mirror of
https://github.com/mpv-player/mpv
synced 2024-11-14 22:48:35 +01:00
03bbaad686
The nnedi3 prescaler requires a normalized range to work properly, but the original implementation did the range normalization after the first step of the first pass. This could lead to severe quality degradation when debanding is not enabled for NNEDI3. Fix this issue by passing `tex_mul` into the shader code. Fixes #2464
220 lines
7.9 KiB
C
220 lines
7.9 KiB
C
/*
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* This file is part of mpv.
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*
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* mpv is free software; you can redistribute it and/or modify
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* it under the terms of the GNU General Public License as published by
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* the Free Software Foundation; either version 2 of the License, or
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* (at your option) any later version.
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*
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* mpv is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* GNU General Public License for more details.
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*
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* You should have received a copy of the GNU General Public License along
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* with mpv. If not, see <http://www.gnu.org/licenses/>.
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*
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* You can alternatively redistribute this file and/or
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* modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation; either
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* version 2.1 of the License, or (at your option) any later version.
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*/
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#include "nnedi3.h"
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#include <assert.h>
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#include <stdint.h>
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#include <float.h>
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#include <libavutil/bswap.h>
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#include "video.h"
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#define GLSL(x) gl_sc_add(sc, #x "\n");
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#define GLSLF(...) gl_sc_addf(sc, __VA_ARGS__)
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#define GLSLH(x) gl_sc_hadd(sc, #x "\n");
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#define GLSLHF(...) gl_sc_haddf(sc, __VA_ARGS__)
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const struct nnedi3_opts nnedi3_opts_def = {
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.neurons = 1,
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.window = 0,
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.upload = NNEDI3_UPLOAD_UBO,
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};
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#define OPT_BASE_STRUCT struct nnedi3_opts
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const struct m_sub_options nnedi3_conf = {
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.opts = (const m_option_t[]) {
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OPT_CHOICE("neurons", neurons, 0,
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({"16", 0},
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{"32", 1},
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{"64", 2},
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{"128", 3})),
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OPT_CHOICE("window", window, 0,
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({"8x4", 0},
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{"8x6", 1})),
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OPT_CHOICE("upload", upload, 0,
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({"ubo", NNEDI3_UPLOAD_UBO},
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{"shader", NNEDI3_UPLOAD_SHADER})),
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{0}
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},
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.size = sizeof(struct nnedi3_opts),
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.defaults = &nnedi3_opts_def,
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};
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const static char nnedi3_weights[40320 * 4 + 1] =
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#include "video/out/opengl/nnedi3_weights.inc"
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;
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const int nnedi3_weight_offsets[9] =
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{0, 1088, 3264, 7616, 16320, 17920, 21120, 27520, 40320};
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const int nnedi3_neurons[4] = {16, 32, 64, 128};
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const int nnedi3_window_width[2] = {8, 8};
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const int nnedi3_window_height[2] = {4, 6};
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const float* get_nnedi3_weights(const struct nnedi3_opts *conf, int *size)
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{
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int idx = conf->window * 4 + conf->neurons;
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const int offset = nnedi3_weight_offsets[idx];
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*size = (nnedi3_weight_offsets[idx + 1] - offset) * 4;
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return (const float*)(nnedi3_weights + offset * 4);
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}
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void pass_nnedi3(GL *gl, struct gl_shader_cache *sc, int planes, int tex_num,
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int step, float tex_mul, const struct nnedi3_opts *conf,
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struct gl_transform *transform)
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{
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assert(0 <= step && step < 2);
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if (!conf)
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conf = &nnedi3_opts_def;
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const int neurons = nnedi3_neurons[conf->neurons];
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const int width = nnedi3_window_width[conf->window];
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const int height = nnedi3_window_height[conf->window];
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const int offset = nnedi3_weight_offsets[conf->window * 4 + conf->neurons];
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const uint32_t *weights = (const int*)(nnedi3_weights + offset * 4);
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GLSLF("// nnedi3 (tex %d, step %d, neurons %d, window %dx%d, mode %d)\n",
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tex_num, step + 1, neurons, width, height, conf->upload);
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// This is required since each row will be encoded into vec4s
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assert(width % 4 == 0);
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const int sample_count = width * height / 4;
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if (conf->upload == NNEDI3_UPLOAD_UBO) {
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char buf[32];
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snprintf(buf, sizeof(buf), "vec4 weights[%d];",
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neurons * (sample_count * 2 + 1));
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gl_sc_uniform_buffer(sc, "NNEDI3_WEIGHTS", buf, 0);
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if (gl->glsl_version < 140)
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gl_sc_enable_extension(sc, "GL_ARB_uniform_buffer_object");
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} else if (conf->upload == NNEDI3_UPLOAD_SHADER) {
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// Somehow necessary for hard coding approach.
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GLSLH(#pragma optionNV(fastprecision on))
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}
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GLSLHF("float nnedi3(sampler2D tex, vec2 pos, vec2 tex_size, int plane, float tex_mul) {\n");
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if (step == 0) {
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*transform = (struct gl_transform){{{1.0,0.0}, {0.0,2.0}}, {0.0,-0.5}};
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GLSLH(if (fract(pos.y * tex_size.y) < 0.5)
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return texture(tex, pos + vec2(0, 0.25) / tex_size)[plane] * tex_mul;)
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GLSLHF("#define GET(i, j) "
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"(texture(tex, pos+vec2((i)-(%f),(j)-(%f)+0.25)/tex_size)[plane]*tex_mul)\n",
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width / 2.0 - 1, (height - 1) / 2.0);
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} else {
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*transform = (struct gl_transform){{{2.0,0.0}, {0.0,1.0}}, {-0.5,0.0}};
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GLSLH(if (fract(pos.x * tex_size.x) < 0.5)
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return texture(tex, pos + vec2(0.25, 0) / tex_size)[plane] * tex_mul;)
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GLSLHF("#define GET(i, j) "
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"(texture(tex, pos+vec2((j)-(%f)+0.25,(i)-(%f))/tex_size)[plane]*tex_mul)\n",
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(height - 1) / 2.0, width / 2.0 - 1);
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}
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GLSLHF("vec4 samples[%d];\n", sample_count);
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for (int y = 0; y < height; y++)
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for (int x = 0; x < width; x += 4) {
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GLSLHF("samples[%d] = vec4(GET(%d, %d), GET(%d, %d),"
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"GET(%d, %d), GET(%d, %d));\n",
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(y * width + x) / 4, x, y, x+1, y, x+2, y, x+3, y);
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}
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GLSLHF("float sum = 0, sumsq = 0;"
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"for (int i = 0; i < %d; i++) {"
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"sum += dot(samples[i], vec4(1.0));"
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"sumsq += dot(samples[i], samples[i]);"
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"}\n", sample_count);
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GLSLHF("float mstd0 = sum / %d.0;\n"
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"float mstd1 = sumsq / %d.0 - mstd0 * mstd0;\n"
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"float mstd2 = mix(0, inversesqrt(mstd1), mstd1 >= %.12e);\n"
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"mstd1 *= mstd2;\n",
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width * height, width * height, FLT_EPSILON);
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GLSLHF("float vsum = 0, wsum = 0, sum1, sum2;\n");
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if (conf->upload == NNEDI3_UPLOAD_SHADER) {
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GLSLH(#define T(x) intBitsToFloat(x))
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GLSLH(#define W(i,w0,w1,w2,w3) dot(samples[i],vec4(T(w0),T(w1),T(w2),T(w3))))
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GLSLHF("#define WS(w0,w1) "
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"sum1 = exp(sum1 * mstd2 + T(w0));"
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"sum2 = sum2 * mstd2 + T(w1);"
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"wsum += sum1;"
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"vsum += sum1*(sum2/(1+abs(sum2)));\n");
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for (int n = 0; n < neurons; n++) {
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const uint32_t *weights_ptr = weights + (sample_count * 2 + 1) * 4 * n;
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for (int s = 0; s < 2; s++) {
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GLSLHF("sum%d", s + 1);
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for (int i = 0; i < sample_count; i++) {
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GLSLHF("%cW(%d,%d,%d,%d,%d)", i == 0 ? '=' : '+', i,
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(int)av_le2ne32(weights_ptr[0]),
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(int)av_le2ne32(weights_ptr[1]),
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(int)av_le2ne32(weights_ptr[2]),
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(int)av_le2ne32(weights_ptr[3]));
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weights_ptr += 4;
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}
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GLSLHF(";");
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}
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GLSLHF("WS(%d,%d);\n", (int)av_le2ne32(weights_ptr[0]),
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(int)av_le2ne32(weights_ptr[1]));
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}
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} else if (conf->upload == NNEDI3_UPLOAD_UBO) {
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GLSLH(int idx = 0;)
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GLSLHF("for (int n = 0; n < %d; n++) {\n", neurons);
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for (int s = 0; s < 2; s++) {
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GLSLHF("sum%d = 0;\n"
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"for (int i = 0; i < %d; i++) {"
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"sum%d += dot(samples[i], weights[idx++]);"
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"}\n",
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s + 1, sample_count, s + 1);
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}
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GLSLH(sum1 = exp(sum1 * mstd2 + weights[idx][0]);
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sum2 = sum2 * mstd2 + weights[idx++][1];
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wsum += sum1;
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vsum += sum1*(sum2/(1+abs(sum2)));)
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GLSLHF("}\n");
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}
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GLSLH(return clamp(mstd0 + 5.0 * vsum / wsum * mstd1, 0, 1);)
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GLSLHF("}\n"); // nnedi3
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GLSL(vec4 color = vec4(1.0);)
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for (int i = 0; i < planes; i++) {
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GLSLF("color[%d] = nnedi3(texture%d, texcoord%d, texture_size%d, %d, %f);\n",
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i, tex_num, tex_num, tex_num, i, tex_mul);
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}
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}
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