From f9bb7963a9d42e6e3e2d2ae2ecc57f7abe4a6190 Mon Sep 17 00:00:00 2001
From: Sergey Lavrushkin <dualfal@gmail.com>
Date: Tue, 10 Apr 2018 19:41:40 +0300
Subject: [PATCH] Adds SRCNN filter.
---
Changelog | 1 +
libavfilter/Makefile | 1 +
libavfilter/allfilters.c | 1 +
libavfilter/vf_srcnn.c | 420 +++++++++++++++++++++++
libavfilter/vf_srcnn.h | 852 +++++++++++++++++++++++++++++++++++++++++++++++
5 files changed, 1275 insertions(+)
create mode 100644 libavfilter/vf_srcnn.c
create mode 100644 libavfilter/vf_srcnn.h
@@ -53,6 +53,7 @@ version <next>:
- bitstream filter for extracting E-AC-3 core
- Haivision SRT protocol via libsrt
- segafilm muxer
+- SRCNN filter
version 3.4:
@@ -327,6 +327,7 @@ OBJS-$(CONFIG_SMARTBLUR_FILTER) += vf_smartblur.o
OBJS-$(CONFIG_SOBEL_FILTER) += vf_convolution.o
OBJS-$(CONFIG_SPLIT_FILTER) += split.o
OBJS-$(CONFIG_SPP_FILTER) += vf_spp.o
+OBJS-$(CONFIG_SRCNN_FILTER) += vf_srcnn.o
OBJS-$(CONFIG_SSIM_FILTER) += vf_ssim.o framesync.o
OBJS-$(CONFIG_STEREO3D_FILTER) += vf_stereo3d.o
OBJS-$(CONFIG_STREAMSELECT_FILTER) += f_streamselect.o framesync.o
@@ -318,6 +318,7 @@ extern AVFilter ff_vf_smartblur;
extern AVFilter ff_vf_sobel;
extern AVFilter ff_vf_split;
extern AVFilter ff_vf_spp;
+extern AVFilter ff_vf_srcnn;
extern AVFilter ff_vf_ssim;
extern AVFilter ff_vf_stereo3d;
extern AVFilter ff_vf_streamselect;
new file mode 100644
@@ -0,0 +1,420 @@
+/*
+ * Copyright (c) 2018 Sergey Lavrushkin
+ *
+ * This file is part of FFmpeg.
+ *
+ * FFmpeg is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public
+ * License as published by the Free Software Foundation; either
+ * version 2.1 of the License, or (at your option) any later version.
+ *
+ * FFmpeg is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with FFmpeg; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
+ */
+
+/**
+ * @file
+ * Filter implementing image super-resolution using deep convolutional networks.
+ * https://arxiv.org/abs/1501.00092
+ */
+
+#include "avfilter.h"
+#include "formats.h"
+#include "internal.h"
+#include "libavutil/opt.h"
+#include "unistd.h"
+#include "vf_srcnn.h"
+#include "libavformat/avio.h"
+
+typedef struct Convolution
+{
+ double* kernel;
+ double* biases;
+ int32_t size, input_channels, output_channels;
+} Convolution;
+
+typedef struct SRCNNContext {
+ const AVClass *class;
+
+ /// SRCNN convolutions
+ struct Convolution conv1, conv2, conv3;
+ /// Path to binary file with kernels specifications
+ char* config_file_path;
+ /// Buffers for network input/output and feature maps
+ double* input_output_buf;
+ double* conv1_buf;
+ double* conv2_buf;
+} SRCNNContext;
+
+
+#define OFFSET(x) offsetof(SRCNNContext, x)
+#define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM
+static const AVOption srcnn_options[] = {
+ { "config_file", "path to configuration file with network parameters", OFFSET(config_file_path), AV_OPT_TYPE_STRING, {.str=NULL}, 0, 0, FLAGS },
+ { NULL }
+};
+
+AVFILTER_DEFINE_CLASS(srcnn);
+
+#define CHECK_FILE_SIZE(file_size, srcnn_size, avio_context) if (srcnn_size > file_size){ \
+ av_log(context, AV_LOG_ERROR, "error reading configuration file\n");\
+ avio_closep(&avio_context); \
+ return AVERROR(EIO); \
+ }
+
+#define CHECK_ALLOCATION(call, end_call) if (call){ \
+ av_log(context, AV_LOG_ERROR, "could not allocate memory for convolutions\n"); \
+ end_call; \
+ return AVERROR(ENOMEM); \
+ }
+
+static int allocate_read_conv_data(Convolution* conv, AVIOContext* config_file_context)
+{
+ int32_t kernel_size = conv->output_channels * conv->size * conv->size * conv->input_channels;
+ int32_t i;
+
+ conv->kernel = av_malloc(kernel_size * sizeof(double));
+ if (!conv->kernel){
+ return AVERROR(ENOMEM);
+ }
+ for (i = 0; i < kernel_size; ++i){
+ conv->kernel[i] = av_int2double(avio_rl64(config_file_context));
+ }
+
+ conv->biases = av_malloc(conv->output_channels * sizeof(double));
+ if (!conv->biases){
+ return AVERROR(ENOMEM);
+ }
+ for (i = 0; i < conv->output_channels; ++i){
+ conv->biases[i] = av_int2double(avio_rl64(config_file_context));
+ }
+
+ return 0;
+}
+
+static int allocate_copy_conv_data(Convolution* conv, const double* kernel, const double* biases)
+{
+ int32_t kernel_size = conv->output_channels * conv->size * conv->size * conv->input_channels;
+
+ conv->kernel = av_malloc(kernel_size * sizeof(double));
+ if (!conv->kernel){
+ return AVERROR(ENOMEM);
+ }
+ memcpy(conv->kernel, kernel, kernel_size * sizeof(double));
+
+ conv->biases = av_malloc(conv->output_channels * sizeof(double));
+ if (!conv->kernel){
+ return AVERROR(ENOMEM);
+ }
+ memcpy(conv->biases, biases, conv->output_channels * sizeof(double));
+
+ return 0;
+}
+
+static av_cold int init(AVFilterContext* context)
+{
+ SRCNNContext *srcnn_context = context->priv;
+ AVIOContext* config_file_context;
+ int64_t file_size, srcnn_size;
+
+ /// Check specified confguration file name and read network weights from it
+ if (!srcnn_context->config_file_path){
+ av_log(context, AV_LOG_INFO, "configuration file for network was not specified, using default weights for x2 upsampling\n");
+
+ /// Create convolution kernels and copy default weights
+ srcnn_context->conv1.input_channels = 1;
+ srcnn_context->conv1.output_channels = 64;
+ srcnn_context->conv1.size = 9;
+ CHECK_ALLOCATION(allocate_copy_conv_data(&srcnn_context->conv1, conv1_kernel, conv1_biases), )
+
+ srcnn_context->conv2.input_channels = 64;
+ srcnn_context->conv2.output_channels = 32;
+ srcnn_context->conv2.size = 1;
+ CHECK_ALLOCATION(allocate_copy_conv_data(&srcnn_context->conv2, conv2_kernel, conv2_biases), )
+
+ srcnn_context->conv3.input_channels = 32;
+ srcnn_context->conv3.output_channels = 1;
+ srcnn_context->conv3.size = 5;
+ CHECK_ALLOCATION(allocate_copy_conv_data(&srcnn_context->conv3, conv3_kernel, conv3_biases), )
+ }
+ else if (access(srcnn_context->config_file_path, R_OK) != -1){
+ if (avio_open(&config_file_context, srcnn_context->config_file_path, AVIO_FLAG_READ) < 0){
+ av_log(context, AV_LOG_ERROR, "failed to open configuration file\n");
+ return AVERROR(EIO);
+ }
+
+ file_size = avio_size(config_file_context);
+
+ /// Create convolution kernels and read weights from file
+ srcnn_context->conv1.input_channels = 1;
+ srcnn_context->conv1.size = (int32_t)avio_rl32(config_file_context);
+ srcnn_context->conv1.output_channels = (int32_t)avio_rl32(config_file_context);
+ srcnn_size = 8 + (srcnn_context->conv1.output_channels * srcnn_context->conv1.size *
+ srcnn_context->conv1.size * srcnn_context->conv1.input_channels +
+ srcnn_context->conv1.output_channels << 3);
+ CHECK_FILE_SIZE(file_size, srcnn_size, config_file_context)
+ CHECK_ALLOCATION(allocate_read_conv_data(&srcnn_context->conv1, config_file_context), avio_closep(&config_file_context))
+
+ srcnn_context->conv2.input_channels = (int32_t)avio_rl32(config_file_context);
+ srcnn_context->conv2.size = (int32_t)avio_rl32(config_file_context);
+ srcnn_context->conv2.output_channels = (int32_t)avio_rl32(config_file_context);
+ srcnn_size += 12 + (srcnn_context->conv2.output_channels * srcnn_context->conv2.size *
+ srcnn_context->conv2.size * srcnn_context->conv2.input_channels +
+ srcnn_context->conv2.output_channels << 3);
+ CHECK_FILE_SIZE(file_size, srcnn_size, config_file_context)
+ CHECK_ALLOCATION(allocate_read_conv_data(&srcnn_context->conv2, config_file_context), avio_closep(&config_file_context))
+
+ srcnn_context->conv3.input_channels = (int32_t)avio_rl32(config_file_context);
+ srcnn_context->conv3.size = (int32_t)avio_rl32(config_file_context);
+ srcnn_context->conv3.output_channels = 1;
+ srcnn_size += 8 + (srcnn_context->conv3.output_channels * srcnn_context->conv3.size *
+ srcnn_context->conv3.size * srcnn_context->conv3.input_channels
+ + srcnn_context->conv3.output_channels << 3);
+ if (file_size != srcnn_size){
+ av_log(context, AV_LOG_ERROR, "error reading configuration file\n");
+ avio_closep(&config_file_context);
+ return AVERROR(EIO);
+ }
+ CHECK_ALLOCATION(allocate_read_conv_data(&srcnn_context->conv3, config_file_context), avio_closep(&config_file_context))
+
+ avio_closep(&config_file_context);
+ }
+ else{
+ av_log(context, AV_LOG_ERROR, "specified configuration file does not exist or not readable\n");
+ return AVERROR(EIO);
+ }
+
+ return 0;
+}
+
+static int query_formats(AVFilterContext* context)
+{
+ const enum AVPixelFormat pixel_formats[] = {AV_PIX_FMT_YUV420P, AV_PIX_FMT_YUV422P, AV_PIX_FMT_YUV444P,
+ AV_PIX_FMT_YUV410P, AV_PIX_FMT_YUV411P, AV_PIX_FMT_GRAY8,
+ AV_PIX_FMT_NONE};
+ AVFilterFormats *formats_list;
+
+ formats_list = ff_make_format_list(pixel_formats);
+ if (!formats_list){
+ av_log(context, AV_LOG_ERROR, "could not create formats list\n");
+ return AVERROR(ENOMEM);
+ }
+ return ff_set_common_formats(context, formats_list);
+}
+
+static int config_props(AVFilterLink* inlink)
+{
+ AVFilterContext *context = inlink->dst;
+ SRCNNContext *srcnn_context = context->priv;
+ int min_dim;
+
+ /// Check if input data width or height is too low
+ min_dim = FFMIN(inlink->w, inlink->h);
+ if (min_dim <= srcnn_context->conv1.size >> 1 || min_dim <= srcnn_context->conv2.size >> 1 || min_dim <= srcnn_context->conv3.size >> 1){
+ av_log(context, AV_LOG_ERROR, "input width or height is too low\n");
+ return AVERROR(EIO);
+ }
+
+ /// Allocate network buffers
+ srcnn_context->input_output_buf = av_malloc(inlink->h * inlink->w * sizeof(double));
+ srcnn_context->conv1_buf = av_malloc(inlink->h * inlink->w * srcnn_context->conv1.output_channels * sizeof(double));
+ srcnn_context->conv2_buf = av_malloc(inlink->h * inlink->w * srcnn_context->conv2.output_channels * sizeof(double));
+
+ if (!srcnn_context->input_output_buf || !srcnn_context->conv1_buf || !srcnn_context->conv2_buf){
+ av_log(context, AV_LOG_ERROR, "could not allocate memory for srcnn buffers\n");
+ return AVERROR(ENOMEM);
+ }
+
+ return 0;
+}
+
+typedef struct ThreadData{
+ uint8_t* out;
+ int out_linesize, height, width;
+} ThreadData;
+
+typedef struct ConvThreadData
+{
+ const Convolution* conv;
+ const double* input;
+ double* output;
+ int height, width;
+} ConvThreadData;
+
+/// Convert uint8 data to double and scale it to use in network
+static int uint8_to_double(AVFilterContext* context, void* arg, int jobnr, int nb_jobs)
+{
+ SRCNNContext* srcnn_context = context->priv;
+ const ThreadData* td = arg;
+ const int slice_start = (td->height * jobnr ) / nb_jobs;
+ const int slice_end = (td->height * (jobnr + 1)) / nb_jobs;
+ const uint8_t* src = td->out + slice_start * td->out_linesize;
+ double* dst = srcnn_context->input_output_buf + slice_start * td->width;
+ int y, x;
+
+ for (y = slice_start; y < slice_end; ++y){
+ for (x = 0; x < td->width; ++x){
+ dst[x] = (double)src[x] / 255.0;
+ }
+ src += td->out_linesize;
+ dst += td->width;
+ }
+
+ return 0;
+}
+
+/// Convert double data from network to uint8 and scale it to output as filter result
+static int double_to_uint8(AVFilterContext* context, void* arg, int jobnr, int nb_jobs)
+{
+ SRCNNContext* srcnn_context = context->priv;
+ const ThreadData* td = arg;
+ const int slice_start = (td->height * jobnr ) / nb_jobs;
+ const int slice_end = (td->height * (jobnr + 1)) / nb_jobs;
+ const double* src = srcnn_context->input_output_buf + slice_start * td->width;
+ uint8_t* dst = td->out + slice_start * td->out_linesize;
+ int y, x;
+
+ for (y = slice_start; y < slice_end; ++y){
+ for (x = 0; x < td->width; ++x){
+ dst[x] = (uint8_t)(255.0 * FFMIN(src[x], 1.0));
+ }
+ src += td->width;
+ dst += td->out_linesize;
+ }
+
+ return 0;
+}
+
+#define CLAMP_TO_EDGE(x, w) ((x) < 0 ? 0 : ((x) >= (w) ? (w - 1) : (x)))
+
+static int convolve(AVFilterContext* context, void* arg, int jobnr, int nb_jobs)
+{
+ const ConvThreadData* td = arg;
+ const int slice_start = (td->height * jobnr ) / nb_jobs;
+ const int slice_end = (td->height * (jobnr + 1)) / nb_jobs;
+ const double* src = td->input;
+ double* dst = td->output + slice_start * td->width * td->conv->output_channels;
+ int y, x;
+ int32_t n_filter, ch, kernel_y, kernel_x;
+ int32_t radius = td->conv->size >> 1;
+ int src_linesize = td->width * td->conv->input_channels;
+ int filter_linesize = td->conv->size * td->conv->input_channels;
+ int filter_size = td->conv->size * filter_linesize;
+
+ for (y = slice_start; y < slice_end; ++y){
+ for (x = 0; x < td->width; ++x){
+ for (n_filter = 0; n_filter < td->conv->output_channels; ++n_filter){
+ dst[n_filter] = td->conv->biases[n_filter];
+ for (ch = 0; ch < td->conv->input_channels; ++ch){
+ for (kernel_y = 0; kernel_y < td->conv->size; ++kernel_y){
+ for (kernel_x = 0; kernel_x < td->conv->size; ++kernel_x){
+ dst[n_filter] += src[CLAMP_TO_EDGE(y + kernel_y - radius, td->height) * src_linesize +
+ CLAMP_TO_EDGE(x + kernel_x - radius, td->width) * td->conv->input_channels + ch] *
+ td->conv->kernel[n_filter * filter_size + kernel_y * filter_linesize +
+ kernel_x * td->conv->input_channels + ch];
+ }
+ }
+ }
+ dst[n_filter] = FFMAX(dst[n_filter], 0.0);
+ }
+ dst += td->conv->output_channels;
+ }
+ }
+
+ return 0;
+}
+
+static int filter_frame(AVFilterLink* inlink, AVFrame* in)
+{
+ AVFilterContext* context = inlink->dst;
+ SRCNNContext* srcnn_context = context->priv;
+ AVFilterLink* outlink = context->outputs[0];
+ AVFrame* out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
+ ThreadData td;
+ ConvThreadData ctd;
+
+ if (!out){
+ av_log(context, AV_LOG_ERROR, "could not allocate memory for output frame\n");
+ av_frame_free(&in);
+ return AVERROR(ENOMEM);
+ }
+ av_frame_copy_props(out, in);
+ av_frame_copy(out, in);
+ av_frame_free(&in);
+ td.out = out->data[0];
+ td.out_linesize = out->linesize[0];
+ td.height = ctd.height = out->height;
+ td.width = ctd.width = out->width;
+
+ context->internal->execute(context, uint8_to_double, &td, NULL, FFMIN(td.height, context->graph->nb_threads));
+ ctd.conv = &srcnn_context->conv1;
+ ctd.input = srcnn_context->input_output_buf;
+ ctd.output = srcnn_context->conv1_buf;
+ context->internal->execute(context, convolve, &ctd, NULL, FFMIN(ctd.height, context->graph->nb_threads));
+ ctd.conv = &srcnn_context->conv2;
+ ctd.input = srcnn_context->conv1_buf;
+ ctd.output = srcnn_context->conv2_buf;
+ context->internal->execute(context, convolve, &ctd, NULL, FFMIN(ctd.height, context->graph->nb_threads));
+ ctd.conv = &srcnn_context->conv3;
+ ctd.input = srcnn_context->conv2_buf;
+ ctd.output = srcnn_context->input_output_buf;
+ context->internal->execute(context, convolve, &ctd, NULL, FFMIN(ctd.height, context->graph->nb_threads));
+ context->internal->execute(context, double_to_uint8, &td, NULL, FFMIN(td.height, context->graph->nb_threads));
+
+ return ff_filter_frame(outlink, out);
+}
+
+static av_cold void uninit(AVFilterContext* context)
+{
+ SRCNNContext* srcnn_context = context->priv;
+
+ /// Free convolution data
+ av_freep(&srcnn_context->conv1.kernel);
+ av_freep(&srcnn_context->conv1.biases);
+ av_freep(&srcnn_context->conv2.kernel);
+ av_freep(&srcnn_context->conv2.biases);
+ av_freep(&srcnn_context->conv3.kernel);
+ av_freep(&srcnn_context->conv3.kernel);
+
+ /// Free network buffers
+ av_freep(&srcnn_context->input_output_buf);
+ av_freep(&srcnn_context->conv1_buf);
+ av_freep(&srcnn_context->conv2_buf);
+}
+
+static const AVFilterPad srcnn_inputs[] = {
+ {
+ .name = "default",
+ .type = AVMEDIA_TYPE_VIDEO,
+ .config_props = config_props,
+ .filter_frame = filter_frame,
+ },
+ { NULL }
+};
+
+static const AVFilterPad srcnn_outputs[] = {
+ {
+ .name = "default",
+ .type = AVMEDIA_TYPE_VIDEO,
+ },
+ { NULL }
+};
+
+AVFilter ff_vf_srcnn = {
+ .name = "srcnn",
+ .description = NULL_IF_CONFIG_SMALL("Apply super resolution convolutional neural network to the input. Use bicubic upsamping with corresponding scaling factor before."),
+ .priv_size = sizeof(SRCNNContext),
+ .init = init,
+ .uninit = uninit,
+ .query_formats = query_formats,
+ .inputs = srcnn_inputs,
+ .outputs = srcnn_outputs,
+ .priv_class = &srcnn_class,
+ .flags = AVFILTER_FLAG_SUPPORT_TIMELINE_GENERIC | AVFILTER_FLAG_SLICE_THREADS,
+};
new file mode 100644
@@ -0,0 +1,852 @@
+/*
+ * Copyright (c) 2018 Sergey Lavrushkin
+ *
+ * This file is part of FFmpeg.
+ *
+ * FFmpeg is free software; you can redistribute it and/or
+ * modify it under the terms of the GNU Lesser General Public
+ * License as published by the Free Software Foundation; either
+ * version 2.1 of the License, or (at your option) any later version.
+ *
+ * FFmpeg is distributed in the hope that it will be useful,
+ * but WITHOUT ANY WARRANTY; without even the implied warranty of
+ * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
+ * Lesser General Public License for more details.
+ *
+ * You should have received a copy of the GNU Lesser General Public
+ * License along with FFmpeg; if not, write to the Free Software
+ * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
+ */
+
+/**
+ * @file
+ * Default cnn weights for x2 upsampling with srcnn filter.
+ */
+
+/// First convolution kernel
+static const double conv1_kernel[] = {
+-0.08866337686777115, 0.055409565567970276, 0.037196505814790726, -0.11961404234170914, -0.12341991066932678, 0.2996342182159424, -0.09118170291185379, -0.00013613555347546935, -0.049023594707250595,
+0.038421183824539185, -0.07726779580116272, 0.027273094281554222, 0.45762088894844055, 0.023581644520163536, -0.20363852381706238, -0.07738441973924637, 0.07288403809070587, 0.06679897010326385,
+-0.07315085083246231, 0.2665306031703949, 0.07836370915174484, -0.2898528277873993, -0.506912887096405, 0.0446651317179203, -0.06246858835220337, -0.024424826726317406, -0.029072929173707962,
+-0.16884787380695343, 0.20686236023902893, -0.2536700665950775, -0.38499701023101807, -0.12601901590824127, 0.7257882356643677, 0.09588377922773361, -0.04487278312444687, -0.011251595802605152,
+-0.02955852635204792, 0.2211706042289734, -0.3845316469669342, -0.053509537130594254, 0.10955915600061417, 0.3725738823413849, -0.28968045115470886, -0.10883618891239166, 0.19628790020942688,
+0.09746792912483215, -0.005647096782922745, -0.13035884499549866, 0.6254252195358276, 0.19104234874248505, -0.011692332103848457, -0.27067890763282776, -0.030754156410694122, 0.029875505715608597,
+0.016808750107884407, -0.1831790804862976, -0.16016070544719696, 0.3598291277885437, -0.1889011114835739, -0.22343340516090393, -0.11111768335103989, 0.3221142590045929, -0.18514074385166168,
+-0.06647012382745743, 0.1800554096698761, -0.0356597937643528, -0.25352174043655396, -0.18370479345321655, 0.2839542329311371, 0.0030237233731895685, 0.24072711169719696, -0.1435547173023224,
+0.0474187433719635, -0.03221237286925316, -0.08801338076591492, 0.2959175109863281, 0.04108741134405136, -0.103544220328331, -0.11681117117404938, -0.010267493315041065, 0.023703521117568016,
+
+-0.043954458087682724, 0.0953388437628746, 0.12233797460794449, -0.0521148182451725, 0.068812295794487, 0.0576486811041832, 0.08686650544404984, -0.12001238018274307, 0.02353638783097267,
+-0.022270673885941505, -0.06377912312746048, 0.010644146241247654, -0.27824145555496216, -0.23719865083694458, -0.21418367326259613, -0.09665020555257797, 0.10458534955978394, 0.06599418818950653,
+-0.031174281612038612, -0.03465353325009346, 0.022143816575407982, -0.24322354793548584, -0.08923598378896713, -0.02724810689687729, -0.09314896911382675, -0.03740973770618439, 0.07819665223360062,
+0.12521375715732574, 0.11189836263656616, 0.34981977939605713, 0.24303556978702545, 0.21350803971290588, 0.3712073266506195, 0.12192775309085846, -0.15492133796215057, 0.01884031854569912,
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+0.002784173935651779, 0.01319826114922762, 0.03299565985798836, -0.009061452932655811, -0.03782084956765175, 0.05905524268746376, 0.03665812313556671, -0.03293836489319801, 0.007655598223209381,
+-0.02654659003019333, -0.051362812519073486, -0.019685762003064156, -0.04363385960459709, -0.033689528703689575, -0.04015159234404564, -0.030751371756196022, -0.02246842533349991, 0.018601812422275543,
+0.012158050201833248, 0.015349633991718292, 0.03493561968207359, -0.01330295018851757, 0.03794550150632858, -0.003826811444014311, -0.044383760541677475, -0.07613663375377655, 0.014979931525886059,
+0.0436096116900444, 0.06885120272636414, 0.09881002455949783, 0.031302209943532944, 0.12420085072517395, 0.15065008401870728, 0.07978155463933945, -0.027734771370887756, -0.05383369326591492,
+-0.0678027868270874, 0.002182385651394725, 0.13103488087654114, 0.05609790235757828, 0.05619135499000549, 0.08134319633245468, 0.10918274521827698, 0.10301676392555237, -0.02375829964876175,
+-0.08856120705604553, -0.03078402765095234, 0.08737516403198242, 0.013652728870511055, 0.01163883414119482, -0.00604214845225215, 0.056429434567689896, 0.10691829025745392, 0.041128937155008316,
+-0.04340420290827751, -0.002507368801161647, 0.012957162223756313, 0.012340170331299305, 0.11861597746610641, 0.09244049340486526, 0.034744489938020706, -0.024895809590816498, 0.035870663821697235,
+-0.040758680552244186, 0.013552304357290268, -0.009587780572474003, 0.01752828061580658, 0.07450903207063675, 0.0692441463470459, 0.0011354148155078292, -0.06966304779052734, 0.008092116564512253,
+0.02915072999894619, 0.04350604489445686, -0.03975748270750046, 0.014310178346931934, 0.0008435412310063839, -0.013759381137788296, 0.02635800465941429, 0.08823874592781067, 0.0821344256401062
+};
+
+/// First convolution biases
+static const double conv1_biases[] = {
+-0.01660689152777195,
+-0.011107334867119789,
+-0.00483096856623888,
+-0.048673778772354126,
+-0.030040957033634186,
+-0.07297247648239136,
+-0.01945866458117962,
+-0.009738028049468994,
+0.6951230764389038,
+-0.07369442284107208,
+-0.01354204025119543,
+0.010336088016629219,
+-0.02956176921725273,
+0.018691286444664,
+-0.02167515829205513,
+0.004088825546205044,
+-0.08033090084791183,
+-0.02080247923731804,
+-0.00025044166250154376,
+0.015665635466575623,
+-0.024439847096800804,
+-0.00014609392383135855,
+-5.004818376619369e-05,
+-0.0011854040203616023,
+-8.353819430340081e-05,
+0.0,
+-0.00037626884295605123,
+0.02971580997109413,
+-9.940328891389072e-05,
+-0.020136557519435883,
+-0.00029498152434825897,
+0.019285818561911583,
+0.005577716510742903,
+-0.0700315311551094,
+-0.024398552253842354,
+-1.7726930309436284e-05,
+0.0050997124053537846,
+-0.011211924254894257,
+0.004536128137260675,
+-0.024612177163362503,
+-0.0225357823073864,
+-0.00016232267080340534,
+-0.00017362962535116822,
+-1.552602043375373e-05,
+-0.06559696048498154,
+-0.0065806107595562935,
+6.683926585537847e-06,
+0.0252289529889822,
+-0.0013730665668845177,
+0.030351819470524788,
+0.0,
+0.003285621991381049,
+0.0055278814397752285,
+0.020766519010066986,
+-0.00849062204360962,
+0.026332268491387367,
+-0.04678987339138985,
+0.010329566895961761,
+-0.023649320006370544,
+0.027851572260260582,
+0.05440746247768402,
+-0.08068252354860306,
+-0.009446502663195133,
+-0.04663233831524849
+};
+
+/// Second convolution kernel
+static const double conv2_kernel[] = {
+-0.24004751443862915, 0.10371380299329758, 0.11173403263092041, 0.04352091997861862, -0.2372848093509674, 0.1215374693274498, -0.23676058650016785, -0.28548064827919006, -0.6127380132675171, -0.12218937277793884, -0.06005159020423889, 0.18506519496440887, 0.16014674305915833, 0.13922938704490662, 0.2135942578315735, 0.10787945240736008, -0.26999104022979736, -0.14241325855255127, -0.0013871012488380075, -0.004951587878167629, 0.3402169644832611, 0.0005581695586442947, 4.7351106331916526e-05, 0.0037513396237045527, 0.0011569701600819826, 0.001654176157899201, -0.0011876021744683385, 0.049887992441654205, -7.201619882835075e-05, -0.17735491693019867, 0.0011244657216593623, -0.22381487488746643, 0.0035836962051689625, -0.3210694193840027, -0.16167263686656952, -0.0007922835648059845, 0.05056063085794449, 0.21074672043323517, 0.07716237753629684, -0.3315621614456177, 0.06265880912542343, 0.0002542850561439991, -0.0012989661190658808, 0.0004486947145778686, -0.41594547033309937, -0.019950004294514656, 0.0002566903131082654, 0.17913155257701874, -0.5950504541397095, 0.3259836733341217, 0.0013792524114251137, -0.08931709825992584, -0.13066786527633667, 0.21108511090278625, -0.05854453891515732, -0.11937838047742844, 0.08559372276067734, -0.11413642764091492, 0.28384047746658325, -0.011619674041867256, 0.32102328538894653, -0.20085231959819794, -0.34134379029273987, -0.029155191034078598,
+
+-0.15286806225776672, -0.45100340247154236, -0.07077684253454208, 0.14408659934997559, 0.05953073874115944, -0.03657171502709389, 0.3870140314102173, -0.12762507796287537, 0.059950776398181915, 0.00540902791544795, 0.16427578032016754, -0.042501527816057205, 0.032962359488010406, -0.19972456991672516, -0.2558594048023224, -0.05479712411761284, -0.1335245817899704, 0.051931269466876984, -0.0005906695732846856, 0.14123854041099548, -0.06595169752836227, 0.0002593870449345559, 0.0004935731994919479, 0.0018757024081423879, -0.0004157331713940948, 0.0006128620007075369, -0.0008253702544607222, 0.00875023566186428, 0.000315613579005003, -0.031592708081007004, -0.0011055622017011046, 0.5397407412528992, 0.16837793588638306, 0.10016077756881714, -0.04458073899149895, -0.0008208212675526738, 0.14558495581150055, 0.05370355769991875, 0.3998671770095825, 0.3651335835456848, -6.220484647201374e-05, -0.0015507896896451712, 0.00019759316637646407, 0.001477571902796626, 0.17199119925498962, 0.20428548753261566, 0.0007169281598180532, -0.15589089691638947, 0.13173037767410278, 0.0430227592587471, 0.0005358970374800265, -0.14488573372364044, -0.056273844093084335, 0.04060659557580948, 0.12327120453119278, -0.0687263160943985, 0.1168481707572937, 0.20592212677001953, -0.07642778009176254, -0.10591034591197968, -0.2585831880569458, -0.234173983335495, 0.1204083263874054, -0.09154298901557922,
+
+0.1729278564453125, 0.12093151360750198, 0.12173106521368027, -0.17765463888645172, -0.03842559829354286, 0.1379096508026123, -0.018014583736658096, -0.00353326671756804, 0.052375391125679016, -0.013713608495891094, -0.023778876289725304, 0.08754374086856842, 0.009544276632368565, 0.002218334935605526, 0.005476833321154118, 0.14335989952087402, -0.30521509051322937, -0.027671312913298607, 0.0002961017016787082, -0.09087705612182617, 0.08001929521560669, 0.000289166287984699, 8.447665459243581e-05, 0.0032733778934925795, -0.0009773650672286749, 0.000969415414147079, 0.0023891173768788576, 0.1590563803911209, 0.00069234031252563, -0.23975391685962677, 0.0003552400739863515, -0.15277449786663055, 0.09689000993967056, -0.13403186202049255, -0.10830442607402802, -0.0011496500810608268, -0.0791272521018982, -0.04548552632331848, 0.07143749296665192, -0.11953869462013245, 0.06519463658332825, 0.0004770815430674702, -0.0012068727519363165, 0.00023571185010951012, -0.02185177616775036, -0.10972553491592407, -0.0004428153915796429, -0.06199837476015091, -0.02185823768377304, 0.13159608840942383, 0.0011464811395853758, -0.12141252309083939, -0.06273757666349411, 0.2553664743900299, 0.1002097874879837, 0.13120368123054504, 0.16516226530075073, -0.14927655458450317, 0.14413973689079285, 0.039363794028759, 0.19443942606449127, -0.01614764891564846, -0.0876186192035675, 0.08571985363960266,
+
+-0.034732215106487274, 0.08880914747714996, 0.115323506295681, -0.2509199380874634, -0.18177348375320435, 0.11170994490385056, -0.06447608023881912, -0.04730312153697014, -0.13159127533435822, 0.01896033063530922, -0.2969268262386322, 0.31513679027557373, 0.016690406948328018, 0.0855814516544342, 0.01695072464644909, 0.1360795795917511, -0.008597755804657936, -0.15839214622974396, -0.0006356500089168549, 0.14604529738426208, 0.029391299933195114, -0.0021237179171293974, -0.0021662425715476274, 0.0011421579401940107, 0.00031981870415620506, -0.00031888089142739773, -0.0013892676215618849, 0.4037177860736847, 0.0010367054492235184, -0.08923333138227463, 0.001726223505102098, 0.04937814548611641, 0.03052854910492897, -0.10994968563318253, 0.041772034019231796, -0.0003509650705382228, -0.09172547608613968, -0.1121240183711052, 0.018248941749334335, -0.1032114252448082, 0.03656036779284477, -0.0008534444496035576, 0.0005108112818561494, 0.001955348066985607, -0.17280977964401245, -0.15745718777179718, 0.0016406632494181395, 0.10295743495225906, -0.056333065032958984, 0.12174493074417114, -0.00029968394665047526, -0.046295735985040665, -0.05203622952103615, 0.17915867269039154, 0.17138905823230743, 0.20149874687194824, 0.14662422239780426, -0.06499027460813522, 0.0864318460226059, 0.026575079187750816, -0.26568517088890076, -0.10079117864370346, -0.20195038616657257, 0.07289135456085205,
+
+0.20596843957901, 0.1484273374080658, 0.11689981073141098, -0.292439341545105, 0.02092818170785904, 0.14047744870185852, -0.032774657011032104, 0.013994990848004818, 0.04893071949481964, -0.0856017917394638, 0.07281561940908432, 0.0699431449174881, -0.006538144778460264, 0.08474163711071014, 0.013837413862347603, 0.10437792539596558, -0.32318544387817383, -0.033461928367614746, -0.0006234075990505517, -0.25232645869255066, 0.08134997636079788, -0.0012573037529364228, -0.00025874844868667424, 0.002164048608392477, 0.000704825681168586, 0.0008626107592135668, -0.0004994627670384943, 0.1802779585123062, 0.0005355331813916564, -0.3850158154964447, -0.000660755904391408, -0.15524353086948395, 0.0770384892821312, -0.1990944892168045, -0.04059717804193497, 0.00019839264859911054, -0.08954143524169922, -0.1745176762342453, 0.19342899322509766, -0.039949242025613785, -0.05351455509662628, 0.0010188281303271651, 0.0012863714946433902, -4.699235432781279e-05, 0.04647690802812576, -0.1538148671388626, -0.0009432003716938198, 0.06832418590784073, -0.07473438233137131, 0.19692155718803406, -0.00023191161744762212, -0.07189866900444031, -0.08010462671518326, 0.22581109404563904, 0.11592476069927216, 0.17914976179599762, 0.13195598125457764, -0.1110662892460823, 0.12462127208709717, 0.006350248120725155, 0.09321404248476028, 0.032797329127788544, 0.0406208336353302, 0.07625015079975128,
+
+0.26654642820358276, 0.006987582892179489, 0.056940462440252304, -0.21681314706802368, 0.07780187577009201, 0.0550677552819252, -0.07760556042194366, 0.03872932121157646, -0.7930355668067932, -0.1105983555316925, 0.11750592291355133, 0.13262803852558136, -0.06422358006238937, 0.02154429443180561, 0.10654937475919724, 0.05221962183713913, -0.48878803849220276, -0.22840070724487305, 0.0011379553470760584, 0.15314219892024994, 0.07926332950592041, 0.0003804231819231063, 0.0017872434109449387, 0.0007042611250653863, 0.0002458576636854559, -0.001502114930190146, 0.00033512181835249066, 0.1798011213541031, -0.00030350624001584947, -0.09183648973703384, -0.00031797270639799535, -0.17676876485347748, 0.05354951694607735, -0.30156299471855164, 0.019367441534996033, -0.00010185350402025506, -0.03712425008416176, -0.07796591520309448, -0.1688132882118225, -0.5796422958374023, 0.15654867887496948, -0.0013217078521847725, -0.001091445330530405, 0.0011883607367053628, 0.10660554468631744, -0.12484317272901535, 0.0004226503078825772, 0.09296494722366333, -0.38826271891593933, 0.2994518280029297, 0.0007777059799991548, -0.2824214696884155, -0.09771981835365295, 0.30562764406204224, 0.21152275800704956, 0.07008504122495651, 0.08235848695039749, -0.009461170062422752, 0.14994531869888306, 0.025700503960251808, 0.2208600640296936, 0.016543129459023476, -0.04067225754261017, 0.012883936055004597,
+
+0.00617796229198575, -0.013291561044752598, 0.1916685402393341, -0.017105795443058014, -0.07506846636533737, 0.18045775592327118, -0.30787673592567444, 0.04832560196518898, 0.05962129309773445, 0.1261044591665268, -0.2459549754858017, 0.12365790456533432, 0.028636902570724487, -0.006177236791700125, -0.04891420155763626, 0.16809219121932983, -0.10486529022455215, -0.10494883358478546, -0.0004520704969763756, 0.23579229414463043, 0.05076323449611664, -0.001182716921903193, -0.0001052700899890624, 0.0018256279872730374, 0.0008991276263259351, -0.001528103486634791, -0.0005336360190995038, 0.16323579847812653, 0.0020393324084579945, 0.015845002606511116, 0.0016316768014803529, -0.06386037170886993, 0.0540936253964901, -0.14962895214557648, -0.014346976764500141, 0.0012925119372084737, -0.12354017049074173, 0.016353895887732506, -0.2519243061542511, -0.042811259627342224, 0.19090451300144196, -0.00022991615696810186, 0.0018943509785458446, -0.0005430503515526652, -0.11097119003534317, -0.05055755749344826, -0.001144487177953124, -0.002318614162504673, -0.11912520974874496, -0.022436127066612244, 0.00014450220623984933, -0.1372481733560562, -0.02418547123670578, 0.24273015558719635, 0.1387740820646286, 0.1362992823123932, 0.15725626051425934, -0.157984659075737, 0.10887137055397034, 0.07719193398952484, 0.09739567339420319, -0.09165967255830765, -0.2062297910451889, 0.11893536150455475,
+
+-0.09508167952299118, -0.07543941587209702, 0.2706283628940582, 0.08787128329277039, 0.10140055418014526, 0.26852965354919434, -0.5909307599067688, 0.19821986556053162, 0.08937512338161469, 0.05567803606390953, -0.11613370478153229, 0.03911638632416725, 0.06315726786851883, 0.10782184451818466, -0.01980738714337349, 0.1451241374015808, -0.060943953692913055, -0.07014007121324539, 0.00016978045459836721, 0.17468222975730896, 0.06063257157802582, -7.286974141607061e-05, 0.0005939672118984163, 0.0018404772272333503, 0.001129048760049045, 0.00019233254715800285, 0.0019600382074713707, 0.07629802823066711, 0.0003428335185162723, -0.0005339051713235676, -0.00011325302330078557, -0.03201869875192642, 0.04179591313004494, -0.3185126781463623, 0.08271040767431259, 0.0021725951228290796, -0.16681934893131256, -0.031819552183151245, -0.3288743495941162, 0.0464513823390007, 0.17611919343471527, 0.000690086861141026, 7.961438677739352e-05, -0.00019473303109407425, -0.0969485193490982, -0.03324940800666809, -0.0008172128000296652, 0.22586534917354584, -0.2223370373249054, -0.05459794029593468, -9.828664769884199e-05, -0.14924103021621704, -0.03904952108860016, 0.2069503366947174, 0.07704979181289673, 0.1661059856414795, 0.14414143562316895, -0.23807625472545624, 0.10244176536798477, 0.09765428304672241, 0.08840622752904892, -0.024117084220051765, 0.0006691144080832601, 0.1786615550518036,
+
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+0.0005521097918972373, 0.017729170620441437, -0.1722581833600998, 0.0037039422895759344, 0.001567360362969339, -0.10055038332939148, 0.021108632907271385, 0.020772647112607956, 0.14595064520835876, -0.04253007844090462, 0.013751122169196606, 0.0076897949911653996, 0.04191797226667404, 0.01694018393754959, 0.002107905922457576, -0.06683442741632462, 0.020539015531539917, 0.02914385125041008, -7.801321044098586e-05, 0.00048368109855800867, -0.01766815409064293, -0.0005448150914162397, 0.0010524365352466702, -0.0007671643979847431, -0.00012459020945243537, 0.0008768694824539125, -0.0005135779501870275, -0.0037997858598828316, 0.00038613981450907886, 0.014108768664300442, 0.0006932157557457685, -0.0067222160287201405, -0.0209006667137146, 0.026551542803645134, -0.0011496779043227434, -0.0007507435511797667, 0.02834414131939411, 0.009201196022331715, 0.0057718404568731785, 0.02169930189847946, -0.014502635225653648, -3.491714596748352e-05, -0.0003578605828806758, -0.001178428647108376, 0.06057244539260864, 0.020316433161497116, -0.0011969138868153095, -0.04873412102460861, 0.023842258378863335, -0.023542333394289017, 0.0017061911057680845, 0.021966224536299706, 0.0003367953177075833, -0.1909828633069992, 0.06507214158773422, -0.02517489530146122, -0.04564562439918518, 0.030473219230771065, -0.035557761788368225, 0.0190313421189785, 0.025006592273712158, 0.0028738449327647686, 0.013087435625493526, -0.017678551375865936,
+
+0.5722816586494446, 0.44931724667549133, 0.033467985689640045, -0.05215294659137726, -0.1651076078414917, 0.09514902532100677, -0.2535097599029541, -0.31727728247642517, 0.020857004448771477, 0.01630846969783306, -0.09314350038766861, 0.1957118958234787, -0.39591383934020996, 0.26922011375427246, 0.3317633271217346, 0.11175347119569778, -0.2671031951904297, -0.056412164121866226, -0.0015118089504539967, 0.2937302589416504, 0.1793442815542221, -0.001025194302201271, 0.0010095476172864437, 0.0035850228741765022, 0.0006587953539565206, 0.000939257733989507, 0.0003379232657607645, 0.3479364216327667, -0.0004258739354554564, -0.0808158591389656, 0.00038307232898660004, -0.011362356133759022, -0.0033058011904358864, -0.08819703757762909, -0.32478445768356323, -0.0011537037789821625, -0.273912638425827, -0.11553899198770523, 0.17199908196926117, -0.0041303266771137714, 0.41343948245048523, 0.0003570480039343238, 0.0014987858012318611, 0.0013575225602835417, -0.55711829662323, -0.28808870911598206, -0.002448621904477477, 0.17940248548984528, -0.20062221586704254, 0.31715089082717896, 0.0008355412282980978, -0.07066480815410614, -0.13722951710224152, -0.10970398038625717, 0.05873332545161247, 0.24034948647022247, 0.182510644197464, 0.11015398055315018, 0.24339579045772552, -0.04150482639670372, 0.19960984587669373, -0.15185965597629547, -0.27342841029167175, 0.13767993450164795,
+
+0.22348885238170624, -0.008877726271748543, -0.171895369887352, -0.43331223726272583, 0.20232950150966644, 0.043170031160116196, -0.36004438996315, -0.006740920711308718, 0.18264558911323547, -0.11805032193660736, -0.07412461191415787, 0.032417088747024536, 0.051556725054979324, 0.08561589568853378, 0.4091699719429016, -0.0786430686712265, -0.22887086868286133, -0.2439272403717041, 0.00014124371227808297, 0.6468839049339294, -0.036077044904232025, -0.0014531002379953861, -0.0011161002330482006, 0.003305896883830428, 0.0017938324017450213, -3.7506528315134346e-05, -0.0016759017016738653, 0.40134409070014954, -0.0007333348621614277, -0.2809791564941406, -0.001019181334413588, 0.019602011889219284, 0.09314858913421631, -0.5306268334388733, 0.17580009996891022, -1.5525150956818834e-05, -0.2091640830039978, -0.6634456515312195, -0.14848995208740234, -0.06595541536808014, -0.034880805760622025, -1.1966582178501994e-06, 0.00036120228469371796, -0.0012568037491291761, -0.10609765350818634, -0.5816946625709534, -0.0006648825947195292, 0.4456590414047241, -0.512170672416687, 0.24637466669082642, 0.0010917421896010637, -0.23795755207538605, -0.2328575998544693, -0.07656370103359222, 0.33030301332473755, 0.2731899917125702, 0.09424741566181183, -0.1698189079761505, 0.01702292636036873, -0.10659436136484146, 0.11089695990085602, -0.08941251039505005, -0.35293179750442505, 0.06545879691839218
+};
+
+/// Second convolution biases
+static const double conv2_biases[] = {
+0.12326373159885406,
+0.13270756602287292,
+0.07082673907279968,
+0.051456157118082047,
+0.05844561755657196,
+0.1315319687128067,
+0.08097290247678757,
+0.10153213143348694,
+0.055915363132953644,
+0.052281659096479416,
+-0.11212895810604095,
+0.07462140917778015,
+-0.10300768911838531,
+0.108175128698349,
+0.15686865150928497,
+0.18225829303264618,
+0.06780990958213806,
+-0.027867194265127182,
+0.10957542806863785,
+0.03425288572907448,
+0.05988423153758049,
+-0.04818560183048248,
+0.07478125393390656,
+-0.07338137924671173,
+-0.022100606933236122,
+-0.04947621747851372,
+0.00016185229469556361,
+0.16787314414978027,
+-0.08640440553426743,
+0.060469429939985275,
+-0.17337509989738464,
+0.26549988985061646
+};
+
+/// Third convolution kernel
+static const double conv3_kernel[] = {
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+};
+
+/// Third convolution biases
+static const double conv3_biases[] = {
+0.05037664
+};
--
2.14.1