->X); *y = read_big_fixed(xyzTag->Y); *z = read_big_fixed(xyzTag->Z); return true; } bool skcms_GetWTPT(const skcms_ICCProfile* profile, float xyz[3]) { skcms_ICCTag tag; return skcms_GetTagBySignature(profile, skcms_Signature_WTPT, &tag) && read_tag_xyz(&tag, &xyz[0], &xyz[1], &xyz[2]); } static bool read_to_XYZD50(const skcms_ICCTag* rXYZ, const skcms_ICCTag* gXYZ, const skcms_ICCTag* bXYZ, skcms_Matrix3x3* toXYZ) { return read_tag_xyz(rXYZ, &toXYZ->vals[0][0], &toXYZ->vals[1][0], &toXYZ->vals[2][0]) && read_tag_xyz(gXYZ, &toXYZ->vals[0][1], &toXYZ->vals[1][1], &toXYZ->vals[2][1]) && read_tag_xyz(bXYZ, &toXYZ->vals[0][2], &toXYZ->vals[1][2], &toXYZ->vals[2][2]); } typedef struct { uint8_t type [4]; uint8_t reserved_a [4]; uint8_t function_type [2]; uint8_t reserved_b [2]; uint8_t variable [1/*variable*/]; // 1, 3, 4, 5, or 7 s15.16, depending on function_type } para_Layout; static bool read_curve_para(const uint8_t* buf, uint32_t size, skcms_Curve* curve, uint32_t* curve_size) { if (size < SAFE_FIXED_SIZE(para_Layout)) { return false; } const para_Layout* paraTag = (const para_Layout*)buf; enum { kG = 0, kGAB = 1, kGABC = 2, kGABCD = 3, kGABCDEF = 4 }; uint16_t function_type = read_big_u16(paraTag->function_type); if (function_type > kGABCDEF) { return false; } static const uint32_t curve_bytes[] = { 4, 12, 16, 20, 28 }; if (size < SAFE_FIXED_SIZE(para_Layout) + curve_bytes[function_type]) { return false; } if (curve_size) { *curve_size = SAFE_FIXED_SIZE(para_Layout) + curve_bytes[function_type]; } curve->table_entries = 0; curve->parametric.a = 1.0f; curve->parametric.b = 0.0f; curve->parametric.c = 0.0f; curve->parametric.d = 0.0f; curve->parametric.e = 0.0f; curve->parametric.f = 0.0f; curve->parametric.g = read_big_fixed(paraTag->variable); switch (function_type) { case kGAB: curve->parametric.a = read_big_fixed(paraTag->variable + 4); curve->parametric.b = read_big_fixed(paraTag->variable + 8); if (curve->parametric.a == 0) { return false; } curve->parametric.d = -curve->parametric.b / curve->parametric.a; break; case kGABC: curve->parametric.a = read_big_fixed(paraTag->variable + 4); curve->parametric.b = read_big_fixed(paraTag->variable + 8); curve->parametric.e = read_big_fixed(paraTag->variable + 12); if (curve->parametric.a == 0) { return false; } curve->parametric.d = -curve->parametric.b / curve->parametric.a; curve->parametric.f = curve->parametric.e; break; case kGABCD: curve->parametric.a = read_big_fixed(paraTag->variable + 4); curve->parametric.b = read_big_fixed(paraTag->variable + 8); curve->parametric.c = read_big_fixed(paraTag->variable + 12); curve->parametric.d = read_big_fixed(paraTag->variable + 16); break; case kGABCDEF: curve->parametric.a = read_big_fixed(paraTag->variable + 4); curve->parametric.b = read_big_fixed(paraTag->variable + 8); curve->parametric.c = read_big_fixed(paraTag->variable + 12); curve->parametric.d = read_big_fixed(paraTag->variable + 16); curve->parametric.e = read_big_fixed(paraTag->variable + 20); curve->parametric.f = read_big_fixed(paraTag->variable + 24); break; } return classify(curve->parametric) == sRGBish; } typedef struct { uint8_t type [4]; uint8_t reserved [4]; uint8_t value_count [4]; uint8_t variable [1/*variable*/]; // value_count, 8.8 if 1, uint16 (n*65535) if > 1 } curv_Layout; static bool read_curve_curv(const uint8_t* buf, uint32_t size, skcms_Curve* curve, uint32_t* curve_size) { if (size < SAFE_FIXED_SIZE(curv_Layout)) { return false; } const curv_Layout* curvTag = (const curv_Layout*)buf; uint32_t value_count = read_big_u32(curvTag->value_count); if (size < SAFE_FIXED_SIZE(curv_Layout) + value_count * SAFE_SIZEOF(uint16_t)) { return false; } if (curve_size) { *curve_size = SAFE_FIXED_SIZE(curv_Layout) + value_count * SAFE_SIZEOF(uint16_t); } if (value_count < 2) { curve->table_entries = 0; curve->parametric.a = 1.0f; curve->parametric.b = 0.0f; curve->parametric.c = 0.0f; curve->parametric.d = 0.0f; curve->parametric.e = 0.0f; curve->parametric.f = 0.0f; if (value_count == 0) { // Empty tables are a shorthand for an identity curve curve->parametric.g = 1.0f; } else { // Single entry tables are a shorthand for simple gamma curve->parametric.g = read_big_u16(curvTag->variable) * (1.0f / 256.0f); } } else { curve->table_8 = nullptr; curve->table_16 = curvTag->variable; curve->table_entries = value_count; } return true; } // Parses both curveType and parametricCurveType data. Ensures that at most 'size' bytes are read. // If curve_size is not nullptr, writes the number of bytes used by the curve in (*curve_size). static bool read_curve(const uint8_t* buf, uint32_t size, skcms_Curve* curve, uint32_t* curve_size) { if (!buf || size < 4 || !curve) { return false; } uint32_t type = read_big_u32(buf); if (type == skcms_Signature_para) { return read_curve_para(buf, size, curve, curve_size); } else if (type == skcms_Signature_curv) { return read_curve_curv(buf, size, curve, curve_size); } return false; } // mft1 and mft2 share a large chunk of data typedef struct { uint8_t type [ 4]; uint8_t reserved_a [ 4]; uint8_t input_channels [ 1]; uint8_t output_channels [ 1]; uint8_t grid_points [ 1]; uint8_t reserved_b [ 1]; uint8_t matrix [36]; } mft_CommonLayout; typedef struct { mft_CommonLayout common [1]; uint8_t variable [1/*variable*/]; } mft1_Layout; typedef struct { mft_CommonLayout common [1]; uint8_t input_table_entries [2]; uint8_t output_table_entries [2]; uint8_t variable [1/*variable*/]; } mft2_Layout; static bool read_mft_common(const mft_CommonLayout* mftTag, skcms_A2B* a2b) { // MFT matrices are applied before the first set of curves, but must be identity unless the // input is PCSXYZ. We don't support PCSXYZ profiles, so we ignore this matrix. Note that the // matrix in skcms_A2B is applied later in the pipe, so supporting this would require another // field/flag. a2b->matrix_channels = 0; a2b->input_channels = mftTag->input_channels[0]; a2b->output_channels = mftTag->output_channels[0]; // We require exactly three (ie XYZ/Lab/RGB) output channels if (a2b->output_channels != ARRAY_COUNT(a2b->output_curves)) { return false; } // We require at least one, and no more than four (ie CMYK) input channels if (a2b->input_channels < 1 || a2b->input_channels > ARRAY_COUNT(a2b->input_curves)) { return false; } for (uint32_t i = 0; i < a2b->input_channels; ++i) { a2b->grid_points[i] = mftTag->grid_points[0]; } // The grid only makes sense with at least two points along each axis if (a2b->grid_points[0] < 2) { return false; } return true; } static bool init_a2b_tables(const uint8_t* table_base, uint64_t max_tables_len, uint32_t byte_width, uint32_t input_table_entries, uint32_t output_table_entries, skcms_A2B* a2b) { // byte_width is 1 or 2, [input|output]_table_entries are in [2, 4096], so no overflow uint32_t byte_len_per_input_table = input_table_entries * byte_width; uint32_t byte_len_per_output_table = output_table_entries * byte_width; // [input|output]_channels are <= 4, so still no overflow uint32_t byte_len_all_input_tables = a2b->input_channels * byte_len_per_input_table; uint32_t byte_len_all_output_tables = a2b->output_channels * byte_len_per_output_table; uint64_t grid_size = a2b->output_channels * byte_width; for (uint32_t axis = 0; axis < a2b->input_channels; ++axis) { grid_size *= a2b->grid_points[axis]; } if (max_tables_len < byte_len_all_input_tables + grid_size + byte_len_all_output_tables) { return false; } for (uint32_t i = 0; i < a2b->input_channels; ++i) { a2b->input_curves[i].table_entries = input_table_entries; if (byte_width == 1) { a2b->input_curves[i].table_8 = table_base + i * byte_len_per_input_table; a2b->input_curves[i].table_16 = nullptr; } else { a2b->input_curves[i].table_8 = nullptr; a2b->input_curves[i].table_16 = table_base + i * byte_len_per_input_table; } } if (byte_width == 1) { a2b->grid_8 = table_base + byte_len_all_input_tables; a2b->grid_16 = nullptr; } else { a2b->grid_8 = nullptr; a2b->grid_16 = table_base + byte_len_all_input_tables; } const uint8_t* output_table_base = table_base + byte_len_all_input_tables + grid_size; for (uint32_t i = 0; i < a2b->output_channels; ++i) { a2b->output_curves[i].table_entries = output_table_entries; if (byte_width == 1) { a2b->output_curves[i].table_8 = output_table_base + i * byte_len_per_output_table; a2b->output_curves[i].table_16 = nullptr; } else { a2b->output_curves[i].table_8 = nullptr; a2b->output_curves[i].table_16 = output_table_base + i * byte_len_per_output_table; } } return true; } static bool read_tag_mft1(const skcms_ICCTag* tag, skcms_A2B* a2b) { if (tag->size < SAFE_FIXED_SIZE(mft1_Layout)) { return false; } const mft1_Layout* mftTag = (const mft1_Layout*)tag->buf; if (!read_mft_common(mftTag->common, a2b)) { return false; } uint32_t input_table_entries = 256; uint32_t output_table_entries = 256; return init_a2b_tables(mftTag->variable, tag->size - SAFE_FIXED_SIZE(mft1_Layout), 1, input_table_entries, output_table_entries, a2b); } static bool read_tag_mft2(const skcms_ICCTag* tag, skcms_A2B* a2b) { if (tag->size < SAFE_FIXED_SIZE(mft2_Layout)) { return false; } const mft2_Layout* mftTag = (const mft2_Layout*)tag->buf; if (!read_mft_common(mftTag->common, a2b)) { return false; } uint32_t input_table_entries = read_big_u16(mftTag->input_table_entries); uint32_t output_table_entries = read_big_u16(mftTag->output_table_entries); // ICC spec mandates that 2 <= table_entries <= 4096 if (input_table_entries < 2 || input_table_entries > 4096 || output_table_entries < 2 || output_table_entries > 4096) { return false; } return init_a2b_tables(mftTag->variable, tag->size - SAFE_FIXED_SIZE(mft2_Layout), 2, input_table_entries, output_table_entries, a2b); } static bool read_curves(const uint8_t* buf, uint32_t size, uint32_t curve_offset, uint32_t num_curves, skcms_Curve* curves) { for (uint32_t i = 0; i < num_curves; ++i) { if (curve_offset > size) { return false; } uint32_t curve_bytes; if (!read_curve(buf + curve_offset, size - curve_offset, &curves[i], &curve_bytes)) { return false; } if (curve_bytes > UINT32_MAX - 3) { return false; } curve_bytes = (curve_bytes + 3) & ~3U; uint64_t new_offset_64 = (uint64_t)curve_offset + curve_bytes; curve_offset = (uint32_t)new_offset_64; if (new_offset_64 != curve_offset) { return false; } } return true; } typedef struct { uint8_t type [ 4]; uint8_t reserved_a [ 4]; uint8_t input_channels [ 1]; uint8_t output_channels [ 1]; uint8_t reserved_b [ 2]; uint8_t b_curve_offset [ 4]; uint8_t matrix_offset [ 4]; uint8_t m_curve_offset [ 4]; uint8_t clut_offset [ 4]; uint8_t a_curve_offset [ 4]; } mAB_Layout; typedef struct { uint8_t grid_points [16]; uint8_t grid_byte_width [ 1]; uint8_t reserved [ 3]; uint8_t variable [1/*variable*/]; } mABCLUT_Layout; static bool read_tag_mab(const skcms_ICCTag* tag, skcms_A2B* a2b, bool pcs_is_xyz) { if (tag->size < SAFE_SIZEOF(mAB_Layout)) { return false; } const mAB_Layout* mABTag = (const mAB_Layout*)tag->buf; a2b->input_channels = mABTag->input_channels[0]; a2b->output_channels = mABTag->output_channels[0]; // We require exactly three (ie XYZ/Lab/RGB) output channels if (a2b->output_channels != ARRAY_COUNT(a2b->output_curves)) { return false; } // We require no more than four (ie CMYK) input channels if (a2b->input_channels > ARRAY_COUNT(a2b->input_curves)) { return false; } uint32_t b_curve_offset = read_big_u32(mABTag->b_curve_offset); uint32_t matrix_offset = read_big_u32(mABTag->matrix_offset); uint32_t m_curve_offset = read_big_u32(mABTag->m_curve_offset); uint32_t clut_offset = read_big_u32(mABTag->clut_offset); uint32_t a_curve_offset = read_big_u32(mABTag->a_curve_offset); // "B" curves must be present if (0 == b_curve_offset) { return false; } if (!read_curves(tag->buf, tag->size, b_curve_offset, a2b->output_channels, a2b->output_curves)) { return false; } // "M" curves and Matrix must be used together if (0 != m_curve_offset) { if (0 == matrix_offset) { return false; } a2b->matrix_channels = a2b->output_channels; if (!read_curves(tag->buf, tag->size, m_curve_offset, a2b->matrix_channels, a2b->matrix_curves)) { return false; } // Read matrix, which is stored as a row-major 3x3, followed by the fourth column if (tag->size < matrix_offset + 12 * SAFE_SIZEOF(uint32_t)) { return false; } float encoding_factor = pcs_is_xyz ? 65535 / 32768.0f : 1.0f; const uint8_t* mtx_buf = tag->buf + matrix_offset; a2b->matrix.vals[0][0] = encoding_factor * read_big_fixed(mtx_buf + 0); a2b->matrix.vals[0][1] = encoding_factor * read_big_fixed(mtx_buf + 4); a2b->matrix.vals[0][2] = encoding_factor * read_big_fixed(mtx_buf + 8); a2b->matrix.vals[1][0] = encoding_factor * read_big_fixed(mtx_buf + 12); a2b->matrix.vals[1][1] = encoding_factor * read_big_fixed(mtx_buf + 16); a2b->matrix.vals[1][2] = encoding_factor * read_big_fixed(mtx_buf + 20); a2b->matrix.vals[2][0] = encoding_factor * read_big_fixed(mtx_buf + 24); a2b->matrix.vals[2][1] = encoding_factor * read_big_fixed(mtx_buf + 28); a2b->matrix.vals[2][2] = encoding_factor * read_big_fixed(mtx_buf + 32); a2b->matrix.vals[0][3] = encoding_factor * read_big_fixed(mtx_buf + 36); a2b->matrix.vals[1][3] = encoding_factor * read_big_fixed(mtx_buf + 40); a2b->matrix.vals[2][3] = encoding_factor * read_big_fixed(mtx_buf + 44); } else { if (0 != matrix_offset) { return false; } a2b->matrix_channels = 0; } // "A" curves and CLUT must be used together if (0 != a_curve_offset) { if (0 == clut_offset) { return false; } if (!read_curves(tag->buf, tag->size, a_curve_offset, a2b->input_channels, a2b->input_curves)) { return false; } if (tag->size < clut_offset + SAFE_FIXED_SIZE(mABCLUT_Layout)) { return false; } const mABCLUT_Layout* clut = (const mABCLUT_Layout*)(tag->buf + clut_offset); if (clut->grid_byte_width[0] == 1) { a2b->grid_8 = clut->variable; a2b->grid_16 = nullptr; } else if (clut->grid_byte_width[0] == 2) { a2b->grid_8 = nullptr; a2b->grid_16 = clut->variable; } else { return false; } uint64_t grid_size = a2b->output_channels * clut->grid_byte_width[0]; for (uint32_t i = 0; i < a2b->input_channels; ++i) { a2b->grid_points[i] = clut->grid_points[i]; // The grid only makes sense with at least two points along each axis if (a2b->grid_points[i] < 2) { return false; } grid_size *= a2b->grid_points[i]; } if (tag->size < clut_offset + SAFE_FIXED_SIZE(mABCLUT_Layout) + grid_size) { return false; } } else { if (0 != clut_offset) { return false; } // If there is no CLUT, the number of input and output channels must match if (a2b->input_channels != a2b->output_channels) { return false; } // Zero out the number of input channels to signal that we're skipping this stage a2b->input_channels = 0; } return true; } // If you pass f, we'll fit a possibly-non-zero value for *f. // If you pass nullptr, we'll assume you want *f to be treated as zero. static int fit_linear(const skcms_Curve* curve, int N, float tol, float* c, float* d, float* f = nullptr) { assert(N > 1); // We iteratively fit the first points to the TF's linear piece. // We want the cx + f line to pass through the first and last points we fit exactly. // // As we walk along the points we find the minimum and maximum slope of the line before the // error would exceed our tolerance. We stop when the range [slope_min, slope_max] becomes // emtpy, when we definitely can't add any more points. // // Some points' error intervals may intersect the running interval but not lie fully // within it. So we keep track of the last point we saw that is a valid end point candidate, // and once the search is done, back up to build the line through *that* point. const float dx = 1.0f / (N - 1); int lin_points = 1; float f_zero = 0.0f; if (f) { *f = eval_curve(curve, 0); } else { f = &f_zero; } float slope_min = -INFINITY_; float slope_max = +INFINITY_; for (int i = 1; i < N; ++i) { float x = i * dx; float y = eval_curve(curve, x); float slope_max_i = (y + tol - *f) / x, slope_min_i = (y - tol - *f) / x; if (slope_max_i < slope_min || slope_max < slope_min_i) { // Slope intervals would no longer overlap. break; } slope_max = fminf_(slope_max, slope_max_i); slope_min = fmaxf_(slope_min, slope_min_i); float cur_slope = (y - *f) / x; if (slope_min <= cur_slope && cur_slope <= slope_max) { lin_points = i + 1; *c = cur_slope; } } // Set D to the last point that met our tolerance. *d = (lin_points - 1) * dx; return lin_points; } static bool read_a2b(const skcms_ICCTag* tag, skcms_A2B* a2b, bool pcs_is_xyz) { bool ok = false; if (tag->type == skcms_Signature_mft1) { ok = read_tag_mft1(tag, a2b); } else if (tag->type == skcms_Signature_mft2) { ok = read_tag_mft2(tag, a2b); } else if (tag->type == skcms_Signature_mAB) { ok = read_tag_mab(tag, a2b, pcs_is_xyz); } if (!ok) { return false; } // Detect and canonicalize identity tables. skcms_Curve* curves[] = { a2b->input_channels > 0 ? a2b->input_curves + 0 : nullptr, a2b->input_channels > 1 ? a2b->input_curves + 1 : nullptr, a2b->input_channels > 2 ? a2b->input_curves + 2 : nullptr, a2b->input_channels > 3 ? a2b->input_curves + 3 : nullptr, a2b->matrix_channels > 0 ? a2b->matrix_curves + 0 : nullptr, a2b->matrix_channels > 1 ? a2b->matrix_curves + 1 : nullptr, a2b->matrix_channels > 2 ? a2b->matrix_curves + 2 : nullptr, a2b->output_channels > 0 ? a2b->output_curves + 0 : nullptr, a2b->output_channels > 1 ? a2b->output_curves + 1 : nullptr, a2b->output_channels > 2 ? a2b->output_curves + 2 : nullptr, }; for (int i = 0; i < ARRAY_COUNT(curves); i++) { skcms_Curve* curve = curves[i]; if (curve && curve->table_entries && curve->table_entries <= (uint32_t)INT_MAX) { int N = (int)curve->table_entries; float c = 0.0f, d = 0.0f, f = 0.0f; if (N == fit_linear(curve, N, 1.0f/(2*N), &c,&d,&f) && c == 1.0f && f == 0.0f) { curve->table_entries = 0; curve->table_8 = nullptr; curve->table_16 = nullptr; curve->parametric = skcms_TransferFunction{1,1,0,0,0,0,0}; } } } return true; } void skcms_GetTagByIndex(const skcms_ICCProfile* profile, uint32_t idx, skcms_ICCTag* tag) { if (!profile || !profile->buffer || !tag) { return; } if (idx > profile->tag_count) { return; } const tag_Layout* tags = get_tag_table(profile); tag->signature = read_big_u32(tags[idx].signature); tag->size = read_big_u32(tags[idx].size); tag->buf = read_big_u32(tags[idx].offset) + profile->buffer; tag->type = read_big_u32(tag->buf); } bool skcms_GetTagBySignature(const skcms_ICCProfile* profile, uint32_t sig, skcms_ICCTag* tag) { if (!profile || !profile->buffer || !tag) { return false; } const tag_Layout* tags = get_tag_table(profile); for (uint32_t i = 0; i < profile->tag_count; ++i) { if (read_big_u32(tags[i].signature) == sig) { tag->signature = sig; tag->size = read_big_u32(tags[i].size); tag->buf = read_big_u32(tags[i].offset) + profile->buffer; tag->type = read_big_u32(tag->buf); return true; } } return false; } static bool usable_as_src(const skcms_ICCProfile* profile) { return profile->has_A2B || (profile->has_trc && profile->has_toXYZD50); } bool skcms_Parse(const void* buf, size_t len, skcms_ICCProfile* profile) { assert(SAFE_SIZEOF(header_Layout) == 132); if (!profile) { return false; } memset(profile, 0, SAFE_SIZEOF(*profile)); if (len < SAFE_SIZEOF(header_Layout)) { return false; } // Byte-swap all header fields const header_Layout* header = (const header_Layout*)buf; profile->buffer = (const uint8_t*)buf; profile->size = read_big_u32(header->size); uint32_t version = read_big_u32(header->version); profile->data_color_space = read_big_u32(header->data_color_space); profile->pcs = read_big_u32(header->pcs); uint32_t signature = read_big_u32(header->signature); float illuminant_X = read_big_fixed(header->illuminant_X); float illuminant_Y = read_big_fixed(header->illuminant_Y); float illuminant_Z = read_big_fixed(header->illuminant_Z); profile->tag_count = read_big_u32(header->tag_count); // Validate signature, size (smaller than buffer, large enough to hold tag table), // and major version uint64_t tag_table_size = profile->tag_count * SAFE_SIZEOF(tag_Layout); if (signature != skcms_Signature_acsp || profile->size > len || profile->size < SAFE_SIZEOF(header_Layout) + tag_table_size || (version >> 24) > 4) { return false; } // Validate that illuminant is D50 white if (fabsf_(illuminant_X - 0.9642f) > 0.0100f || fabsf_(illuminant_Y - 1.0000f) > 0.0100f || fabsf_(illuminant_Z - 0.8249f) > 0.0100f) { return false; } // Validate that all tag entries have sane offset + size const tag_Layout* tags = get_tag_table(profile); for (uint32_t i = 0; i < profile->tag_count; ++i) { uint32_t tag_offset = read_big_u32(tags[i].offset); uint32_t tag_size = read_big_u32(tags[i].size); uint64_t tag_end = (uint64_t)tag_offset + (uint64_t)tag_size; if (tag_size < 4 || tag_end > profile->size) { return false; } } if (profile->pcs != skcms_Signature_XYZ && profile->pcs != skcms_Signature_Lab) { return false; } bool pcs_is_xyz = profile->pcs == skcms_Signature_XYZ; // Pre-parse commonly used tags. skcms_ICCTag kTRC; if (profile->data_color_space == skcms_Signature_Gray && skcms_GetTagBySignature(profile, skcms_Signature_kTRC, &kTRC)) { if (!read_curve(kTRC.buf, kTRC.size, &profile->trc[0], nullptr)) { // Malformed tag return false; } profile->trc[1] = profile->trc[0]; profile->trc[2] = profile->trc[0]; profile->has_trc = true; if (pcs_is_xyz) { profile->toXYZD50.vals[0][0] = illuminant_X; profile->toXYZD50.vals[1][1] = illuminant_Y; profile->toXYZD50.vals[2][2] = illuminant_Z; profile->has_toXYZD50 = true; } } else { skcms_ICCTag rTRC, gTRC, bTRC; if (skcms_GetTagBySignature(profile, skcms_Signature_rTRC, &rTRC) && skcms_GetTagBySignature(profile, skcms_Signature_gTRC, &gTRC) && skcms_GetTagBySignature(profile, skcms_Signature_bTRC, &bTRC)) { if (!read_curve(rTRC.buf, rTRC.size, &profile->trc[0], nullptr) || !read_curve(gTRC.buf, gTRC.size, &profile->trc[1], nullptr) || !read_curve(bTRC.buf, bTRC.size, &profile->trc[2], nullptr)) { // Malformed TRC tags return false; } profile->has_trc = true; } skcms_ICCTag rXYZ, gXYZ, bXYZ; if (skcms_GetTagBySignature(profile, skcms_Signature_rXYZ, &rXYZ) && skcms_GetTagBySignature(profile, skcms_Signature_gXYZ, &gXYZ) && skcms_GetTagBySignature(profile, skcms_Signature_bXYZ, &bXYZ)) { if (!read_to_XYZD50(&rXYZ, &gXYZ, &bXYZ, &profile->toXYZD50)) { // Malformed XYZ tags return false; } profile->has_toXYZD50 = true; } } skcms_ICCTag a2b_tag; // For now, we're preferring A2B0, like Skia does and the ICC spec tells us to. // TODO: prefer A2B1 (relative colormetric) over A2B0 (perceptual)? // This breaks with the ICC spec, but we think it's a good idea, given that TRC curves // and all our known users are thinking exclusively in terms of relative colormetric. const uint32_t sigs[] = { skcms_Signature_A2B0, skcms_Signature_A2B1 }; for (int i = 0; i < ARRAY_COUNT(sigs); i++) { if (skcms_GetTagBySignature(profile, sigs[i], &a2b_tag)) { if (!read_a2b(&a2b_tag, &profile->A2B, pcs_is_xyz)) { // Malformed A2B tag return false; } profile->has_A2B = true; break; } } return usable_as_src(profile); } const skcms_ICCProfile* skcms_sRGB_profile() { static const skcms_ICCProfile sRGB_profile = { nullptr, // buffer, moot here 0, // size, moot here skcms_Signature_RGB, // data_color_space skcms_Signature_XYZ, // pcs 0, // tag count, moot here // We choose to represent sRGB with its canonical transfer function, // and with its canonical XYZD50 gamut matrix. true, // has_trc, followed by the 3 trc curves { {{0, {2.4f, (float)(1/1.055), (float)(0.055/1.055), (float)(1/12.92), 0.04045f, 0, 0}}}, {{0, {2.4f, (float)(1/1.055), (float)(0.055/1.055), (float)(1/12.92), 0.04045f, 0, 0}}}, {{0, {2.4f, (float)(1/1.055), (float)(0.055/1.055), (float)(1/12.92), 0.04045f, 0, 0}}}, }, true, // has_toXYZD50, followed by 3x3 toXYZD50 matrix {{ { 0.436065674f, 0.385147095f, 0.143066406f }, { 0.222488403f, 0.716873169f, 0.060607910f }, { 0.013916016f, 0.097076416f, 0.714096069f }, }}, false, // has_A2B, followed by a2b itself which we don't care about. { 0, { {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, }, {0,0,0,0}, nullptr, nullptr, 0, { {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, }, {{ { 0,0,0,0 }, { 0,0,0,0 }, { 0,0,0,0 }, }}, 0, { {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, }, }, }; return &sRGB_profile; } const skcms_ICCProfile* skcms_XYZD50_profile() { // Just like sRGB above, but with identity transfer functions and toXYZD50 matrix. static const skcms_ICCProfile XYZD50_profile = { nullptr, // buffer, moot here 0, // size, moot here skcms_Signature_RGB, // data_color_space skcms_Signature_XYZ, // pcs 0, // tag count, moot here true, // has_trc, followed by the 3 trc curves { {{0, {1,1, 0,0,0,0,0}}}, {{0, {1,1, 0,0,0,0,0}}}, {{0, {1,1, 0,0,0,0,0}}}, }, true, // has_toXYZD50, followed by 3x3 toXYZD50 matrix {{ { 1,0,0 }, { 0,1,0 }, { 0,0,1 }, }}, false, // has_A2B, followed by a2b itself which we don't care about. { 0, { {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, }, {0,0,0,0}, nullptr, nullptr, 0, { {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, }, {{ { 0,0,0,0 }, { 0,0,0,0 }, { 0,0,0,0 }, }}, 0, { {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, {{0, {0,0, 0,0,0,0,0}}}, }, }, }; return &XYZD50_profile; } const skcms_TransferFunction* skcms_sRGB_TransferFunction() { return &skcms_sRGB_profile()->trc[0].parametric; } const skcms_TransferFunction* skcms_sRGB_Inverse_TransferFunction() { static const skcms_TransferFunction sRGB_inv = {0.416666657f, 1.137283325f, -0.0f, 12.920000076f, 0.003130805f, -0.054969788f, -0.0f}; return &sRGB_inv; } const skcms_TransferFunction* skcms_Identity_TransferFunction() { static const skcms_TransferFunction identity = {1,1,0,0,0,0,0}; return &identity; } const uint8_t skcms_252_random_bytes[] = { 8, 179, 128, 204, 253, 38, 134, 184, 68, 102, 32, 138, 99, 39, 169, 215, 119, 26, 3, 223, 95, 239, 52, 132, 114, 74, 81, 234, 97, 116, 244, 205, 30, 154, 173, 12, 51, 159, 122, 153, 61, 226, 236, 178, 229, 55, 181, 220, 191, 194, 160, 126, 168, 82, 131, 18, 180, 245, 163, 22, 246, 69, 235, 252, 57, 108, 14, 6, 152, 240, 255, 171, 242, 20, 227, 177, 238, 96, 85, 16, 211, 70, 200, 149, 155, 146, 127, 145, 100, 151, 109, 19, 165, 208, 195, 164, 137, 254, 182, 248, 64, 201, 45, 209, 5, 147, 207, 210, 113, 162, 83, 225, 9, 31, 15, 231, 115, 37, 58, 53, 24, 49, 197, 56, 120, 172, 48, 21, 214, 129, 111, 11, 50, 187, 196, 34, 60, 103, 71, 144, 47, 203, 77, 80, 232, 140, 222, 250, 206, 166, 247, 139, 249, 221, 72, 106, 27, 199, 117, 54, 219, 135, 118, 40, 79, 41, 251, 46, 93, 212, 92, 233, 148, 28, 121, 63, 123, 158, 105, 59, 29, 42, 143, 23, 0, 107, 176, 87, 104, 183, 156, 193, 189, 90, 188, 65, 190, 17, 198, 7, 186, 161, 1, 124, 78, 125, 170, 133, 174, 218, 67, 157, 75, 101, 89, 217, 62, 33, 141, 228, 25, 35, 91, 230, 4, 2, 13, 73, 86, 167, 237, 84, 243, 44, 185, 66, 130, 110, 150, 142, 216, 88, 112, 36, 224, 136, 202, 76, 94, 98, 175, 213 }; bool skcms_ApproximatelyEqualProfiles(const skcms_ICCProfile* A, const skcms_ICCProfile* B) { // Test for exactly equal profiles first. if (A == B || 0 == memcmp(A,B, sizeof(skcms_ICCProfile))) { return true; } // For now this is the essentially the same strategy we use in test_only.c // for our skcms_Transform() smoke tests: // 1) transform A to XYZD50 // 2) transform B to XYZD50 // 3) return true if they're similar enough // Our current criterion in 3) is maximum 1 bit error per XYZD50 byte. // skcms_252_random_bytes are 252 of a random shuffle of all possible bytes. // 252 is evenly divisible by 3 and 4. Only 192, 10, 241, and 43 are missing. if (A->data_color_space != B->data_color_space) { return false; } // Interpret as RGB_888 if data color space is RGB or GRAY, RGBA_8888 if CMYK. // TODO: working with RGBA_8888 either way is probably fastest. skcms_PixelFormat fmt = skcms_PixelFormat_RGB_888; size_t npixels = 84; if (A->data_color_space == skcms_Signature_CMYK) { fmt = skcms_PixelFormat_RGBA_8888; npixels = 63; } // TODO: if A or B is a known profile (skcms_sRGB_profile, skcms_XYZD50_profile), // use pre-canned results and skip that skcms_Transform() call? uint8_t dstA[252], dstB[252]; if (!skcms_Transform( skcms_252_random_bytes, fmt, skcms_AlphaFormat_Unpremul, A, dstA, skcms_PixelFormat_RGB_888, skcms_AlphaFormat_Unpremul, skcms_XYZD50_profile(), npixels)) { return false; } if (!skcms_Transform( skcms_252_random_bytes, fmt, skcms_AlphaFormat_Unpremul, B, dstB, skcms_PixelFormat_RGB_888, skcms_AlphaFormat_Unpremul, skcms_XYZD50_profile(), npixels)) { return false; } // TODO: make sure this final check has reasonable codegen. for (size_t i = 0; i < 252; i++) { if (abs((int)dstA[i] - (int)dstB[i]) > 1) { return false; } } return true; } bool skcms_TRCs_AreApproximateInverse(const skcms_ICCProfile* profile, const skcms_TransferFunction* inv_tf) { if (!profile || !profile->has_trc) { return false; } return skcms_AreApproximateInverses(&profile->trc[0], inv_tf) && skcms_AreApproximateInverses(&profile->trc[1], inv_tf) && skcms_AreApproximateInverses(&profile->trc[2], inv_tf); } static bool is_zero_to_one(float x) { return 0 <= x && x <= 1; } typedef struct { float vals[3]; } skcms_Vector3; static skcms_Vector3 mv_mul(const skcms_Matrix3x3* m, const skcms_Vector3* v) { skcms_Vector3 dst = {{0,0,0}}; for (int row = 0; row < 3; ++row) { dst.vals[row] = m->vals[row][0] * v->vals[0] + m->vals[row][1] * v->vals[1] + m->vals[row][2] * v->vals[2]; } return dst; } bool skcms_AdaptToXYZD50(float wx, float wy, skcms_Matrix3x3* toXYZD50) { if (!is_zero_to_one(wx) || !is_zero_to_one(wy) || !toXYZD50) { return false; } // Assumes that Y is 1.0f. skcms_Vector3 wXYZ = { { wx / wy, 1, (1 - wx - wy) / wy } }; // Now convert toXYZ matrix to toXYZD50. skcms_Vector3 wXYZD50 = { { 0.96422f, 1.0f, 0.82521f } }; // Calculate the chromatic adaptation matrix. We will use the Bradford method, thus // the matrices below. The Bradford method is used by Adobe and is widely considered // to be the best. skcms_Matrix3x3 xyz_to_lms = {{ { 0.8951f, 0.2664f, -0.1614f }, { -0.7502f, 1.7135f, 0.0367f }, { 0.0389f, -0.0685f, 1.0296f }, }}; skcms_Matrix3x3 lms_to_xyz = {{ { 0.9869929f, -0.1470543f, 0.1599627f }, { 0.4323053f, 0.5183603f, 0.0492912f }, { -0.0085287f, 0.0400428f, 0.9684867f }, }}; skcms_Vector3 srcCone = mv_mul(&xyz_to_lms, &wXYZ); skcms_Vector3 dstCone = mv_mul(&xyz_to_lms, &wXYZD50); *toXYZD50 = {{ { dstCone.vals[0] / srcCone.vals[0], 0, 0 }, { 0, dstCone.vals[1] / srcCone.vals[1], 0 }, { 0, 0, dstCone.vals[2] / srcCone.vals[2] }, }}; *toXYZD50 = skcms_Matrix3x3_concat(toXYZD50, &xyz_to_lms); *toXYZD50 = skcms_Matrix3x3_concat(&lms_to_xyz, toXYZD50); return true; } bool skcms_PrimariesToXYZD50(float rx, float ry, float gx, float gy, float bx, float by, float wx, float wy, skcms_Matrix3x3* toXYZD50) { if (!is_zero_to_one(rx) || !is_zero_to_one(ry) || !is_zero_to_one(gx) || !is_zero_to_one(gy) || !is_zero_to_one(bx) || !is_zero_to_one(by) || !is_zero_to_one(wx) || !is_zero_to_one(wy) || !toXYZD50) { return false; } // First, we need to convert xy values (primaries) to XYZ. skcms_Matrix3x3 primaries = {{ { rx, gx, bx }, { ry, gy, by }, { 1 - rx - ry, 1 - gx - gy, 1 - bx - by }, }}; skcms_Matrix3x3 primaries_inv; if (!skcms_Matrix3x3_invert(&primaries, &primaries_inv)) { return false; } // Assumes that Y is 1.0f. skcms_Vector3 wXYZ = { { wx / wy, 1, (1 - wx - wy) / wy } }; skcms_Vector3 XYZ = mv_mul(&primaries_inv, &wXYZ); skcms_Matrix3x3 toXYZ = {{ { XYZ.vals[0], 0, 0 }, { 0, XYZ.vals[1], 0 }, { 0, 0, XYZ.vals[2] }, }}; toXYZ = skcms_Matrix3x3_concat(&primaries, &toXYZ); skcms_Matrix3x3 DXtoD50; if (!skcms_AdaptToXYZD50(wx, wy, &DXtoD50)) { return false; } *toXYZD50 = skcms_Matrix3x3_concat(&DXtoD50, &toXYZ); return true; } bool skcms_Matrix3x3_invert(const skcms_Matrix3x3* src, skcms_Matrix3x3* dst) { double a00 = src->vals[0][0], a01 = src->vals[1][0], a02 = src->vals[2][0], a10 = src->vals[0][1], a11 = src->vals[1][1], a12 = src->vals[2][1], a20 = src->vals[0][2], a21 = src->vals[1][2], a22 = src->vals[2][2]; double b0 = a00*a11 - a01*a10, b1 = a00*a12 - a02*a10, b2 = a01*a12 - a02*a11, b3 = a20, b4 = a21, b5 = a22; double determinant = b0*b5 - b1*b4 + b2*b3; if (determinant == 0) { return false; } double invdet = 1.0 / determinant; if (invdet > +FLT_MAX || invdet < -FLT_MAX || !isfinitef_((float)invdet)) { return false; } b0 *= invdet; b1 *= invdet; b2 *= invdet; b3 *= invdet; b4 *= invdet; b5 *= invdet; dst->vals[0][0] = (float)( a11*b5 - a12*b4 ); dst->vals[1][0] = (float)( a02*b4 - a01*b5 ); dst->vals[2][0] = (float)( + b2 ); dst->vals[0][1] = (float)( a12*b3 - a10*b5 ); dst->vals[1][1] = (float)( a00*b5 - a02*b3 ); dst->vals[2][1] = (float)( - b1 ); dst->vals[0][2] = (float)( a10*b4 - a11*b3 ); dst->vals[1][2] = (float)( a01*b3 - a00*b4 ); dst->vals[2][2] = (float)( + b0 ); for (int r = 0; r < 3; ++r) for (int c = 0; c < 3; ++c) { if (!isfinitef_(dst->vals[r][c])) { return false; } } return true; } skcms_Matrix3x3 skcms_Matrix3x3_concat(const skcms_Matrix3x3* A, const skcms_Matrix3x3* B) { skcms_Matrix3x3 m = { { { 0,0,0 },{ 0,0,0 },{ 0,0,0 } } }; for (int r = 0; r < 3; r++) for (int c = 0; c < 3; c++) { m.vals[r][c] = A->vals[r][0] * B->vals[0][c] + A->vals[r][1] * B->vals[1][c] + A->vals[r][2] * B->vals[2][c]; } return m; } #if defined(__clang__) [[clang::no_sanitize("float-divide-by-zero")]] // Checked for by classify() on the way out. #endif bool skcms_TransferFunction_invert(const skcms_TransferFunction* src, skcms_TransferFunction* dst) { TF_PQish pq; TF_HLGish hlg; switch (classify(*src, &pq, &hlg)) { case Bad: return false; case sRGBish: break; // handled below case PQish: *dst = { TFKind_marker(PQish), -pq.A, pq.D, 1.0f/pq.F , pq.B, -pq.E, 1.0f/pq.C}; return true; case HLGish: *dst = { TFKind_marker(HLGinvish), 1.0f/hlg.R, 1.0f/hlg.G , 1.0f/hlg.a, hlg.b, hlg.c, 0 }; return true; case HLGinvish: *dst = { TFKind_marker(HLGish), 1.0f/hlg.R, 1.0f/hlg.G , 1.0f/hlg.a, hlg.b, hlg.c, 0 }; return true; } assert (classify(*src) == sRGBish); // We're inverting this function, solving for x in terms of y. // y = (cx + f) x < d // (ax + b)^g + e x ≥ d // The inverse of this function can be expressed in the same piecewise form. skcms_TransferFunction inv = {0,0,0,0,0,0,0}; // We'll start by finding the new threshold inv.d. // In principle we should be able to find that by solving for y at x=d from either side. // (If those two d values aren't the same, it's a discontinuous transfer function.) float d_l = src->c * src->d + src->f, d_r = powf_(src->a * src->d + src->b, src->g) + src->e; if (fabsf_(d_l - d_r) > 1/512.0f) { return false; } inv.d = d_l; // TODO(mtklein): better in practice to choose d_r? // When d=0, the linear section collapses to a point. We leave c,d,f all zero in that case. if (inv.d > 0) { // Inverting the linear section is pretty straightfoward: // y = cx + f // y - f = cx // (1/c)y - f/c = x inv.c = 1.0f/src->c; inv.f = -src->f/src->c; } // The interesting part is inverting the nonlinear section: // y = (ax + b)^g + e. // y - e = (ax + b)^g // (y - e)^1/g = ax + b // (y - e)^1/g - b = ax // (1/a)(y - e)^1/g - b/a = x // // To make that fit our form, we need to move the (1/a) term inside the exponentiation: // let k = (1/a)^g // (1/a)( y - e)^1/g - b/a = x // (ky - ke)^1/g - b/a = x float k = powf_(src->a, -src->g); // (1/a)^g == a^-g inv.g = 1.0f / src->g; inv.a = k; inv.b = -k * src->e; inv.e = -src->b / src->a; // We need to enforce the same constraints here that we do when fitting a curve, // a >= 0 and ad+b >= 0. These constraints are checked by classify(), so they're true // of the source function if we're here. // Just like when fitting the curve, there's really no way to rescue a < 0. if (inv.a < 0) { return false; } // On the other hand we can rescue an ad+b that's gone slightly negative here. if (inv.a * inv.d + inv.b < 0) { inv.b = -inv.a * inv.d; } // That should usually make classify(inv) == sRGBish true, but there are a couple situations // where we might still fail here, like non-finite parameter values. if (classify(inv) != sRGBish) { return false; } assert (inv.a >= 0); assert (inv.a * inv.d + inv.b >= 0); // Now in principle we're done. // But to preserve the valuable invariant inv(src(1.0f)) == 1.0f, we'll tweak // e or f of the inverse, depending on which segment contains src(1.0f). float s = skcms_TransferFunction_eval(src, 1.0f); if (!isfinitef_(s)) { return false; } float sign = s < 0 ? -1.0f : 1.0f; s *= sign; if (s < inv.d) { inv.f = 1.0f - sign * inv.c * s; } else { inv.e = 1.0f - sign * powf_(inv.a * s + inv.b, inv.g); } *dst = inv; return classify(*dst) == sRGBish; } // ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ // // From here below we're approximating an skcms_Curve with an skcms_TransferFunction{g,a,b,c,d,e,f}: // // tf(x) = cx + f x < d // tf(x) = (ax + b)^g + e x ≥ d // // When fitting, we add the additional constraint that both pieces meet at d: // // cd + f = (ad + b)^g + e // // Solving for e and folding it through gives an alternate formulation of the non-linear piece: // // tf(x) = cx + f x < d // tf(x) = (ax + b)^g - (ad + b)^g + cd + f x ≥ d // // Our overall strategy is then: // For a couple tolerances, // - fit_linear(): fit c,d,f iteratively to as many points as our tolerance allows // - invert c,d,f // - fit_nonlinear(): fit g,a,b using Gauss-Newton given those inverted c,d,f // (and by constraint, inverted e) to the inverse of the table. // Return the parameters with least maximum error. // // To run Gauss-Newton to find g,a,b, we'll also need the gradient of the residuals // of round-trip f_inv(x), the inverse of the non-linear piece of f(x). // // let y = Table(x) // r(x) = x - f_inv(y) // // ∂r/∂g = ln(ay + b)*(ay + b)^g // - ln(ad + b)*(ad + b)^g // ∂r/∂a = yg(ay + b)^(g-1) // - dg(ad + b)^(g-1) // ∂r/∂b = g(ay + b)^(g-1) // - g(ad + b)^(g-1) // Return the residual of roundtripping skcms_Curve(x) through f_inv(y) with parameters P, // and fill out the gradient of the residual into dfdP. static float rg_nonlinear(float x, const skcms_Curve* curve, const skcms_TransferFunction* tf, float dfdP[3]) { const float y = eval_curve(curve, x); const float g = tf->g, a = tf->a, b = tf->b, c = tf->c, d = tf->d, f = tf->f; const float Y = fmaxf_(a*y + b, 0.0f), D = a*d + b; assert (D >= 0); // The gradient. dfdP[0] = logf_(Y)*powf_(Y, g) - logf_(D)*powf_(D, g); dfdP[1] = y*g*powf_(Y, g-1) - d*g*powf_(D, g-1); dfdP[2] = g*powf_(Y, g-1) - g*powf_(D, g-1); // The residual. const float f_inv = powf_(Y, g) - powf_(D, g) + c*d + f; return x - f_inv; } static bool gauss_newton_step(const skcms_Curve* curve, skcms_TransferFunction* tf, float x0, float dx, int N) { // We'll sample x from the range [x0,x1] (both inclusive) N times with even spacing. // // Let P = [ tf->g, tf->a, tf->b ] (the three terms that we're adjusting). // // We want to do P' = P + (Jf^T Jf)^-1 Jf^T r(P), // where r(P) is the residual vector // and Jf is the Jacobian matrix of f(), ∂r/∂P. // // Let's review the shape of each of these expressions: // r(P) is [N x 1], a column vector with one entry per value of x tested // Jf is [N x 3], a matrix with an entry for each (x,P) pair // Jf^T is [3 x N], the transpose of Jf // // Jf^T Jf is [3 x N] * [N x 3] == [3 x 3], a 3x3 matrix, // and so is its inverse (Jf^T Jf)^-1 // Jf^T r(P) is [3 x N] * [N x 1] == [3 x 1], a column vector with the same shape as P // // Our implementation strategy to get to the final ∆P is // 1) evaluate Jf^T Jf, call that lhs // 2) evaluate Jf^T r(P), call that rhs // 3) invert lhs // 4) multiply inverse lhs by rhs // // This is a friendly implementation strategy because we don't have to have any // buffers that scale with N, and equally nice don't have to perform any matrix // operations that are variable size. // // Other implementation strategies could trade this off, e.g. evaluating the // pseudoinverse of Jf ( (Jf^T Jf)^-1 Jf^T ) directly, then multiplying that by // the residuals. That would probably require implementing singular value // decomposition, and would create a [3 x N] matrix to be multiplied by the // [N x 1] residual vector, but on the upside I think that'd eliminate the // possibility of this gauss_newton_step() function ever failing. // 0) start off with lhs and rhs safely zeroed. skcms_Matrix3x3 lhs = {{ {0,0,0}, {0,0,0}, {0,0,0} }}; skcms_Vector3 rhs = { {0,0,0} }; // 1,2) evaluate lhs and evaluate rhs // We want to evaluate Jf only once, but both lhs and rhs involve Jf^T, // so we'll have to update lhs and rhs at the same time. for (int i = 0; i < N; i++) { float x = x0 + i*dx; float dfdP[3] = {0,0,0}; float resid = rg_nonlinear(x,curve,tf, dfdP); for (int r = 0; r < 3; r++) { for (int c = 0; c < 3; c++) { lhs.vals[r][c] += dfdP[r] * dfdP[c]; } rhs.vals[r] += dfdP[r] * resid; } } // If any of the 3 P parameters are unused, this matrix will be singular. // Detect those cases and fix them up to indentity instead, so we can invert. for (int k = 0; k < 3; k++) { if (lhs.vals[0][k]==0 && lhs.vals[1][k]==0 && lhs.vals[2][k]==0 && lhs.vals[k][0]==0 && lhs.vals[k][1]==0 && lhs.vals[k][2]==0) { lhs.vals[k][k] = 1; } } // 3) invert lhs skcms_Matrix3x3 lhs_inv; if (!skcms_Matrix3x3_invert(&lhs, &lhs_inv)) { return false; } // 4) multiply inverse lhs by rhs skcms_Vector3 dP = mv_mul(&lhs_inv, &rhs); tf->g += dP.vals[0]; tf->a += dP.vals[1]; tf->b += dP.vals[2]; return isfinitef_(tf->g) && isfinitef_(tf->a) && isfinitef_(tf->b); } static float max_roundtrip_error_checked(const skcms_Curve* curve, const skcms_TransferFunction* tf_inv) { skcms_TransferFunction tf; if (!skcms_TransferFunction_invert(tf_inv, &tf) || sRGBish != classify(tf)) { return INFINITY_; } skcms_TransferFunction tf_inv_again; if (!skcms_TransferFunction_invert(&tf, &tf_inv_again)) { return INFINITY_; } return skcms_MaxRoundtripError(curve, &tf_inv_again); } // Fit the points in [L,N) to the non-linear piece of tf, or return false if we can't. static bool fit_nonlinear(const skcms_Curve* curve, int L, int N, skcms_TransferFunction* tf) { // This enforces a few constraints that are not modeled in gauss_newton_step()'s optimization. auto fixup_tf = [tf]() { // a must be non-negative. That ensures the function is monotonically increasing. // We don't really know how to fix up a if it goes negative. if (tf->a < 0) { return false; } // ad+b must be non-negative. That ensures we don't end up with complex numbers in powf. // We feel just barely not uneasy enough to tweak b so ad+b is zero in this case. if (tf->a * tf->d + tf->b < 0) { tf->b = -tf->a * tf->d; } assert (tf->a >= 0 && tf->a * tf->d + tf->b >= 0); // cd+f must be ~= (ad+b)^g+e. That ensures the function is continuous. We keep e as a free // parameter so we can guarantee this. tf->e = tf->c*tf->d + tf->f - powf_(tf->a*tf->d + tf->b, tf->g); return true; }; if (!fixup_tf()) { return false; } // No matter where we start, dx should always represent N even steps from 0 to 1. const float dx = 1.0f / (N-1); skcms_TransferFunction best_tf = *tf; float best_max_error = INFINITY_; // Need this or several curves get worse... *sigh* float init_error = max_roundtrip_error_checked(curve, tf); if (init_error < best_max_error) { best_max_error = init_error; best_tf = *tf; } // As far as we can tell, 1 Gauss-Newton step won't converge, and 3 steps is no better than 2. for (int j = 0; j < 8; j++) { if (!gauss_newton_step(curve, tf, L*dx, dx, N-L) || !fixup_tf()) { *tf = best_tf; return isfinitef_(best_max_error); } float max_error = max_roundtrip_error_checked(curve, tf); if (max_error < best_max_error) { best_max_error = max_error; best_tf = *tf; } } *tf = best_tf; return isfinitef_(best_max_error); } bool skcms_ApproximateCurve(const skcms_Curve* curve, skcms_TransferFunction* approx, float* max_error) { if (!curve || !approx || !max_error) { return false; } if (curve->table_entries == 0) { // No point approximating an skcms_TransferFunction with an skcms_TransferFunction! return false; } if (curve->table_entries == 1 || curve->table_entries > (uint32_t)INT_MAX) { // We need at least two points, and must put some reasonable cap on the maximum number. return false; } int N = (int)curve->table_entries; const float dx = 1.0f / (N - 1); *max_error = INFINITY_; const float kTolerances[] = { 1.5f / 65535.0f, 1.0f / 512.0f }; for (int t = 0; t < ARRAY_COUNT(kTolerances); t++) { skcms_TransferFunction tf, tf_inv; // It's problematic to fit curves with non-zero f, so always force it to zero explicitly. tf.f = 0.0f; int L = fit_linear(curve, N, kTolerances[t], &tf.c, &tf.d); if (L == N) { // If the entire data set was linear, move the coefficients to the nonlinear portion // with G == 1. This lets use a canonical representation with d == 0. tf.g = 1; tf.a = tf.c; tf.b = tf.f; tf.c = tf.d = tf.e = tf.f = 0; } else if (L == N - 1) { // Degenerate case with only two points in the nonlinear segment. Solve directly. tf.g = 1; tf.a = (eval_curve(curve, (N-1)*dx) - eval_curve(curve, (N-2)*dx)) / dx; tf.b = eval_curve(curve, (N-2)*dx) - tf.a * (N-2)*dx; tf.e = 0; } else { // Start by guessing a gamma-only curve through the midpoint. int mid = (L + N) / 2; float mid_x = mid / (N - 1.0f); float mid_y = eval_curve(curve, mid_x); tf.g = log2f_(mid_y) / log2f_(mid_x); tf.a = 1; tf.b = 0; tf.e = tf.c*tf.d + tf.f - powf_(tf.a*tf.d + tf.b, tf.g); if (!skcms_TransferFunction_invert(&tf, &tf_inv) || !fit_nonlinear(curve, L,N, &tf_inv)) { continue; } // We fit tf_inv, so calculate tf to keep in sync. // fit_nonlinear() should guarantee invertibility. if (!skcms_TransferFunction_invert(&tf_inv, &tf)) { assert(false); continue; } } // We'd better have a sane, sRGB-ish TF by now. // Other non-Bad TFs would be fine, but we know we've only ever tried to fit sRGBish; // anything else is just some accident of math and the way we pun tf.g as a type flag. // fit_nonlinear() should guarantee this, but the special cases may fail this test. if (sRGBish != classify(tf)) { continue; } // We find our error by roundtripping the table through tf_inv. // // (The most likely use case for this approximation is to be inverted and // used as the transfer function for a destination color space.) // // We've kept tf and tf_inv in sync above, but we can't guarantee that tf is // invertible, so re-verify that here (and use the new inverse for testing). // fit_nonlinear() should guarantee this, but the special cases that don't use // it may fail this test. if (!skcms_TransferFunction_invert(&tf, &tf_inv)) { continue; } float err = skcms_MaxRoundtripError(curve, &tf_inv); if (*max_error > err) { *max_error = err; *approx = tf; } } return isfinitef_(*max_error); } // ~~~~ Impl. of skcms_Transform() ~~~~ typedef enum { Op_load_a8, Op_load_g8, Op_load_8888_palette8, Op_load_4444, Op_load_565, Op_load_888, Op_load_8888, Op_load_1010102, Op_load_161616LE, Op_load_16161616LE, Op_load_161616BE, Op_load_16161616BE, Op_load_hhh, Op_load_hhhh, Op_load_fff, Op_load_ffff, Op_swap_rb, Op_clamp, Op_invert, Op_force_opaque, Op_premul, Op_unpremul, Op_matrix_3x3, Op_matrix_3x4, Op_lab_to_xyz, Op_tf_r, Op_tf_g, Op_tf_b, Op_tf_a, Op_pq_r, Op_pq_g, Op_pq_b, Op_pq_a, Op_hlg_r, Op_hlg_g, Op_hlg_b, Op_hlg_a, Op_hlginv_r, Op_hlginv_g, Op_hlginv_b, Op_hlginv_a, Op_table_r, Op_table_g, Op_table_b, Op_table_a, Op_clut, Op_store_a8, Op_store_g8, Op_store_4444, Op_store_565, Op_store_888, Op_store_8888, Op_store_1010102, Op_store_161616LE, Op_store_16161616LE, Op_store_161616BE, Op_store_16161616BE, Op_store_hhh, Op_store_hhhh, Op_store_fff, Op_store_ffff, } Op; #if defined(__clang__) template using Vec = T __attribute__((ext_vector_type(N))); #elif defined(__GNUC__) // For some reason GCC accepts this nonsense, but not the more straightforward version, // template using Vec = T __attribute__((vector_size(N*sizeof(T)))); template struct VecHelper { typedef T __attribute__((vector_size(N*sizeof(T)))) V; }; template using Vec = typename VecHelper::V; #endif // First, instantiate our default exec_ops() implementation using the default compiliation target. namespace baseline { #if defined(SKCMS_PORTABLE) || !(defined(__clang__) || defined(__GNUC__)) \ || (defined(__EMSCRIPTEN_major__) && !defined(__wasm_simd128__)) #define N 1 template using V = T; using Color = float; #elif defined(__AVX512F__) #define N 16 template using V = Vec; using Color = float; #elif defined(__AVX__) #define N 8 template using V = Vec; using Color = float; #elif defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && defined(SKCMS_OPT_INTO_NEON_FP16) #define N 8 template using V = Vec; using Color = _Float16; #else #define N 4 template using V = Vec; using Color = float; #endif #include "src/Transform_inl.h" #undef N } // Now, instantiate any other versions of run_program() we may want for runtime detection. #if !defined(SKCMS_PORTABLE) && \ !defined(SKCMS_NO_RUNTIME_CPU_DETECTION) && \ (( defined(__clang__) && __clang_major__ >= 5) || \ (!defined(__clang__) && defined(__GNUC__))) \ && defined(__x86_64__) #if !defined(__AVX2__) #if defined(__clang__) #pragma clang attribute push(__attribute__((target("avx2,f16c"))), apply_to=function) #elif defined(__GNUC__) #pragma GCC push_options #pragma GCC target("avx2,f16c") #endif namespace hsw { #define USING_AVX #define USING_AVX_F16C #define USING_AVX2 #define N 8 template using V = Vec; using Color = float; #include "src/Transform_inl.h" // src/Transform_inl.h will undefine USING_* for us. #undef N } #if defined(__clang__) #pragma clang attribute pop #elif defined(__GNUC__) #pragma GCC pop_options #endif #define TEST_FOR_HSW #endif #if !defined(__AVX512F__) #if defined(__clang__) #pragma clang attribute push(__attribute__((target("avx512f,avx512dq,avx512cd,avx512bw,avx512vl"))), apply_to=function) #elif defined(__GNUC__) #pragma GCC push_options #pragma GCC target("avx512f,avx512dq,avx512cd,avx512bw,avx512vl") #endif namespace skx { #define USING_AVX512F #define N 16 template using V = Vec; using Color = float; #include "src/Transform_inl.h" // src/Transform_inl.h will undefine USING_* for us. #undef N } #if defined(__clang__) #pragma clang attribute pop #elif defined(__GNUC__) #pragma GCC pop_options #endif #define TEST_FOR_SKX #endif #if defined(TEST_FOR_HSW) || defined(TEST_FOR_SKX) enum class CpuType { None, HSW, SKX }; static CpuType cpu_type() { static const CpuType type = []{ // See http://www.sandpile.org/x86/cpuid.htm // First, a basic cpuid(1) lets us check prerequisites for HSW, SKX. uint32_t eax, ebx, ecx, edx; __asm__ __volatile__("cpuid" : "=a"(eax), "=b"(ebx), "=c"(ecx), "=d"(edx) : "0"(1), "2"(0)); if ((edx & (1u<<25)) && // SSE (edx & (1u<<26)) && // SSE2 (ecx & (1u<< 0)) && // SSE3 (ecx & (1u<< 9)) && // SSSE3 (ecx & (1u<<12)) && // FMA (N.B. not used, avoided even) (ecx & (1u<<19)) && // SSE4.1 (ecx & (1u<<20)) && // SSE4.2 (ecx & (1u<<26)) && // XSAVE (ecx & (1u<<27)) && // OSXSAVE (ecx & (1u<<28)) && // AVX (ecx & (1u<<29))) { // F16C // Call cpuid(7) to check for AVX2 and AVX-512 bits. __asm__ __volatile__("cpuid" : "=a"(eax), "=b"(ebx), "=c"(ecx), "=d"(edx) : "0"(7), "2"(0)); // eax from xgetbv(0) will tell us whether XMM, YMM, and ZMM state is saved. uint32_t xcr0, dont_need_edx; __asm__ __volatile__("xgetbv" : "=a"(xcr0), "=d"(dont_need_edx) : "c"(0)); if ((xcr0 & (1u<<1)) && // XMM register state saved? (xcr0 & (1u<<2)) && // YMM register state saved? (ebx & (1u<<5))) { // AVX2 // At this point we're at least HSW. Continue checking for SKX. if ((xcr0 & (1u<< 5)) && // Opmasks state saved? (xcr0 & (1u<< 6)) && // First 16 ZMM registers saved? (xcr0 & (1u<< 7)) && // High 16 ZMM registers saved? (ebx & (1u<<16)) && // AVX512F (ebx & (1u<<17)) && // AVX512DQ (ebx & (1u<<28)) && // AVX512CD (ebx & (1u<<30)) && // AVX512BW (ebx & (1u<<31))) { // AVX512VL return CpuType::SKX; } return CpuType::HSW; } } return CpuType::None; }(); return type; } #endif #endif typedef struct { Op op; const void* arg; } OpAndArg; static OpAndArg select_curve_op(const skcms_Curve* curve, int channel) { static const struct { Op sRGBish, PQish, HLGish, HLGinvish, table; } ops[] = { { Op_tf_r, Op_pq_r, Op_hlg_r, Op_hlginv_r, Op_table_r }, { Op_tf_g, Op_pq_g, Op_hlg_g, Op_hlginv_g, Op_table_g }, { Op_tf_b, Op_pq_b, Op_hlg_b, Op_hlginv_b, Op_table_b }, { Op_tf_a, Op_pq_a, Op_hlg_a, Op_hlginv_a, Op_table_a }, }; const auto& op = ops[channel]; if (curve->table_entries == 0) { const OpAndArg noop = { Op_load_a8/*doesn't matter*/, nullptr }; const skcms_TransferFunction& tf = curve->parametric; if (tf.g == 1 && tf.a == 1 && tf.b == 0 && tf.c == 0 && tf.d == 0 && tf.e == 0 && tf.f == 0) { return noop; } switch (classify(tf)) { case Bad: return noop; case sRGBish: return OpAndArg{op.sRGBish, &tf}; case PQish: return OpAndArg{op.PQish, &tf}; case HLGish: return OpAndArg{op.HLGish, &tf}; case HLGinvish: return OpAndArg{op.HLGinvish, &tf}; } } return OpAndArg{op.table, curve}; } static size_t bytes_per_pixel(skcms_PixelFormat fmt) { switch (fmt >> 1) { // ignore rgb/bgr case skcms_PixelFormat_A_8 >> 1: return 1; case skcms_PixelFormat_G_8 >> 1: return 1; case skcms_PixelFormat_RGBA_8888_Palette8 >> 1: return 1; case skcms_PixelFormat_ABGR_4444 >> 1: return 2; case skcms_PixelFormat_RGB_565 >> 1: return 2; case skcms_PixelFormat_RGB_888 >> 1: return 3; case skcms_PixelFormat_RGBA_8888 >> 1: return 4; case skcms_PixelFormat_RGBA_8888_sRGB >> 1: return 4; case skcms_PixelFormat_RGBA_1010102 >> 1: return 4; case skcms_PixelFormat_RGB_161616LE >> 1: return 6; case skcms_PixelFormat_RGBA_16161616LE >> 1: return 8; case skcms_PixelFormat_RGB_161616BE >> 1: return 6; case skcms_PixelFormat_RGBA_16161616BE >> 1: return 8; case skcms_PixelFormat_RGB_hhh_Norm >> 1: return 6; case skcms_PixelFormat_RGBA_hhhh_Norm >> 1: return 8; case skcms_PixelFormat_RGB_hhh >> 1: return 6; case skcms_PixelFormat_RGBA_hhhh >> 1: return 8; case skcms_PixelFormat_RGB_fff >> 1: return 12; case skcms_PixelFormat_RGBA_ffff >> 1: return 16; } assert(false); return 0; } static bool prep_for_destination(const skcms_ICCProfile* profile, skcms_Matrix3x3* fromXYZD50, skcms_TransferFunction* invR, skcms_TransferFunction* invG, skcms_TransferFunction* invB) { // We only support destinations with parametric transfer functions // and with gamuts that can be transformed from XYZD50. return profile->has_trc && profile->has_toXYZD50 && profile->trc[0].table_entries == 0 && profile->trc[1].table_entries == 0 && profile->trc[2].table_entries == 0 && skcms_TransferFunction_invert(&profile->trc[0].parametric, invR) && skcms_TransferFunction_invert(&profile->trc[1].parametric, invG) && skcms_TransferFunction_invert(&profile->trc[2].parametric, invB) && skcms_Matrix3x3_invert(&profile->toXYZD50, fromXYZD50); } bool skcms_Transform(const void* src, skcms_PixelFormat srcFmt, skcms_AlphaFormat srcAlpha, const skcms_ICCProfile* srcProfile, void* dst, skcms_PixelFormat dstFmt, skcms_AlphaFormat dstAlpha, const skcms_ICCProfile* dstProfile, size_t npixels) { return skcms_TransformWithPalette(src, srcFmt, srcAlpha, srcProfile, dst, dstFmt, dstAlpha, dstProfile, npixels, nullptr); } bool skcms_TransformWithPalette(const void* src, skcms_PixelFormat srcFmt, skcms_AlphaFormat srcAlpha, const skcms_ICCProfile* srcProfile, void* dst, skcms_PixelFormat dstFmt, skcms_AlphaFormat dstAlpha, const skcms_ICCProfile* dstProfile, size_t nz, const void* palette) { const size_t dst_bpp = bytes_per_pixel(dstFmt), src_bpp = bytes_per_pixel(srcFmt); // Let's just refuse if the request is absurdly big. if (nz * dst_bpp > INT_MAX || nz * src_bpp > INT_MAX) { return false; } int n = (int)nz; // Null profiles default to sRGB. Passing null for both is handy when doing format conversion. if (!srcProfile) { srcProfile = skcms_sRGB_profile(); } if (!dstProfile) { dstProfile = skcms_sRGB_profile(); } // We can't transform in place unless the PixelFormats are the same size. if (dst == src && dst_bpp != src_bpp) { return false; } // TODO: more careful alias rejection (like, dst == src + 1)? if (needs_palette(srcFmt) && !palette) { return false; } Op program [32]; const void* arguments[32]; Op* ops = program; const void** args = arguments; // These are always parametric curves of some sort. skcms_Curve dst_curves[3]; dst_curves[0].table_entries = dst_curves[1].table_entries = dst_curves[2].table_entries = 0; skcms_Matrix3x3 from_xyz; switch (srcFmt >> 1) { default: return false; case skcms_PixelFormat_A_8 >> 1: *ops++ = Op_load_a8; break; case skcms_PixelFormat_G_8 >> 1: *ops++ = Op_load_g8; break; case skcms_PixelFormat_ABGR_4444 >> 1: *ops++ = Op_load_4444; break; case skcms_PixelFormat_RGB_565 >> 1: *ops++ = Op_load_565; break; case skcms_PixelFormat_RGB_888 >> 1: *ops++ = Op_load_888; break; case skcms_PixelFormat_RGBA_8888 >> 1: *ops++ = Op_load_8888; break; case skcms_PixelFormat_RGBA_1010102 >> 1: *ops++ = Op_load_1010102; break; case skcms_PixelFormat_RGB_161616LE >> 1: *ops++ = Op_load_161616LE; break; case skcms_PixelFormat_RGBA_16161616LE >> 1: *ops++ = Op_load_16161616LE; break; case skcms_PixelFormat_RGB_161616BE >> 1: *ops++ = Op_load_161616BE; break; case skcms_PixelFormat_RGBA_16161616BE >> 1: *ops++ = Op_load_16161616BE; break; case skcms_PixelFormat_RGB_hhh_Norm >> 1: *ops++ = Op_load_hhh; break; case skcms_PixelFormat_RGBA_hhhh_Norm >> 1: *ops++ = Op_load_hhhh; break; case skcms_PixelFormat_RGB_hhh >> 1: *ops++ = Op_load_hhh; break; case skcms_PixelFormat_RGBA_hhhh >> 1: *ops++ = Op_load_hhhh; break; case skcms_PixelFormat_RGB_fff >> 1: *ops++ = Op_load_fff; break; case skcms_PixelFormat_RGBA_ffff >> 1: *ops++ = Op_load_ffff; break; case skcms_PixelFormat_RGBA_8888_Palette8 >> 1: *ops++ = Op_load_8888_palette8; *args++ = palette; break; case skcms_PixelFormat_RGBA_8888_sRGB >> 1: *ops++ = Op_load_8888; *ops++ = Op_tf_r; *args++ = skcms_sRGB_TransferFunction(); *ops++ = Op_tf_g; *args++ = skcms_sRGB_TransferFunction(); *ops++ = Op_tf_b; *args++ = skcms_sRGB_TransferFunction(); break; } if (srcFmt == skcms_PixelFormat_RGB_hhh_Norm || srcFmt == skcms_PixelFormat_RGBA_hhhh_Norm) { *ops++ = Op_clamp; } if (srcFmt & 1) { *ops++ = Op_swap_rb; } skcms_ICCProfile gray_dst_profile; if ((dstFmt >> 1) == (skcms_PixelFormat_G_8 >> 1)) { // When transforming to gray, stop at XYZ (by setting toXYZ to identity), then transform // luminance (Y) by the destination transfer function. gray_dst_profile = *dstProfile; skcms_SetXYZD50(&gray_dst_profile, &skcms_XYZD50_profile()->toXYZD50); dstProfile = &gray_dst_profile; } if (srcProfile->data_color_space == skcms_Signature_CMYK) { // Photoshop creates CMYK images as inverse CMYK. // These happen to be the only ones we've _ever_ seen. *ops++ = Op_invert; // With CMYK, ignore the alpha type, to avoid changing K or conflating CMY with K. srcAlpha = skcms_AlphaFormat_Unpremul; } if (srcAlpha == skcms_AlphaFormat_Opaque) { *ops++ = Op_force_opaque; } else if (srcAlpha == skcms_AlphaFormat_PremulAsEncoded) { *ops++ = Op_unpremul; } if (dstProfile != srcProfile) { if (!prep_for_destination(dstProfile, &from_xyz, &dst_curves[0].parametric, &dst_curves[1].parametric, &dst_curves[2].parametric)) { return false; } if (srcProfile->has_A2B) { if (srcProfile->A2B.input_channels) { for (int i = 0; i < (int)srcProfile->A2B.input_channels; i++) { OpAndArg oa = select_curve_op(&srcProfile->A2B.input_curves[i], i); if (oa.arg) { *ops++ = oa.op; *args++ = oa.arg; } } *ops++ = Op_clamp; *ops++ = Op_clut; *args++ = &srcProfile->A2B; } if (srcProfile->A2B.matrix_channels == 3) { for (int i = 0; i < 3; i++) { OpAndArg oa = select_curve_op(&srcProfile->A2B.matrix_curves[i], i); if (oa.arg) { *ops++ = oa.op; *args++ = oa.arg; } } static const skcms_Matrix3x4 I = {{ {1,0,0,0}, {0,1,0,0}, {0,0,1,0}, }}; if (0 != memcmp(&I, &srcProfile->A2B.matrix, sizeof(I))) { *ops++ = Op_matrix_3x4; *args++ = &srcProfile->A2B.matrix; } } if (srcProfile->A2B.output_channels == 3) { for (int i = 0; i < 3; i++) { OpAndArg oa = select_curve_op(&srcProfile->A2B.output_curves[i], i); if (oa.arg) { *ops++ = oa.op; *args++ = oa.arg; } } } if (srcProfile->pcs == skcms_Signature_Lab) { *ops++ = Op_lab_to_xyz; } } else if (srcProfile->has_trc && srcProfile->has_toXYZD50) { for (int i = 0; i < 3; i++) { OpAndArg oa = select_curve_op(&srcProfile->trc[i], i); if (oa.arg) { *ops++ = oa.op; *args++ = oa.arg; } } } else { return false; } // A2B sources should already be in XYZD50 at this point. // Others still need to be transformed using their toXYZD50 matrix. // N.B. There are profiles that contain both A2B tags and toXYZD50 matrices. // If we use the A2B tags, we need to ignore the XYZD50 matrix entirely. assert (srcProfile->has_A2B || srcProfile->has_toXYZD50); static const skcms_Matrix3x3 I = {{ { 1.0f, 0.0f, 0.0f }, { 0.0f, 1.0f, 0.0f }, { 0.0f, 0.0f, 1.0f }, }}; const skcms_Matrix3x3* to_xyz = srcProfile->has_A2B ? &I : &srcProfile->toXYZD50; // There's a chance the source and destination gamuts are identical, // in which case we can skip the gamut transform. if (0 != memcmp(&dstProfile->toXYZD50, to_xyz, sizeof(skcms_Matrix3x3))) { // Concat the entire gamut transform into from_xyz, // now slightly misnamed but it's a handy spot to stash the result. from_xyz = skcms_Matrix3x3_concat(&from_xyz, to_xyz); *ops++ = Op_matrix_3x3; *args++ = &from_xyz; } // Encode back to dst RGB using its parametric transfer functions. for (int i = 0; i < 3; i++) { OpAndArg oa = select_curve_op(dst_curves+i, i); if (oa.arg) { assert (oa.op != Op_table_r && oa.op != Op_table_g && oa.op != Op_table_b && oa.op != Op_table_a); *ops++ = oa.op; *args++ = oa.arg; } } } // Clamp here before premul to make sure we're clamping to normalized values _and_ gamut, // not just to values that fit in [0,1]. // // E.g. r = 1.1, a = 0.5 would fit fine in fixed point after premul (ra=0.55,a=0.5), // but would be carrying r > 1, which is really unexpected for downstream consumers. if (dstFmt < skcms_PixelFormat_RGB_hhh) { *ops++ = Op_clamp; } if (dstAlpha == skcms_AlphaFormat_Opaque) { *ops++ = Op_force_opaque; } else if (dstAlpha == skcms_AlphaFormat_PremulAsEncoded) { *ops++ = Op_premul; } if (dstFmt & 1) { *ops++ = Op_swap_rb; } switch (dstFmt >> 1) { default: return false; case skcms_PixelFormat_A_8 >> 1: *ops++ = Op_store_a8; break; case skcms_PixelFormat_G_8 >> 1: *ops++ = Op_store_g8; break; case skcms_PixelFormat_ABGR_4444 >> 1: *ops++ = Op_store_4444; break; case skcms_PixelFormat_RGB_565 >> 1: *ops++ = Op_store_565; break; case skcms_PixelFormat_RGB_888 >> 1: *ops++ = Op_store_888; break; case skcms_PixelFormat_RGBA_8888 >> 1: *ops++ = Op_store_8888; break; case skcms_PixelFormat_RGBA_1010102 >> 1: *ops++ = Op_store_1010102; break; case skcms_PixelFormat_RGB_161616LE >> 1: *ops++ = Op_store_161616LE; break; case skcms_PixelFormat_RGBA_16161616LE >> 1: *ops++ = Op_store_16161616LE; break; case skcms_PixelFormat_RGB_161616BE >> 1: *ops++ = Op_store_161616BE; break; case skcms_PixelFormat_RGBA_16161616BE >> 1: *ops++ = Op_store_16161616BE; break; case skcms_PixelFormat_RGB_hhh_Norm >> 1: *ops++ = Op_store_hhh; break; case skcms_PixelFormat_RGBA_hhhh_Norm >> 1: *ops++ = Op_store_hhhh; break; case skcms_PixelFormat_RGB_hhh >> 1: *ops++ = Op_store_hhh; break; case skcms_PixelFormat_RGBA_hhhh >> 1: *ops++ = Op_store_hhhh; break; case skcms_PixelFormat_RGB_fff >> 1: *ops++ = Op_store_fff; break; case skcms_PixelFormat_RGBA_ffff >> 1: *ops++ = Op_store_ffff; break; case skcms_PixelFormat_RGBA_8888_sRGB >> 1: *ops++ = Op_tf_r; *args++ = skcms_sRGB_Inverse_TransferFunction(); *ops++ = Op_tf_g; *args++ = skcms_sRGB_Inverse_TransferFunction(); *ops++ = Op_tf_b; *args++ = skcms_sRGB_Inverse_TransferFunction(); *ops++ = Op_store_8888; break; } auto run = baseline::run_program; #if defined(TEST_FOR_HSW) switch (cpu_type()) { case CpuType::None: break; case CpuType::HSW: run = hsw::run_program; break; case CpuType::SKX: run = hsw::run_program; break; } #endif #if defined(TEST_FOR_SKX) switch (cpu_type()) { case CpuType::None: break; case CpuType::HSW: break; case CpuType::SKX: run = skx::run_program; break; } #endif run(program, arguments, (const char*)src, (char*)dst, n, src_bpp,dst_bpp); return true; } static void assert_usable_as_destination(const skcms_ICCProfile* profile) { #if defined(NDEBUG) (void)profile; #else skcms_Matrix3x3 fromXYZD50; skcms_TransferFunction invR, invG, invB; assert(prep_for_destination(profile, &fromXYZD50, &invR, &invG, &invB)); #endif } bool skcms_MakeUsableAsDestination(skcms_ICCProfile* profile) { skcms_Matrix3x3 fromXYZD50; if (!profile->has_trc || !profile->has_toXYZD50 || !skcms_Matrix3x3_invert(&profile->toXYZD50, &fromXYZD50)) { return false; } skcms_TransferFunction tf[3]; for (int i = 0; i < 3; i++) { skcms_TransferFunction inv; if (profile->trc[i].table_entries == 0 && skcms_TransferFunction_invert(&profile->trc[i].parametric, &inv)) { tf[i] = profile->trc[i].parametric; continue; } float max_error; // Parametric curves from skcms_ApproximateCurve() are guaranteed to be invertible. if (!skcms_ApproximateCurve(&profile->trc[i], &tf[i], &max_error)) { return false; } } for (int i = 0; i < 3; ++i) { profile->trc[i].table_entries = 0; profile->trc[i].parametric = tf[i]; } assert_usable_as_destination(profile); return true; } bool skcms_MakeUsableAsDestinationWithSingleCurve(skcms_ICCProfile* profile) { // Operate on a copy of profile, so we can choose the best TF for the original curves skcms_ICCProfile result = *profile; if (!skcms_MakeUsableAsDestination(&result)) { return false; } int best_tf = 0; float min_max_error = INFINITY_; for (int i = 0; i < 3; i++) { skcms_TransferFunction inv; if (!skcms_TransferFunction_invert(&result.trc[i].parametric, &inv)) { return false; } float err = 0; for (int j = 0; j < 3; ++j) { err = fmaxf_(err, skcms_MaxRoundtripError(&profile->trc[j], &inv)); } if (min_max_error > err) { min_max_error = err; best_tf = i; } } for (int i = 0; i < 3; i++) { result.trc[i].parametric = result.trc[best_tf].parametric; } *profile = result; assert_usable_as_destination(profile); return true; }