sumit
6/17/2019 - 4:18 AM

running tensor-rt sample model on tx2


cd /home/nvidia/tegra_multimedia_api/samples/backend
./backend 1 ../../data/Video/sample_outdoor_car_1080p_10fps.h264 H264 --trt-deployfile ../../data/Model/GoogleNet_one_class/GoogleNet_modified_oneClass_halfHD.prototxt --trt-modelfile ../../data/Model/GoogleNet_one_class/GoogleNet_modified_oneClass_halfHD.caffemodel --trt-forcefp32 0 --trt-proc-interval 1 -fps 10


backend <channel-num> <in-file1> <in-file2>... <in-format> [options]

Channel-num:
	1-4, Number of file arguments should exactly match the number of channels specified

Supported formats:
	H264
	H265

OPTIONS:
	-h,--help            Prints this text
	-fps <fps>           Display rate in frames per second [Default = 30]

	--input-nalu         Input to the decoder will be nal units[Default]
	--input-chunks       Input to the decoder will be a chunk of bytes

	--trt-deployfile     set deploy file name
	--trt-modelfile      set model file name
	--trt-proc-interval  set process interval, 1 frame will be process every trt-proc-interval
	--trt-forcefp32      0 to use fp16 (if supported), 1 to use fp32
	--trt-dumpresult     1 to dump result, 0[default] otherwise
	--trt-enable-perf    1[default] to enable perf measurement, 0 otherwise