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  1. /*
  2. * Copyright (c) 2018 Sergey Lavrushkin
  3. *
  4. * This file is part of FFmpeg.
  5. *
  6. * FFmpeg is free software; you can redistribute it and/or
  7. * modify it under the terms of the GNU Lesser General Public
  8. * License as published by the Free Software Foundation; either
  9. * version 2.1 of the License, or (at your option) any later version.
  10. *
  11. * FFmpeg is distributed in the hope that it will be useful,
  12. * but WITHOUT ANY WARRANTY; without even the implied warranty of
  13. * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
  14. * Lesser General Public License for more details.
  15. *
  16. * You should have received a copy of the GNU Lesser General Public
  17. * License along with FFmpeg; if not, write to the Free Software
  18. * Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
  19. */
  20. /**
  21. * @file
  22. * Filter implementing image super-resolution using deep convolutional networks.
  23. * https://arxiv.org/abs/1501.00092
  24. * https://arxiv.org/abs/1609.05158
  25. */
  26. #include "avfilter.h"
  27. #include "formats.h"
  28. #include "internal.h"
  29. #include "libavutil/opt.h"
  30. #include "libavutil/pixdesc.h"
  31. #include "libavformat/avio.h"
  32. #include "libswscale/swscale.h"
  33. #include "dnn_interface.h"
  34. typedef struct SRContext {
  35. const AVClass *class;
  36. char *model_filename;
  37. DNNBackendType backend_type;
  38. DNNModule *dnn_module;
  39. DNNModel *model;
  40. int scale_factor;
  41. struct SwsContext *sws_uv_scale;
  42. int sws_uv_height;
  43. struct SwsContext *sws_pre_scale;
  44. } SRContext;
  45. #define OFFSET(x) offsetof(SRContext, x)
  46. #define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM
  47. static const AVOption sr_options[] = {
  48. { "dnn_backend", "DNN backend used for model execution", OFFSET(backend_type), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, 1, FLAGS, "backend" },
  49. { "native", "native backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 0 }, 0, 0, FLAGS, "backend" },
  50. #if (CONFIG_LIBTENSORFLOW == 1)
  51. { "tensorflow", "tensorflow backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 1 }, 0, 0, FLAGS, "backend" },
  52. #endif
  53. { "scale_factor", "scale factor for SRCNN model", OFFSET(scale_factor), AV_OPT_TYPE_INT, { .i64 = 2 }, 2, 4, FLAGS },
  54. { "model", "path to model file specifying network architecture and its parameters", OFFSET(model_filename), AV_OPT_TYPE_STRING, {.str=NULL}, 0, 0, FLAGS },
  55. { NULL }
  56. };
  57. AVFILTER_DEFINE_CLASS(sr);
  58. static av_cold int init(AVFilterContext *context)
  59. {
  60. SRContext *sr_context = context->priv;
  61. sr_context->dnn_module = ff_get_dnn_module(sr_context->backend_type);
  62. if (!sr_context->dnn_module){
  63. av_log(context, AV_LOG_ERROR, "could not create DNN module for requested backend\n");
  64. return AVERROR(ENOMEM);
  65. }
  66. if (!sr_context->model_filename){
  67. av_log(context, AV_LOG_ERROR, "model file for network was not specified\n");
  68. return AVERROR(EIO);
  69. }
  70. if (!sr_context->dnn_module->load_model) {
  71. av_log(context, AV_LOG_ERROR, "load_model for network was not specified\n");
  72. return AVERROR(EIO);
  73. }
  74. sr_context->model = (sr_context->dnn_module->load_model)(sr_context->model_filename, NULL, NULL);
  75. if (!sr_context->model){
  76. av_log(context, AV_LOG_ERROR, "could not load DNN model\n");
  77. return AVERROR(EIO);
  78. }
  79. return 0;
  80. }
  81. static int query_formats(AVFilterContext *context)
  82. {
  83. const enum AVPixelFormat pixel_formats[] = {AV_PIX_FMT_YUV420P, AV_PIX_FMT_YUV422P, AV_PIX_FMT_YUV444P,
  84. AV_PIX_FMT_YUV410P, AV_PIX_FMT_YUV411P, AV_PIX_FMT_GRAY8,
  85. AV_PIX_FMT_NONE};
  86. AVFilterFormats *formats_list;
  87. formats_list = ff_make_format_list(pixel_formats);
  88. if (!formats_list){
  89. av_log(context, AV_LOG_ERROR, "could not create formats list\n");
  90. return AVERROR(ENOMEM);
  91. }
  92. return ff_set_common_formats(context, formats_list);
  93. }
  94. static int config_output(AVFilterLink *outlink)
  95. {
  96. AVFilterContext *context = outlink->src;
  97. SRContext *ctx = context->priv;
  98. DNNReturnType result;
  99. AVFilterLink *inlink = context->inputs[0];
  100. int out_width, out_height;
  101. // have a try run in case that the dnn model resize the frame
  102. result = ctx->model->get_output(ctx->model->model, "x", inlink->w, inlink->h,
  103. "y", &out_width, &out_height);
  104. if (result != DNN_SUCCESS) {
  105. av_log(ctx, AV_LOG_ERROR, "could not get output from the model\n");
  106. return AVERROR(EIO);
  107. }
  108. if (inlink->w != out_width || inlink->h != out_height) {
  109. //espcn
  110. outlink->w = out_width;
  111. outlink->h = out_height;
  112. if (inlink->format != AV_PIX_FMT_GRAY8){
  113. const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(inlink->format);
  114. int sws_src_h = AV_CEIL_RSHIFT(inlink->h, desc->log2_chroma_h);
  115. int sws_src_w = AV_CEIL_RSHIFT(inlink->w, desc->log2_chroma_w);
  116. int sws_dst_h = AV_CEIL_RSHIFT(outlink->h, desc->log2_chroma_h);
  117. int sws_dst_w = AV_CEIL_RSHIFT(outlink->w, desc->log2_chroma_w);
  118. ctx->sws_uv_scale = sws_getContext(sws_src_w, sws_src_h, AV_PIX_FMT_GRAY8,
  119. sws_dst_w, sws_dst_h, AV_PIX_FMT_GRAY8,
  120. SWS_BICUBIC, NULL, NULL, NULL);
  121. ctx->sws_uv_height = sws_src_h;
  122. }
  123. } else {
  124. //srcnn
  125. outlink->w = out_width * ctx->scale_factor;
  126. outlink->h = out_height * ctx->scale_factor;
  127. ctx->sws_pre_scale = sws_getContext(inlink->w, inlink->h, inlink->format,
  128. outlink->w, outlink->h, outlink->format,
  129. SWS_BICUBIC, NULL, NULL, NULL);
  130. }
  131. return 0;
  132. }
  133. static int filter_frame(AVFilterLink *inlink, AVFrame *in)
  134. {
  135. AVFilterContext *context = inlink->dst;
  136. SRContext *ctx = context->priv;
  137. AVFilterLink *outlink = context->outputs[0];
  138. AVFrame *out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
  139. DNNReturnType dnn_result;
  140. const char *model_output_name = "y";
  141. if (!out){
  142. av_log(context, AV_LOG_ERROR, "could not allocate memory for output frame\n");
  143. av_frame_free(&in);
  144. return AVERROR(ENOMEM);
  145. }
  146. av_frame_copy_props(out, in);
  147. if (ctx->sws_pre_scale) {
  148. sws_scale(ctx->sws_pre_scale,
  149. (const uint8_t **)in->data, in->linesize, 0, in->height,
  150. out->data, out->linesize);
  151. dnn_result = (ctx->dnn_module->execute_model)(ctx->model, "x", out,
  152. (const char **)&model_output_name, 1, out);
  153. } else {
  154. dnn_result = (ctx->dnn_module->execute_model)(ctx->model, "x", in,
  155. (const char **)&model_output_name, 1, out);
  156. }
  157. if (dnn_result != DNN_SUCCESS){
  158. av_log(ctx, AV_LOG_ERROR, "failed to execute loaded model\n");
  159. av_frame_free(&in);
  160. av_frame_free(&out);
  161. return AVERROR(EIO);
  162. }
  163. if (ctx->sws_uv_scale) {
  164. sws_scale(ctx->sws_uv_scale, (const uint8_t **)(in->data + 1), in->linesize + 1,
  165. 0, ctx->sws_uv_height, out->data + 1, out->linesize + 1);
  166. sws_scale(ctx->sws_uv_scale, (const uint8_t **)(in->data + 2), in->linesize + 2,
  167. 0, ctx->sws_uv_height, out->data + 2, out->linesize + 2);
  168. }
  169. av_frame_free(&in);
  170. return ff_filter_frame(outlink, out);
  171. }
  172. static av_cold void uninit(AVFilterContext *context)
  173. {
  174. SRContext *sr_context = context->priv;
  175. if (sr_context->dnn_module){
  176. (sr_context->dnn_module->free_model)(&sr_context->model);
  177. av_freep(&sr_context->dnn_module);
  178. }
  179. sws_freeContext(sr_context->sws_uv_scale);
  180. sws_freeContext(sr_context->sws_pre_scale);
  181. }
  182. static const AVFilterPad sr_inputs[] = {
  183. {
  184. .name = "default",
  185. .type = AVMEDIA_TYPE_VIDEO,
  186. .filter_frame = filter_frame,
  187. },
  188. { NULL }
  189. };
  190. static const AVFilterPad sr_outputs[] = {
  191. {
  192. .name = "default",
  193. .config_props = config_output,
  194. .type = AVMEDIA_TYPE_VIDEO,
  195. },
  196. { NULL }
  197. };
  198. AVFilter ff_vf_sr = {
  199. .name = "sr",
  200. .description = NULL_IF_CONFIG_SMALL("Apply DNN-based image super resolution to the input."),
  201. .priv_size = sizeof(SRContext),
  202. .init = init,
  203. .uninit = uninit,
  204. .query_formats = query_formats,
  205. .inputs = sr_inputs,
  206. .outputs = sr_outputs,
  207. .priv_class = &sr_class,
  208. };