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Sur d’autres sites (6475)

  • 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

  • fftools/ffmpeg_opt : Document VAAPI -device usage for DirectX Adapter

    14 avril 2023, par Sil Vilerino
    fftools/ffmpeg_opt : Document VAAPI -device usage for DirectX Adapter

    Initial review at https://github.com/intel-media-ci/ffmpeg/pull/619/
    

    Signed-off-by : Sil Vilerino <sivileri@microsoft.com>
    
Reviewed-by : Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
    
Reviewed-by : Wu, Tong1 <tong1.wu@intel.com>
    • [DH] doc/ffmpeg.texi
    • [DH] fftools/ffmpeg_opt.c

  • avconv / ffmpeg webcam capture while using minimum CPU processing

    10 septembre 2015, par user3585723

    I have a question about avconv (or ffmpeg) usage.

    My goal is to capture video from a webcam and saving it to a file.
    Also, I don’t want to use too much CPU processing. (I don’t want avconv to scale or re-encode the stream)

    So, I was thinking to use the compressed mjpeg video stream from the webcam and directly saving it to a file.

    My webcam is a Microsoft LifeCam HD 3000 and its capabilities are :

    ffmpeg -f v4l2 -list_formats all -i /dev/video0
    

    
Raw: yuyv422 : YUV 4:2:2 (YUYV) : 640x480 1280x720 960x544 800x448 640x360 424x240 352x288 320x240 800x600 176x144 160x120 1280x800
    

    
Compressed: mjpeg : MJPEG : 640x480 1280x720 960x544 800x448 640x360 800x600 416x240 352x288 176x144 320x240 160x120

    What would be the avconv command to save the Compressed stream directly without having avconv doing scaling or re-encoding.

    For now, I am using this command :

    avconv -f video4linux2 -r 30 -s 320x240 -i /dev/video0 test.avi

    I’m not sure that this command is CPU efficient since I don’t tell anywhere to use the mjpeg Compressed capability of the webcam.

    Is avconv taking care of the configuration of the webcam setting before starting to record the file ? Is it always working of raw stream and doing scaling and enconding on the raw stream ?

    Thanks for your answer

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