virtualenv/FFmpeg
1
0
Fork 0
mirror of https://github.com/FFmpeg/FFmpeg.git synced 2024-12-12 19:18:44 +02:00
Code Issues Releases Activity
185d0acdc7
FFmpeg/libavfilter/dnn/Makefile

11 lines
542 B
Makefile
Raw Normal View History

libavfilter/dnn: move dnn files from libavfilter to libavfilter/dnn it is expected that there will be more files to support native mode, so put all the dnn codes under libavfilter/dnn The main change of this patch is to move the file location, see below: modified: libavfilter/Makefile new file: libavfilter/dnn/Makefile renamed: libavfilter/dnn_backend_native.c -> libavfilter/dnn/dnn_backend_native.c renamed: libavfilter/dnn_backend_native.h -> libavfilter/dnn/dnn_backend_native.h renamed: libavfilter/dnn_backend_tf.c -> libavfilter/dnn/dnn_backend_tf.c renamed: libavfilter/dnn_backend_tf.h -> libavfilter/dnn/dnn_backend_tf.h renamed: libavfilter/dnn_interface.c -> libavfilter/dnn/dnn_interface.c Signed-off-by: Guo, Yejun <yejun.guo@intel.com> Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
2019-07-16 07:55:45 +02:00
OBJS-$(CONFIG_DNN) += dnn/dnn_interface.o
dnn: change dnn interface to replace DNNData* with AVFrame* Currently, every filter needs to provide code to transfer data from AVFrame* to model input (DNNData*), and also from model output (DNNData*) to AVFrame*. Actually, such transfer can be implemented within DNN module, and so filter can focus on its own business logic. DNN module also exports the function pointer pre_proc and post_proc in struct DNNModel, just in case that a filter has its special logic to transfer data between AVFrame* and DNNData*. The default implementation within DNN module is used if the filter does not set pre/post_proc.
2020-08-28 06:51:44 +02:00
OBJS-$(CONFIG_DNN) += dnn/dnn_io_proc.o
dnn/queue: add queue and safe_queue support Signed-off-by: Xie, Lin <lin.xie@intel.com> Signed-off-by: Wu Zhiwen <zhiwen.wu@intel.com> Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
2020-11-09 08:09:13 +02:00
OBJS-$(CONFIG_DNN) += dnn/queue.o
OBJS-$(CONFIG_DNN) += dnn/safe_queue.o
lavfi/dnn: refine dnn interface to add DNNExecBaseParams Different function type of model requires different parameters, for example, object detection detects lots of objects (cat/dog/...) in the frame, and classifcation needs to know which object (cat or dog) it is going to classify. The current interface needs to add a new function with more parameters to support new requirement, with this change, we can just add a new struct (for example DNNExecClassifyParams) based on DNNExecBaseParams, and so we can continue to use the current interface execute_model just with params changed.
2021-04-01 04:06:06 +02:00
OBJS-$(CONFIG_DNN) += dnn/dnn_backend_common.o
libavfilter/dnn: move dnn files from libavfilter to libavfilter/dnn it is expected that there will be more files to support native mode, so put all the dnn codes under libavfilter/dnn The main change of this patch is to move the file location, see below: modified: libavfilter/Makefile new file: libavfilter/dnn/Makefile renamed: libavfilter/dnn_backend_native.c -> libavfilter/dnn/dnn_backend_native.c renamed: libavfilter/dnn_backend_native.h -> libavfilter/dnn/dnn_backend_native.h renamed: libavfilter/dnn_backend_tf.c -> libavfilter/dnn/dnn_backend_tf.c renamed: libavfilter/dnn_backend_tf.h -> libavfilter/dnn/dnn_backend_tf.h renamed: libavfilter/dnn_interface.c -> libavfilter/dnn/dnn_interface.c Signed-off-by: Guo, Yejun <yejun.guo@intel.com> Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
2019-07-16 07:55:45 +02:00
DNN-OBJS-$(CONFIG_LIBTENSORFLOW) += dnn/dnn_backend_tf.o
dnn: add openvino as one of dnn backend OpenVINO is a Deep Learning Deployment Toolkit at https://github.com/openvinotoolkit/openvino, it supports CPU, GPU and heterogeneous plugins to accelerate deep learning inferencing. Please refer to https://github.com/openvinotoolkit/openvino/blob/master/build-instruction.md to build openvino (c library is built at the same time). Please add option -DENABLE_MKL_DNN=ON for cmake to enable CPU path. The header files and libraries are installed to /usr/local/deployment_tools/inference_engine/ with default options on my system. To build FFmpeg with openvion, take my system as an example, run with: $ export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/deployment_tools/inference_engine/lib/intel64/:/usr/local/deployment_tools/inference_engine/external/tbb/lib/ $ ../ffmpeg/configure --enable-libopenvino --extra-cflags=-I/usr/local/deployment_tools/inference_engine/include/ --extra-ldflags=-L/usr/local/deployment_tools/inference_engine/lib/intel64 $ make Here are the features provided by OpenVINO inference engine: - support more DNN model formats It supports TensorFlow, Caffe, ONNX, MXNet and Kaldi by converting them into OpenVINO format with a python script. And torth model can be first converted into ONNX and then to OpenVINO format. see the script at https://github.com/openvinotoolkit/openvino/tree/master/model-optimizer/mo.py which also does some optimization at model level. - optimize at inference stage It optimizes for X86 CPUs with SSE, AVX etc. It also optimizes based on OpenCL for Intel GPUs. (only Intel GPU supported becuase Intel OpenCL extension is used for optimization) Signed-off-by: Guo, Yejun <yejun.guo@intel.com> Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
2020-05-25 09:38:09 +02:00
DNN-OBJS-$(CONFIG_LIBOPENVINO) += dnn/dnn_backend_openvino.o
libavfilter/dnn: move dnn files from libavfilter to libavfilter/dnn it is expected that there will be more files to support native mode, so put all the dnn codes under libavfilter/dnn The main change of this patch is to move the file location, see below: modified: libavfilter/Makefile new file: libavfilter/dnn/Makefile renamed: libavfilter/dnn_backend_native.c -> libavfilter/dnn/dnn_backend_native.c renamed: libavfilter/dnn_backend_native.h -> libavfilter/dnn/dnn_backend_native.h renamed: libavfilter/dnn_backend_tf.c -> libavfilter/dnn/dnn_backend_tf.c renamed: libavfilter/dnn_backend_tf.h -> libavfilter/dnn/dnn_backend_tf.h renamed: libavfilter/dnn_interface.c -> libavfilter/dnn/dnn_interface.c Signed-off-by: Guo, Yejun <yejun.guo@intel.com> Signed-off-by: Pedro Arthur <bygrandao@gmail.com>
2019-07-16 07:55:45 +02:00
OBJS-$(CONFIG_DNN) += $(DNN-OBJS-yes)
Reference in New Issue Copy Permalink