Media & AI 가속기를 탑재한 카카오클라우드의 Video Instance 활용기

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$16 X48 INPUT_FILE=videos/sample_60sec_3840x2160_60fps_h264.mp4 ENC_OPTION="-max_interleave_delta 0 -profile:v main -preset fast -f
mp4 –y" ffmpeg -re -i ${INPUT_FILE} -filter_complex "[0]split=3[a1][a2][a3]; [a1]scale=1920:1080[a11]; [a2]scale=1280:720[a21]; [a3]scale=640:360,fps=30[e]; [a11]split[a][b1]; [b1]fps=30[b]; [a21]split[c][d1]; [d1]fps=30[d]" -map '[a]' -c:v libx264 -b:v 12M -maxrate 12M -threads $N $ENC_OPTION 1080p60.mp4 -map '[b]' -c:v libx264 -b:v 10M -maxrate 10M -threads $N $ENC_OPTION 1080p30.mp4 -map '[c]' -c:v libx264 -b:v 7M -maxrate 7M -threads $N $ENC_OPTION 720p60.mp4 -map '[d]' -c:v libx264 -b:v 5M -maxrate 5M -threads $N $ENC_OPTION 720p30.mp4 -map '[e]' -c:v libx264 -b:v 2500K -maxrate 2500K -threads $N $ENC_OPTION 360p30.mp4 ױੌ .VMUJ4DBMJOH੘স 1FSGPSNBODF࠺Ү

ENC_OPTION="-max_interleave_delta 0 -profile:v main -f mp4 –y" ffmpeg -lxlnx_hwdev 0
-c:v mpsoc_vcu_h264 -i ${INPUT_FILE} -filter_complex "multiscale_xma=outputs=3: out_1_width=1920: out_1_height=1080: out_1_rate=full: out_2_width=1280: out_1_height=720: out_1_rate=full: out_3_width=640: out_2_height=360: out_2_rate=half: [a1][a2][e]; [a1]split[a][b1]; [b1]fps=30[b]; [a2]split[c][d1]; [d1]fps=30[d]" -map '[a]' -c:v mpsoc_vcu_h264 -b:v 12M -max-bitrate 12M $ENC_OPTION 1080p60.mp4 -map '[b]' -c:v mpsoc_vcu_h264 -b:v 10M -max-bitrate 10M $ENC_OPTION 1080p30.mp4 -map '[c]' -c:v mpsoc_vcu_h264 -b:v 7M -max-bitrate 7M $ENC_OPTION 720p60.mp4 -map '[d]' -c:v mpsoc_vcu_h264 -b:v 5M -max-bitrate 5M $ENC_OPTION 720p30.mp4 -map '[e]' -c:v mpsoc_vcu_h264 -b:v 2500K -max-bitrate 2500K $ENC_OPTION 360p30.mp4 ױੌ .VMUJ4DBMJOH੘স 1FSGPSNBODF࠺Ү 75*OTUBODF

75*OTUBODF ENC_OPTION="-max_interleave_delta 0 -profile:v main -preset fast -f mp4 –y"
ffmpeg -hwaccel ama -c:v h264_ama -i ${INPUT_FILE} -filter_complex "scaler_ama=outputs=3: out_res=(1920x1080|full)(1280x720|full)(640x360|half)(320x180|half) [a1][a2][e]; [a1]split[a][b1]; [b1]fps=30[b]; [a2]split[c][d1]; [d1]fps=30[d]" -map '[a]' -c:v h264_ama -b:v 12M –maxrate 12M $ENC_OPTION 1080p60.mp4 -map '[b]' -c:v h264_ama -b:v 10M –maxrate 10M $ENC_OPTION 1080p30.mp4 -map '[b]' -c:v h264_ama -b:v 7M –maxrate 7M $ENC_OPTION 720p60.mp4 -map '[c]' -c:v h264_ama -b:v 5M –maxrate 5M $ENC_OPTION 720p30.mp4 -map '[d]' -c:v h264_ama -b:v 2500K –maxrate 2500K $ENC_OPTION 360p30.mp4 ױੌ .VMUJ4DBMJOH੘স 1FSGPSNBODF࠺Ү

ENC_OPTION="-max_interleave_delta 0 -profile:v main -preset fast -f mp4 –y" ffmpeg
-hwaccel cuda -hwaccel_output_format cuda -i ${INPUT_FILE} -filter_complex "[0]split=3[a1][a2][a3]; [a1]scale_cuda=1920:1080[a11]; [a2]scale_cuda=1280:720[a21]; [a3]scale_cuda=640:360[a31]; [a11]split[a][b1]; [b1]fps=30[b]; [a21]split[c][d1]; [d1]fps=30[d]; [a31]fps=30[e]" -map '[a]' -c:v h264_nvenc -b:v 12M -maxrate 12M $ENC_OPTION 1080p60.mp4 -map '[b]' -c:v h264_nvenc -b:v 10M -maxrate 10M $ENC_OPTION 1080p30.mp4 -map '[c]' -c:v h264_nvenc -b:v 7M -maxrate 7M $ENC_OPTION 720p60.mp4 -map '[d]' -c:v h264_nvenc -b:v 5M -maxrate 5M $ENC_OPTION 720p30.mp4 -map '[e]' -c:v h264_nvenc -b:v 2500K -maxrate 2500K $ENC_OPTION 360p30.mp4 ױੌ .VMUJ4DBMJOH੘স 1FSGPSNBODF࠺Ү (16 5

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INPUT_FILE=sample_60sec_1920x1080_60fps_h264.mp4 # VT1 Instance ffmpeg -xlnx_hwdev ${DEVICE_ID} -c:v mpsoc_vcu_h264 \
-i ${INPUT_FILE} -c:v mpsoc_vcu_hevc -b:v 10M -f mp4 -y /tmp/output.mp4 # VT2 Instance ffmpeg -hwaccel ama -hwaccel_device /dev/ama_transcoder${DEVICE_ID} -c:v h264_ama -i ${INPUT_FILE} -c:v hevc_ama –slice ${CORE_ID} -b:v 10M -f mp4 -y /tmp/output.mp4 .VMUJ4USFBN5SBOTDPEJOH੘স 1FSGPSNBODF࠺Ү

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#include <opencv2/core.hpp> ... #include <vitis/ai/classification.hpp> #include <vitis/ai/demo.hpp> #include "./process_result.hpp" int
main(int argc, char *argv[]) { std::string model = argv[1]; return vitis::ai::main_for_video_demo( argc, argv, [model] { return vitis::ai::Classification::create(model); }, process_result, 2); } 7*OG*OTUBODF "**OGFSFODF4USFBNJOH

XCLBIN_PATH=/opt/xilinx/xclbin/v70.xclbin DECODER="kernel_vdu_decoder:{kernel_vdu_decoder_0}" gst-launch-1.0 rtspsrc location=${SRC_URL} ! rtph264depay ! h264parse !
"video/x-h264, stream-format=byte-stream, alignment=au" ! vvas_xvideodec dev-idx=0 xclbin-location=${XCLBIN_PATH} kernel-name=${DECODER} instance-id=0 avoid-dynamic-alloc=0 ! identity sync=0 ! vvas_xinfer preprocess-config=${PPE_CFG_PATH} infer-config=${INFER_CFG_PATH} ! vvas_xmetaconvert config-location=${META_CFG_PATH} ! vvas_xoverlay ! videoconvert ! x264enc ! filesink location=output.h264 7*OG*OTUBODF "**OGFSFODF4USFBNJOH

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XCLBIN_PATH=/opt/xilinx/xclbin/v70.xclbin DECODER="kernel_vdu_decoder:{kernel_vdu_decoder_0}" SCALER="image_processing:{image_processing_1}" gst-launch-1.0 -v filesrc location=input.mp4 ! qtdemux !
h264parse ! vvas_xvideodec dev-idx=0 xclbin-location=${XCLBIN_PATH} kernel-name=$DECODER instance-id=0 avoid-dynamic-alloc=0 ! identity sync=0 ! videoconvert ! vvas_xinfer preprocess-config=${PPE_CFG} infer-config="yolo_car.json" ! vvas_xinfer preprocess-config=${PPE_CFG} infer-config="resnet_car_color.json" ! vvas_xinfer preprocess-config=${PPE_CFG} infer-config="resnet_car_make.json" ! vvas_xinfer preprocess-config=${PPE_CFG_PATH} infer-config="resnet_car_type.json" ! vvas_xabrscaler dev-idx=0 xclbin-location=${XCLBIN_PATH} kernel-name=${SCALER} ! video/x-raw, width=480, height=270, format=NV12 ! vvas_xmetaconvert config-location=${META_CFG_PATH} ! vvas_xoverlay ! videoconvert ! x264enc ! mp4mux ! filesink location=out.mp4 7*OG*OTUBODF%FNP $BTDBEF.VMUJQMF"**OGFSFODF

{ "inference-level" : 1, "attach-ppe-outbuf" : false, "kernel" : {
"config" : { "batch-size" : 14, "model-name" : "yolov3_voc_tf", "model-class" : "YOLOV3", "model-format" : "BGR", "model-path" : "/workspace/models/", "vitis-ai-preprocess" : false, "debug-level" : 2, "max-objects": 3, "filter-labels" : ["car"] } } } { "inference-level" : 2, "inference-max-queue" : 14, "attach-ppe-outbuf" : true, "kernel" : { "config": { "batch-size" : 14, "model-name" : "chen_color_resnet18_pt", "model-class" : "CLASSIFICATION", "model-format" : "BGR", "model-path" : "/workspace/models/", "performance-test" : false, "vitis-ai-preprocess" : false, "debug-level" : 2 } } } ZPMP@DBSKTPO SFTOFU@DBS@DPMPSKTPO 7*OG*OTUBODF%FNP $BTDBEF.VMUJQMF"**OGFSFODF

{ "inference-level" : 1, "attach-ppe-outbuf" : false, "kernel" : {
"config" : { "batch-size" : 14, "model-name" : "yolov3_voc_tf", "model-class" : "YOLOV3", "model-format" : "BGR", "model-path" : "/workspace/models/", "vitis-ai-preprocess" : false, "debug-level" : 2, "max-objects": 3, "filter-labels" : ["car"] } } } ZPMP@DBSKTPO 7*OG*OTUBODF%FNP { "inference-level" : 2, "inference-max-queue" : 14, "attach-ppe-outbuf" : true, "kernel" : { "config": { "batch-size" : 14, "model-name" : "chen_color_resnet18_pt", "model-class" : "CLASSIFICATION", "model-format" : "BGR", "model-path" : "/workspace/models/", "performance-test" : false, "vitis-ai-preprocess" : false, "debug-level" : 2 } } } SFTOFU@DBS@DPMPSKTPO $BTDBEF.VMUJQMF"**OGFSFODF

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Media & AI 가속기를 탑재한 카카오클라우드의 Video Instance 활용기

Media & AI 가속기를 탑재한 카카오클라우드의 Video Instance 활용기

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