Guo, Yejun: > > >> -----Original Message----- >> From: ffmpeg-devel <ffmpeg-devel-boun...@ffmpeg.org> On Behalf Of >> Andreas Rheinhardt >> Sent: 2021年4月26日 9:34 >> To: ffmpeg-devel@ffmpeg.org >> Subject: Re: [FFmpeg-devel] [PATCH 6/6] lavfi/dnn_classify: add filter >> dnn_classify for classification based on detection bounding boxes >> >> Guo, Yejun: >>> >>> >>>> -----Original Message----- >>>> From: Guo, Yejun <yejun....@intel.com> >>>> Sent: 2021年4月18日 18:08 >>>> To: ffmpeg-devel@ffmpeg.org >>>> Cc: Guo, Yejun <yejun....@intel.com> >>>> Subject: [PATCH 6/6] 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/20 >>>> 21.1/emotions-recognition-retail-0003.bin >>>> wget >>>> >> https://github.com/guoyejun/ffmpeg_dnn/raw/main/models/openvino/20 >>>> 21.1/emotions-recognition-retail-0003.xml >>>> wget >>>> >> https://github.com/guoyejun/ffmpeg_dnn/raw/main/models/openvino/20 >>>> 21.1/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-ad >>>> >> as-0001.label,dnn_classify=dnn_backend=openvino:model=emotions-recog >>>> >> nition-retail-0003.xml:input=data:output=prob_emotion:confidence=0.3:la >>>> bels=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....@intel.com> >>>> --- >>>> configure | 1 + >>>> doc/filters.texi | 36 ++++ >>>> libavfilter/Makefile | 1 + >>>> libavfilter/allfilters.c | 1 + >>>> libavfilter/vf_dnn_classify.c | 330 >>>> ++++++++++++++++++++++++++++++++++ >>>> 5 files changed, 369 insertions(+) >>>> create mode 100644 libavfilter/vf_dnn_classify.c >>>> >>>> + >>>> +AVFilter ff_vf_dnn_classify = { >>>> + .name = "dnn_classify", >>>> + .description = NULL_IF_CONFIG_SMALL("Apply DNN classify >> filter >>>> to the input."), >>>> + .priv_size = sizeof(DnnClassifyContext), >>>> + .init = dnn_classify_init, >>>> + .uninit = dnn_classify_uninit, >>>> + .query_formats = dnn_classify_query_formats, >>>> + .inputs = dnn_classify_inputs, >>>> + .outputs = dnn_classify_outputs, >>>> + .priv_class = &dnn_classify_class, >>>> + .activate = dnn_classify_activate, >>>> +}; >>> >>> I've locally added 'const' for AVFilter ff_vf_dnn_classify, any other >> comment? thanks. >>> >> If you did this, then this filter may only be added after the bump. > > thanks, I'll remove/add 'const' by checking the bump when it can be pushed. > > btw, any rough estimate when the bump will happen? thanks. > Really soon if no issues are detected any more. Probably done in two days.
- Andreas _______________________________________________ ffmpeg-devel mailing list ffmpeg-devel@ffmpeg.org https://ffmpeg.org/mailman/listinfo/ffmpeg-devel To unsubscribe, visit link above, or email ffmpeg-devel-requ...@ffmpeg.org with subject "unsubscribe".
