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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. DNNData input;
  41. DNNData output;
  42. int scale_factor;
  43. struct SwsContext *sws_contexts[3];
  44. int sws_slice_h, sws_input_linesize, sws_output_linesize;
  45. } SRContext;
  46. #define OFFSET(x) offsetof(SRContext, x)
  47. #define FLAGS AV_OPT_FLAG_FILTERING_PARAM | AV_OPT_FLAG_VIDEO_PARAM
  48. static const AVOption sr_options[] = {
  49. { "dnn_backend", "DNN backend used for model execution", OFFSET(backend_type), AV_OPT_TYPE_INT, { .i64 = 0 }, 0, 1, FLAGS, "backend" },
  50. { "native", "native backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 0 }, 0, 0, FLAGS, "backend" },
  51. #if (CONFIG_LIBTENSORFLOW == 1)
  52. { "tensorflow", "tensorflow backend flag", 0, AV_OPT_TYPE_CONST, { .i64 = 1 }, 0, 0, FLAGS, "backend" },
  53. #endif
  54. { "scale_factor", "scale factor for SRCNN model", OFFSET(scale_factor), AV_OPT_TYPE_INT, { .i64 = 2 }, 2, 4, FLAGS },
  55. { "model", "path to model file specifying network architecture and its parameters", OFFSET(model_filename), AV_OPT_TYPE_STRING, {.str=NULL}, 0, 0, FLAGS },
  56. { NULL }
  57. };
  58. AVFILTER_DEFINE_CLASS(sr);
  59. static av_cold int init(AVFilterContext *context)
  60. {
  61. SRContext *sr_context = context->priv;
  62. sr_context->dnn_module = ff_get_dnn_module(sr_context->backend_type);
  63. if (!sr_context->dnn_module){
  64. av_log(context, AV_LOG_ERROR, "could not create DNN module for requested backend\n");
  65. return AVERROR(ENOMEM);
  66. }
  67. if (!sr_context->model_filename){
  68. av_log(context, AV_LOG_ERROR, "model file for network was not specified\n");
  69. return AVERROR(EIO);
  70. }
  71. if (!sr_context->dnn_module->load_model) {
  72. av_log(context, AV_LOG_ERROR, "load_model for network was not specified\n");
  73. return AVERROR(EIO);
  74. }
  75. sr_context->model = (sr_context->dnn_module->load_model)(sr_context->model_filename);
  76. if (!sr_context->model){
  77. av_log(context, AV_LOG_ERROR, "could not load DNN model\n");
  78. return AVERROR(EIO);
  79. }
  80. sr_context->input.dt = DNN_FLOAT;
  81. sr_context->sws_contexts[0] = NULL;
  82. sr_context->sws_contexts[1] = NULL;
  83. sr_context->sws_contexts[2] = NULL;
  84. return 0;
  85. }
  86. static int query_formats(AVFilterContext *context)
  87. {
  88. const enum AVPixelFormat pixel_formats[] = {AV_PIX_FMT_YUV420P, AV_PIX_FMT_YUV422P, AV_PIX_FMT_YUV444P,
  89. AV_PIX_FMT_YUV410P, AV_PIX_FMT_YUV411P, AV_PIX_FMT_GRAY8,
  90. AV_PIX_FMT_NONE};
  91. AVFilterFormats *formats_list;
  92. formats_list = ff_make_format_list(pixel_formats);
  93. if (!formats_list){
  94. av_log(context, AV_LOG_ERROR, "could not create formats list\n");
  95. return AVERROR(ENOMEM);
  96. }
  97. return ff_set_common_formats(context, formats_list);
  98. }
  99. static int config_props(AVFilterLink *inlink)
  100. {
  101. AVFilterContext *context = inlink->dst;
  102. SRContext *sr_context = context->priv;
  103. AVFilterLink *outlink = context->outputs[0];
  104. DNNReturnType result;
  105. int sws_src_h, sws_src_w, sws_dst_h, sws_dst_w;
  106. const char *model_output_name = "y";
  107. sr_context->input.width = inlink->w * sr_context->scale_factor;
  108. sr_context->input.height = inlink->h * sr_context->scale_factor;
  109. sr_context->input.channels = 1;
  110. result = (sr_context->model->set_input_output)(sr_context->model->model, &sr_context->input, "x", &model_output_name, 1);
  111. if (result != DNN_SUCCESS){
  112. av_log(context, AV_LOG_ERROR, "could not set input and output for the model\n");
  113. return AVERROR(EIO);
  114. }
  115. result = (sr_context->dnn_module->execute_model)(sr_context->model, &sr_context->output, 1);
  116. if (result != DNN_SUCCESS){
  117. av_log(context, AV_LOG_ERROR, "failed to execute loaded model\n");
  118. return AVERROR(EIO);
  119. }
  120. if (sr_context->input.height != sr_context->output.height || sr_context->input.width != sr_context->output.width){
  121. sr_context->input.width = inlink->w;
  122. sr_context->input.height = inlink->h;
  123. result = (sr_context->model->set_input_output)(sr_context->model->model, &sr_context->input, "x", &model_output_name, 1);
  124. if (result != DNN_SUCCESS){
  125. av_log(context, AV_LOG_ERROR, "could not set input and output for the model\n");
  126. return AVERROR(EIO);
  127. }
  128. result = (sr_context->dnn_module->execute_model)(sr_context->model, &sr_context->output, 1);
  129. if (result != DNN_SUCCESS){
  130. av_log(context, AV_LOG_ERROR, "failed to execute loaded model\n");
  131. return AVERROR(EIO);
  132. }
  133. sr_context->scale_factor = 0;
  134. }
  135. outlink->h = sr_context->output.height;
  136. outlink->w = sr_context->output.width;
  137. sr_context->sws_contexts[1] = sws_getContext(sr_context->input.width, sr_context->input.height, AV_PIX_FMT_GRAY8,
  138. sr_context->input.width, sr_context->input.height, AV_PIX_FMT_GRAYF32,
  139. 0, NULL, NULL, NULL);
  140. sr_context->sws_input_linesize = sr_context->input.width << 2;
  141. sr_context->sws_contexts[2] = sws_getContext(sr_context->output.width, sr_context->output.height, AV_PIX_FMT_GRAYF32,
  142. sr_context->output.width, sr_context->output.height, AV_PIX_FMT_GRAY8,
  143. 0, NULL, NULL, NULL);
  144. sr_context->sws_output_linesize = sr_context->output.width << 2;
  145. if (!sr_context->sws_contexts[1] || !sr_context->sws_contexts[2]){
  146. av_log(context, AV_LOG_ERROR, "could not create SwsContext for conversions\n");
  147. return AVERROR(ENOMEM);
  148. }
  149. if (sr_context->scale_factor){
  150. sr_context->sws_contexts[0] = sws_getContext(inlink->w, inlink->h, inlink->format,
  151. outlink->w, outlink->h, outlink->format,
  152. SWS_BICUBIC, NULL, NULL, NULL);
  153. if (!sr_context->sws_contexts[0]){
  154. av_log(context, AV_LOG_ERROR, "could not create SwsContext for scaling\n");
  155. return AVERROR(ENOMEM);
  156. }
  157. sr_context->sws_slice_h = inlink->h;
  158. } else {
  159. if (inlink->format != AV_PIX_FMT_GRAY8){
  160. const AVPixFmtDescriptor *desc = av_pix_fmt_desc_get(inlink->format);
  161. sws_src_h = AV_CEIL_RSHIFT(sr_context->input.height, desc->log2_chroma_h);
  162. sws_src_w = AV_CEIL_RSHIFT(sr_context->input.width, desc->log2_chroma_w);
  163. sws_dst_h = AV_CEIL_RSHIFT(sr_context->output.height, desc->log2_chroma_h);
  164. sws_dst_w = AV_CEIL_RSHIFT(sr_context->output.width, desc->log2_chroma_w);
  165. sr_context->sws_contexts[0] = sws_getContext(sws_src_w, sws_src_h, AV_PIX_FMT_GRAY8,
  166. sws_dst_w, sws_dst_h, AV_PIX_FMT_GRAY8,
  167. SWS_BICUBIC, NULL, NULL, NULL);
  168. if (!sr_context->sws_contexts[0]){
  169. av_log(context, AV_LOG_ERROR, "could not create SwsContext for scaling\n");
  170. return AVERROR(ENOMEM);
  171. }
  172. sr_context->sws_slice_h = sws_src_h;
  173. }
  174. }
  175. return 0;
  176. }
  177. static int filter_frame(AVFilterLink *inlink, AVFrame *in)
  178. {
  179. AVFilterContext *context = inlink->dst;
  180. SRContext *sr_context = context->priv;
  181. AVFilterLink *outlink = context->outputs[0];
  182. AVFrame *out = ff_get_video_buffer(outlink, outlink->w, outlink->h);
  183. DNNReturnType dnn_result;
  184. if (!out){
  185. av_log(context, AV_LOG_ERROR, "could not allocate memory for output frame\n");
  186. av_frame_free(&in);
  187. return AVERROR(ENOMEM);
  188. }
  189. av_frame_copy_props(out, in);
  190. out->height = sr_context->output.height;
  191. out->width = sr_context->output.width;
  192. if (sr_context->scale_factor){
  193. sws_scale(sr_context->sws_contexts[0], (const uint8_t **)in->data, in->linesize,
  194. 0, sr_context->sws_slice_h, out->data, out->linesize);
  195. sws_scale(sr_context->sws_contexts[1], (const uint8_t **)out->data, out->linesize,
  196. 0, out->height, (uint8_t * const*)(&sr_context->input.data),
  197. (const int [4]){sr_context->sws_input_linesize, 0, 0, 0});
  198. } else {
  199. if (sr_context->sws_contexts[0]){
  200. sws_scale(sr_context->sws_contexts[0], (const uint8_t **)(in->data + 1), in->linesize + 1,
  201. 0, sr_context->sws_slice_h, out->data + 1, out->linesize + 1);
  202. sws_scale(sr_context->sws_contexts[0], (const uint8_t **)(in->data + 2), in->linesize + 2,
  203. 0, sr_context->sws_slice_h, out->data + 2, out->linesize + 2);
  204. }
  205. sws_scale(sr_context->sws_contexts[1], (const uint8_t **)in->data, in->linesize,
  206. 0, in->height, (uint8_t * const*)(&sr_context->input.data),
  207. (const int [4]){sr_context->sws_input_linesize, 0, 0, 0});
  208. }
  209. av_frame_free(&in);
  210. dnn_result = (sr_context->dnn_module->execute_model)(sr_context->model, &sr_context->output, 1);
  211. if (dnn_result != DNN_SUCCESS){
  212. av_log(context, AV_LOG_ERROR, "failed to execute loaded model\n");
  213. return AVERROR(EIO);
  214. }
  215. sws_scale(sr_context->sws_contexts[2], (const uint8_t *[4]){(const uint8_t *)sr_context->output.data, 0, 0, 0},
  216. (const int[4]){sr_context->sws_output_linesize, 0, 0, 0},
  217. 0, out->height, (uint8_t * const*)out->data, out->linesize);
  218. return ff_filter_frame(outlink, out);
  219. }
  220. static av_cold void uninit(AVFilterContext *context)
  221. {
  222. int i;
  223. SRContext *sr_context = context->priv;
  224. if (sr_context->dnn_module){
  225. (sr_context->dnn_module->free_model)(&sr_context->model);
  226. av_freep(&sr_context->dnn_module);
  227. }
  228. for (i = 0; i < 3; ++i){
  229. sws_freeContext(sr_context->sws_contexts[i]);
  230. }
  231. }
  232. static const AVFilterPad sr_inputs[] = {
  233. {
  234. .name = "default",
  235. .type = AVMEDIA_TYPE_VIDEO,
  236. .config_props = config_props,
  237. .filter_frame = filter_frame,
  238. },
  239. { NULL }
  240. };
  241. static const AVFilterPad sr_outputs[] = {
  242. {
  243. .name = "default",
  244. .type = AVMEDIA_TYPE_VIDEO,
  245. },
  246. { NULL }
  247. };
  248. AVFilter ff_vf_sr = {
  249. .name = "sr",
  250. .description = NULL_IF_CONFIG_SMALL("Apply DNN-based image super resolution to the input."),
  251. .priv_size = sizeof(SRContext),
  252. .init = init,
  253. .uninit = uninit,
  254. .query_formats = query_formats,
  255. .inputs = sr_inputs,
  256. .outputs = sr_outputs,
  257. .priv_class = &sr_class,
  258. };