Try to used tensorrt inference for yolov3-ssp.weight ,cuda10.0 ,tensorrt5.1.5,
fix lib/yolo.cpp :385
if ((m_configBlocks.at(i).at(“size”) == “2” && m_configBlocks.at(i).at(“stride”) == “1”)||(m_configBlocks.at(i).at(“size”) == “9” && m_configBlocks.at(i).at(“stride”) == “1”)||(m_configBlocks.at(i).at(“size”) == “5” && m_configBlocks.at(i).at(“stride”) == “1”)||(m_configBlocks.at(i).at(“size”) == “13” && m_configBlocks.at(i).at(“stride”) == “1”))
cd deepstream_reference_apps/yolo/
$trt-yolo-app --flagfile=config/yolov3-ssp.txt
cfg : wget https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov3-spp.cfg
weights: wget https://pjreddie.com/media/files/yolov3-spp.weights
Loading pre-trained weights…
Loading complete!
Total Number of weights read : 63052381
layer inp_size out_size weightPtr
(1) conv-bn-leaky 3 x 608 x 608 32 x 608 x 608 992
(2) conv-bn-leaky 32 x 608 x 608 64 x 304 x 304 19680
(3) conv-bn-leaky 64 x 304 x 304 32 x 304 x 304 21856
(4) conv-bn-leaky 32 x 304 x 304 64 x 304 x 304 40544
(5) skip 64 x 304 x 304 64 x 304 x 304 -
(6) conv-bn-leaky 64 x 304 x 304 128 x 152 x 152 114784
(7) conv-bn-leaky 128 x 152 x 152 64 x 152 x 152 123232
(8) conv-bn-leaky 64 x 152 x 152 128 x 152 x 152 197472
(9) skip 128 x 152 x 152 128 x 152 x 152 -
(10) conv-bn-leaky 128 x 152 x 152 64 x 152 x 152 205920
(11) conv-bn-leaky 64 x 152 x 152 128 x 152 x 152 280160
(12) skip 128 x 152 x 152 128 x 152 x 152 -
(13) conv-bn-leaky 128 x 152 x 152 256 x 76 x 76 576096
(14) conv-bn-leaky 256 x 76 x 76 128 x 76 x 76 609376
(15) conv-bn-leaky 128 x 76 x 76 256 x 76 x 76 905312
(16) skip 256 x 76 x 76 256 x 76 x 76 -
(17) conv-bn-leaky 256 x 76 x 76 128 x 76 x 76 938592
(18) conv-bn-leaky 128 x 76 x 76 256 x 76 x 76 1234528
(19) skip 256 x 76 x 76 256 x 76 x 76 -
(20) conv-bn-leaky 256 x 76 x 76 128 x 76 x 76 1267808
(21) conv-bn-leaky 128 x 76 x 76 256 x 76 x 76 1563744
(22) skip 256 x 76 x 76 256 x 76 x 76 -
(23) conv-bn-leaky 256 x 76 x 76 128 x 76 x 76 1597024
(24) conv-bn-leaky 128 x 76 x 76 256 x 76 x 76 1892960
(25) skip 256 x 76 x 76 256 x 76 x 76 -
(26) conv-bn-leaky 256 x 76 x 76 128 x 76 x 76 1926240
(27) conv-bn-leaky 128 x 76 x 76 256 x 76 x 76 2222176
(28) skip 256 x 76 x 76 256 x 76 x 76 -
(29) conv-bn-leaky 256 x 76 x 76 128 x 76 x 76 2255456
(30) conv-bn-leaky 128 x 76 x 76 256 x 76 x 76 2551392
(31) skip 256 x 76 x 76 256 x 76 x 76 -
(32) conv-bn-leaky 256 x 76 x 76 128 x 76 x 76 2584672
(33) conv-bn-leaky 128 x 76 x 76 256 x 76 x 76 2880608
(34) skip 256 x 76 x 76 256 x 76 x 76 -
(35) conv-bn-leaky 256 x 76 x 76 128 x 76 x 76 2913888
(36) conv-bn-leaky 128 x 76 x 76 256 x 76 x 76 3209824
(37) skip 256 x 76 x 76 256 x 76 x 76 -
(38) conv-bn-leaky 256 x 76 x 76 512 x 38 x 38 4391520
(39) conv-bn-leaky 512 x 38 x 38 256 x 38 x 38 4523616
(40) conv-bn-leaky 256 x 38 x 38 512 x 38 x 38 5705312
(41) skip 512 x 38 x 38 512 x 38 x 38 -
(42) conv-bn-leaky 512 x 38 x 38 256 x 38 x 38 5837408
(43) conv-bn-leaky 256 x 38 x 38 512 x 38 x 38 7019104
(44) skip 512 x 38 x 38 512 x 38 x 38 -
(45) conv-bn-leaky 512 x 38 x 38 256 x 38 x 38 7151200
(46) conv-bn-leaky 256 x 38 x 38 512 x 38 x 38 8332896
(47) skip 512 x 38 x 38 512 x 38 x 38 -
(48) conv-bn-leaky 512 x 38 x 38 256 x 38 x 38 8464992
(49) conv-bn-leaky 256 x 38 x 38 512 x 38 x 38 9646688
(50) skip 512 x 38 x 38 512 x 38 x 38 -
(51) conv-bn-leaky 512 x 38 x 38 256 x 38 x 38 9778784
(52) conv-bn-leaky 256 x 38 x 38 512 x 38 x 38 10960480
(53) skip 512 x 38 x 38 512 x 38 x 38 -
(54) conv-bn-leaky 512 x 38 x 38 256 x 38 x 38 11092576
(55) conv-bn-leaky 256 x 38 x 38 512 x 38 x 38 12274272
(56) skip 512 x 38 x 38 512 x 38 x 38 -
(57) conv-bn-leaky 512 x 38 x 38 256 x 38 x 38 12406368
(58) conv-bn-leaky 256 x 38 x 38 512 x 38 x 38 13588064
(59) skip 512 x 38 x 38 512 x 38 x 38 -
(60) conv-bn-leaky 512 x 38 x 38 256 x 38 x 38 13720160
(61) conv-bn-leaky 256 x 38 x 38 512 x 38 x 38 14901856
(62) skip 512 x 38 x 38 512 x 38 x 38 -
(63) conv-bn-leaky 512 x 38 x 38 1024 x 19 x 19 19624544
(64) conv-bn-leaky 1024 x 19 x 19 512 x 19 x 19 20150880
(65) conv-bn-leaky 512 x 19 x 19 1024 x 19 x 19 24873568
(66) skip 1024 x 19 x 19 1024 x 19 x 19 -
(67) conv-bn-leaky 1024 x 19 x 19 512 x 19 x 19 25399904
(68) conv-bn-leaky 512 x 19 x 19 1024 x 19 x 19 30122592
(69) skip 1024 x 19 x 19 1024 x 19 x 19 -
(70) conv-bn-leaky 1024 x 19 x 19 512 x 19 x 19 30648928
(71) conv-bn-leaky 512 x 19 x 19 1024 x 19 x 19 35371616
(72) skip 1024 x 19 x 19 1024 x 19 x 19 -
(73) conv-bn-leaky 1024 x 19 x 19 512 x 19 x 19 35897952
(74) conv-bn-leaky 512 x 19 x 19 1024 x 19 x 19 40620640
(75) skip 1024 x 19 x 19 1024 x 19 x 19 -
(76) conv-bn-leaky 1024 x 19 x 19 512 x 19 x 19 41146976
(77) conv-bn-leaky 512 x 19 x 19 1024 x 19 x 19 45869664
(78) conv-bn-leaky 1024 x 19 x 19 512 x 19 x 19 46396000
maxpool: 512 x 19 x 19
(79) maxpool 512 x 19 x 19 512 x 19 x 19 46396000
(80) route - 512 x 19 x 19 46396000
maxpool: 512 x 19 x 19
(81) maxpool 512 x 19 x 19 512 x 19 x 19 46396000
(82) route - 512 x 19 x 19 46396000
maxpool: 512 x 19 x 19
(83) maxpool 512 x 19 x 19 512 x 19 x 19 46396000
(84) route - 1024 x 19 x 19 46396000
(85) conv-bn-leaky 1024 x 19 x 19 512 x 19 x 19 46922336
(86) conv-bn-leaky 512 x 19 x 19 1024 x 19 x 19 51645024
(87) conv-bn-leaky 1024 x 19 x 19 512 x 19 x 19 52171360
(88) conv-bn-leaky 512 x 19 x 19 1024 x 19 x 19 56894048
(89) conv-linear 1024 x 19 x 19 255 x 19 x 19 57155423
(90) yolo 255 x 19 x 19 255 x 19 x 19 57155423
(91) route - 512 x 19 x 19 57155423
(92) conv-bn-leaky 512 x 19 x 19 256 x 19 x 19 57287519
(93) upsample 256 x 19 x 19 256 x 38 x 38 -
(94) route - 768 x 38 x 38 57287519
(95) conv-bn-leaky 768 x 38 x 38 256 x 38 x 38 57485151
(96) conv-bn-leaky 256 x 38 x 38 512 x 38 x 38 58666847
(97) conv-bn-leaky 512 x 38 x 38 256 x 38 x 38 58798943
(98) conv-bn-leaky 256 x 38 x 38 512 x 38 x 38 59980639
(99) conv-bn-leaky 512 x 38 x 38 256 x 38 x 38 60112735
(100) conv-bn-leaky 256 x 38 x 38 512 x 38 x 38 61294431
(101) conv-linear 512 x 38 x 38 255 x 38 x 38 61425246
(102) yolo 255 x 38 x 38 255 x 38 x 38 61425246
(103) route - 256 x 38 x 38 61425246
(104) conv-bn-leaky 256 x 38 x 38 128 x 38 x 38 61458526
(105) upsample 128 x 38 x 38 128 x 76 x 76 -
(106) route - 384 x 76 x 76 61458526
(107) conv-bn-leaky 384 x 76 x 76 128 x 76 x 76 61508190
(108) conv-bn-leaky 128 x 76 x 76 256 x 76 x 76 61804126
(109) conv-bn-leaky 256 x 76 x 76 128 x 76 x 76 61837406
(110) conv-bn-leaky 128 x 76 x 76 256 x 76 x 76 62133342
(111) conv-bn-leaky 256 x 76 x 76 128 x 76 x 76 62166622
(112) conv-bn-leaky 128 x 76 x 76 256 x 76 x 76 62462558
(113) conv-linear 256 x 76 x 76 255 x 76 x 76 62528093
(114) yolo 255 x 76 x 76 255 x 76 x 76 62528093
Number of unused weights left : 524288
trt-yolo-app: /home/ai/TensorRT_yolo3_module/deepstream_reference_apps/yolo/lib/yolo.cpp:409: void Yolo::createYOLOEngine(nvinfer1::DataType, Int8EntropyCalibrator*): Assertion `0’ failed.
Aborted (core dumped)
Number of unused weights left : 524288 ?