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• lavfi/dnn_classify : add filter dnn_classify for classification based on detection...

  17 mars 2021, par Guo, Yejun

  lavfi/dnn_classify : add filter dnn_classify for classification based on detection bounding boxes
  classification is done on every detection bounding box in frame's side data,
  
  which are the results of object detection (filter dnn_detect).
  Please refer to commit log of dnn_detect for the material for detection,
  
  and see below for classification.
   download material for classifcation :
  
  wget https://github.com/guoyejun/ffmpeg_dnn/raw/main/models/openvino/2021.1/emotions-recognition-retail-0003.bin
  
  wget https://github.com/guoyejun/ffmpeg_dnn/raw/main/models/openvino/2021.1/emotions-recognition-retail-0003.xml
  
  wget https://github.com/guoyejun/ffmpeg_dnn/raw/main/models/openvino/2021.1/emotions-recognition-retail-0003.label
   run command as :
  
  ./ffmpeg -i cici.jpg -vf dnn_detect=dnn_backend=openvino:model=face-detection-adas-0001.xml:input=data:output=detection_out:confidence=0.6:labels=face-detection-adas-0001.label,dnn_classify=dnn_backend=openvino:model=emotions-recognition-retail-0003.xml:input=data:output=prob_emotion:confidence=0.3:labels=emotions-recognition-retail-0003.label:target=face,showinfo -f null -
  We'll see the detect&classify result as below :
  
  [Parsed_showinfo_2 @ 0x55b7d25e77c0]   side data - detection bounding boxes :
  
  [Parsed_showinfo_2 @ 0x55b7d25e77c0] source : face-detection-adas-0001.xml, emotions-recognition-retail-0003.xml
  
  [Parsed_showinfo_2 @ 0x55b7d25e77c0] index : 0,  region : (1005, 813) -> (1086, 905), label : face, confidence : 10000/10000.
  
  [Parsed_showinfo_2 @ 0x55b7d25e77c0]            classify :  label : happy, confidence : 6757/10000.
  
  [Parsed_showinfo_2 @ 0x55b7d25e77c0] index : 1,  region : (888, 839) -> (967, 926), label : face, confidence : 6917/10000.
  
  [Parsed_showinfo_2 @ 0x55b7d25e77c0]            classify :  label : anger, confidence : 4320/10000.
  Signed-off-by : Guo, Yejun <yejun.guo@intel.com>
  

  • [DH] configure
  • [DH] doc/filters.texi
  • [DH] libavfilter/Makefile
  • [DH] libavfilter/allfilters.c
  • [DH] libavfilter/vf_dnn_classify.c

• libavcodec/jpeg2000dec.c : ROI marker support

  23 avril 2020, par Gautam Ramakrishnan

  libavcodec/jpeg2000dec.c : ROI marker support
  This patch adds support for decoding images
  
  with a Region of Interest. Allows decoding
  
  samples such as p0_03.j2k. This patch should
  
  fix ticket #4681.
  Signed-off-by : Michael Niedermayer <michael@niedermayer.cc>
  

  • [DH] libavcodec/jpeg2000.h
  • [DH] libavcodec/jpeg2000dec.c

• lavfi : add filter dnn_detect for object detection

  7 février 2021, par Guo, Yejun

  lavfi : add filter dnn_detect for object detection
  Below are the example steps to do object detection :
  1. download and install l_openvino_toolkit_p_2021.1.110.tgz from
  
  https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit/download.html
  
    or, we can get source code (tag 2021.1), build and install.
  
  2. export LD_LIBRARY_PATH with openvino settings, for example :
  
  .../deployment_tools/inference_engine/lib/intel64/ :.../deployment_tools/inference_engine/external/tbb/lib/
  
  3. rebuild ffmpeg from source code with configure option :
  
  — enable-libopenvino
  
  — extra-cflags='-I.../deployment_tools/inference_engine/include/'
  
  — extra-ldflags='-L.../deployment_tools/inference_engine/lib/intel64'
  
  4. download model files and test image
  
  wget https://github.com/guoyejun/ffmpeg_dnn/raw/main/models/openvino/2021.1/face-detection-adas-0001.bin
  
  wget https://github.com/guoyejun/ffmpeg_dnn/raw/main/models/openvino/2021.1/face-detection-adas-0001.xml
  
  wget
  
  https://github.com/guoyejun/ffmpeg_dnn/raw/main/models/openvino/2021.1/face-detection-adas-0001.label
  
  wget https://github.com/guoyejun/ffmpeg_dnn/raw/main/images/cici.jpg
  
  5. run ffmpeg with :
  
  ./ffmpeg -i cici.jpg -vf dnn_detect=dnn_backend=openvino:model=face-detection-adas-0001.xml:input=data:output=detection_out:confidence=0.6:labels=face-detection-adas-0001.label,showinfo -f null -
  We'll see the detect result as below :
  
  [Parsed_showinfo_1 @ 0x560c21ecbe40]   side data - detection bounding boxes :
  
  [Parsed_showinfo_1 @ 0x560c21ecbe40] source : face-detection-adas-0001.xml
  
  [Parsed_showinfo_1 @ 0x560c21ecbe40] index : 0,  region : (1005, 813) -> (1086, 905), label : face, confidence : 10000/10000.
  
  [Parsed_showinfo_1 @ 0x560c21ecbe40] index : 1,  region : (888, 839) -> (967, 926), label : face, confidence : 6917/10000.
  There are two faces detected with confidence 100% and 69.17%.
  Signed-off-by : Guo, Yejun <yejun.guo@intel.com>
  

  • [DH] configure
  • [DH] doc/filters.texi
  • [DH] libavfilter/Makefile
  • [DH] libavfilter/allfilters.c
  • [DH] libavfilter/vf_dnn_detect.c