Tool/software: Code Composer Studio
Dear Sir,
I am using "tidl_j7_01_00_00_00" version for Importing and running the caffe based mobilenet model.
Confidence Threshold used is: 0.08
Keep top_k used is:20
The result observed from PC Emulation output is having some random bounding boxes which can be observed as below:
I am also sharing the import config and inference config file for your reference below:
modelType = 0 inputNetFile = "E:\tidl_j7_01_00_00_00\ti_dl\test\testvecs\config\tidl_models\caffe\Mob_PD\deploy.prototxt" inputParamsFile = "E:\tidl_j7_01_00_00_00\ti_dl\test\testvecs\config\tidl_models\caffe\Mob_PD\mob_pd.caffemodel" outputNetFile = "E:\tidl_j7_01_00_00_00\ti_dl\test\testvecs\config\tidl_models\caffe\Mob_PD\tidl_net_msi_mobilenet_pd.bin" outputParamsFile = "E:\tidl_j7_01_00_00_00\ti_dl\test\testvecs\config\tidl_models\caffe\Mob_PD\tidl_io_msi_mobilenet_pd_"' quantizationStyle = 2 numParamBits = 12 numParamBits = 16 inElementType = 0 inWidth = 512 inHeight = 512 inNumChannels = 3 perfSimConfig = "E:\tidl_j7_01_00_00_00\ti_dl\test\testvecs\config\import\perfsim_base.cfg" inData = E:\tidl_j7_01_00_00_00\ti_dl\test\testvecs\config\detection_list.txt numFrames = 1 postProcType = 2 inFileFormat = 2
inFileFormat = 2 postProcType = 2 numFrames = 1 padInBuffInTB = 1 netBinFile = "E:\tidl_j7_01_00_00_00\ti_dl\test\testvecs\config\tidl_models\caffe\Mob_PD\tidl_net_msi_mobilenet_pd.bin" ioConfigFile = "E:\tidl_j7_01_00_00_00\ti_dl\test\testvecs\config\tidl_models\caffe\Mob_PD\tidl_io_msi_mobilenet_pd_1.bin" outData = "E:\tidl_j7_01_00_00_00\ti_dl\test\testvecs\config\tidl_models\caffe\Mob_PD\msi_mobilenet.bin" inData = "E:\tidl_j7_01_00_00_00\ti_dl\test\testvecs\config\detection_list.txt" debugTraceLevel = 1 writeTraceLevel = 3
I am also sharing the net log file:
Num of Layer Detected : 65 -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Num|TIDL Layer Name |Out Data Name |Group |#Ins |#Outs |Inbuf Ids |Outbuf Id |In NCHW |Out NCHW |MACS | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- 0|TIDL_DataLayer |data | 0| -1| 1| x x x x x x x x | 0 | 0 0 0 0 | 1 3 512 512 | 0 | 1|TIDL_ConvolutionLayer |conv1 | 0| 1| 1| 0 x x x x x x x | 1 | 1 3 512 512 | 1 16 256 256 | 30408704 | 2|TIDL_ConvolutionLayer |conv2_1/dw | 0| 1| 1| 1 x x x x x x x | 2 | 1 16 256 256 | 1 16 256 256 | 11534336 | 3|TIDL_ConvolutionLayer |conv2_1/sep | 0| 1| 1| 2 x x x x x x x | 3 | 1 16 256 256 | 1 32 256 256 | 37748736 | 4|TIDL_ConvolutionLayer |conv2_2/dw | 0| 1| 1| 3 x x x x x x x | 4 | 1 32 256 256 | 1 32 128 128 | 5767168 | 5|TIDL_ConvolutionLayer |conv2_2/sep | 0| 1| 1| 4 x x x x x x x | 5 | 1 32 128 128 | 1 64 128 128 | 35651584 | 6|TIDL_ConvolutionLayer |conv3_1/dw | 0| 1| 1| 5 x x x x x x x | 6 | 1 64 128 128 | 1 64 128 128 | 11534336 | 7|TIDL_ConvolutionLayer |conv3_1/sep | 0| 1| 1| 6 x x x x x x x | 7 | 1 64 128 128 | 1 64 128 128 | 69206016 | 8|TIDL_ConvolutionLayer |conv3_2/dw | 0| 1| 1| 7 x x x x x x x | 8 | 1 64 128 128 | 1 64 64 64 | 2883584 | 9|TIDL_ConvolutionLayer |conv3_2/sep | 0| 1| 1| 8 x x x x x x x | 9 | 1 64 64 64 | 1 128 64 64 | 34603008 | 10|TIDL_ConvolutionLayer |conv4_1/dw | 0| 1| 1| 9 x x x x x x x | 10 | 1 128 64 64 | 1 128 64 64 | 5767168 | 11|TIDL_ConvolutionLayer |conv4_1/sep | 0| 1| 1| 10 x x x x x x x | 11 | 1 128 64 64 | 1 128 64 64 | 68157440 | 12|TIDL_ConvolutionLayer |conv4_2/dw | 0| 1| 1| 11 x x x x x x x | 12 | 1 128 64 64 | 1 128 32 32 | 1441792 | 13|TIDL_ConvolutionLayer |conv4_2/sep | 0| 1| 1| 12 x x x x x x x | 13 | 1 128 32 32 | 1 256 32 32 | 34078720 | 14|TIDL_ConvolutionLayer |conv5_1/dw | 0| 1| 1| 13 x x x x x x x | 14 | 1 256 32 32 | 1 256 32 32 | 2883584 | 15|TIDL_ConvolutionLayer |conv5_1/sep | 0| 1| 1| 14 x x x x x x x | 15 | 1 256 32 32 | 1 256 32 32 | 67633152 | 16|TIDL_ConvolutionLayer |conv5_2/dw | 0| 1| 1| 15 x x x x x x x | 16 | 1 256 32 32 | 1 256 32 32 | 2883584 | 17|TIDL_ConvolutionLayer |conv5_2/sep | 0| 1| 1| 16 x x x x x x x | 17 | 1 256 32 32 | 1 256 32 32 | 67633152 | 18|TIDL_ConvolutionLayer |conv5_3/dw | 0| 1| 1| 17 x x x x x x x | 18 | 1 256 32 32 | 1 256 32 32 | 2883584 | 19|TIDL_ConvolutionLayer |conv5_3/sep | 0| 1| 1| 18 x x x x x x x | 19 | 1 256 32 32 | 1 256 32 32 | 67633152 | 20|TIDL_ConvolutionLayer |conv5_4/dw | 0| 1| 1| 19 x x x x x x x | 20 | 1 256 32 32 | 1 256 32 32 | 2883584 | 21|TIDL_ConvolutionLayer |conv5_4/sep | 0| 1| 1| 20 x x x x x x x | 21 | 1 256 32 32 | 1 256 32 32 | 67633152 | 22|TIDL_ConvolutionLayer |conv5_5/dw | 0| 1| 1| 21 x x x x x x x | 22 | 1 256 32 32 | 1 256 32 32 | 2883584 | 23|TIDL_ConvolutionLayer |conv5_5/sep | 0| 1| 1| 22 x x x x x x x | 23 | 1 256 32 32 | 1 256 32 32 | 67633152 | 24|TIDL_ConvolutionLayer |conv5_6/dw | 0| 1| 1| 23 x x x x x x x | 24 | 1 256 32 32 | 1 256 16 16 | 720896 | 25|TIDL_ConvolutionLayer |ctx_output1/dw | 0| 1| 1| 23 x x x x x x x | 25 | 1 256 32 32 | 1 256 32 32 | 2883584 | 26|TIDL_ConvolutionLayer |conv5_6/sep | 0| 1| 1| 24 x x x x x x x | 26 | 1 256 16 16 | 1 512 16 16 | 33816576 | 27|TIDL_ConvolutionLayer |ctx_output1/sep | 0| 1| 1| 25 x x x x x x x | 27 | 1 256 32 32 | 1 512 32 32 | 135266304 | 28|TIDL_ConvolutionLayer |ctx_output1/sep/relu_mbox_loc_perm | 0| 1| 1| 27 x x x x x x x | 28 | 1 512 32 32 | 1 16 32 32 | 75497472 | 29|TIDL_ConvolutionLayer |conv6/dw | 0| 1| 1| 26 x x x x x x x | 29 | 1 512 16 16 | 1 512 16 16 | 1441792 | 30|TIDL_ConvolutionLayer |ctx_output1/sep/relu_mbox_conf_perm | 0| 1| 1| 27 x x x x x x x | 30 | 1 512 32 32 | 1 8 32 32 | 37748736 | 31|TIDL_FlattenLayer |ctx_output1/sep/relu_mbox_loc_flat | 0| 1| 1| 28 x x x x x x x | 31 | 1 16 32 32 | 1 1 1 16384 | 16384 | 32|TIDL_FlattenLayer |ctx_output1/sep/relu_mbox_conf_flat | 0| 1| 1| 30 x x x x x x x | 32 | 1 8 32 32 | 1 1 1 8192 | 8192 | 33|TIDL_ConvolutionLayer |conv6/sep | 0| 1| 1| 29 x x x x x x x | 33 | 1 512 16 16 | 1 512 16 16 | 67371008 | 34|TIDL_PoolingLayer |pool6 | 0| 1| 1| 33 x x x x x x x | 34 | 1 512 16 16 | 1 512 8 8 | 131072 | 35|TIDL_PoolingLayer |pool7 | 0| 1| 1| 34 x x x x x x x | 35 | 1 512 8 8 | 1 512 4 4 | 32768 | 36|TIDL_PoolingLayer |pool8 | 0| 1| 1| 35 x x x x x x x | 36 | 1 512 4 4 | 1 512 2 2 | 8192 | 37|TIDL_ConvolutionLayer |ctx_output2/dw | 0| 1| 1| 33 x x x x x x x | 37 | 1 512 16 16 | 1 512 16 16 | 1441792 | 38|TIDL_ConvolutionLayer |ctx_output3/dw | 0| 1| 1| 34 x x x x x x x | 38 | 1 512 8 8 | 1 512 8 8 | 360448 | 39|TIDL_ConvolutionLayer |ctx_output4/dw | 0| 1| 1| 35 x x x x x x x | 39 | 1 512 4 4 | 1 512 4 4 | 90112 | 40|TIDL_ConvolutionLayer |ctx_output5/dw | 0| 1| 1| 36 x x x x x x x | 40 | 1 512 2 2 | 1 512 2 2 | 22528 | 41|TIDL_ConvolutionLayer |ctx_output2/sep | 0| 1| 1| 37 x x x x x x x | 41 | 1 512 16 16 | 1 512 16 16 | 67371008 | 42|TIDL_ConvolutionLayer |ctx_output3/sep | 0| 1| 1| 38 x x x x x x x | 42 | 1 512 8 8 | 1 512 8 8 | 16842752 | 43|TIDL_ConvolutionLayer |ctx_output4/sep | 0| 1| 1| 39 x x x x x x x | 43 | 1 512 4 4 | 1 512 4 4 | 4210688 | 44|TIDL_ConvolutionLayer |ctx_output5/sep | 0| 1| 1| 40 x x x x x x x | 44 | 1 512 2 2 | 1 512 2 2 | 1052672 | 45|TIDL_ConvolutionLayer |ctx_output2/sep/relu_mbox_loc_perm | 0| 1| 1| 41 x x x x x x x | 45 | 1 512 16 16 | 1 24 16 16 | 28311552 | 46|TIDL_ConvolutionLayer |ctx_output3/sep/relu_mbox_loc_perm | 0| 1| 1| 42 x x x x x x x | 46 | 1 512 8 8 | 1 24 8 8 | 7077888 | 47|TIDL_ConvolutionLayer |ctx_output4/sep/relu_mbox_loc_perm | 0| 1| 1| 43 x x x x x x x | 47 | 1 512 4 4 | 1 16 4 4 | 1179648 | 48|TIDL_ConvolutionLayer |ctx_output5/sep/relu_mbox_loc_perm | 0| 1| 1| 44 x x x x x x x | 48 | 1 512 2 2 | 1 16 2 2 | 294912 | 49|TIDL_ConvolutionLayer |ctx_output2/sep/relu_mbox_conf_perm | 0| 1| 1| 41 x x x x x x x | 49 | 1 512 16 16 | 1 12 16 16 | 14155776 | 50|TIDL_ConvolutionLayer |ctx_output3/sep/relu_mbox_conf_perm | 0| 1| 1| 42 x x x x x x x | 50 | 1 512 8 8 | 1 12 8 8 | 3538944 | 51|TIDL_ConvolutionLayer |ctx_output4/sep/relu_mbox_conf_perm | 0| 1| 1| 43 x x x x x x x | 51 | 1 512 4 4 | 1 8 4 4 | 589824 | 52|TIDL_ConvolutionLayer |ctx_output5/sep/relu_mbox_conf_perm | 0| 1| 1| 44 x x x x x x x | 52 | 1 512 2 2 | 1 8 2 2 | 147456 | 53|TIDL_FlattenLayer |ctx_output2/sep/relu_mbox_loc_flat | 0| 1| 1| 45 x x x x x x x | 53 | 1 24 16 16 | 1 1 1 6144 | 6144 | 54|TIDL_FlattenLayer |ctx_output3/sep/relu_mbox_loc_flat | 0| 1| 1| 46 x x x x x x x | 54 | 1 24 8 8 | 1 1 1 1536 | 1536 | 55|TIDL_FlattenLayer |ctx_output4/sep/relu_mbox_loc_flat | 0| 1| 1| 47 x x x x x x x | 55 | 1 16 4 4 | 1 1 1 256 | 256 | 56|TIDL_FlattenLayer |ctx_output5/sep/relu_mbox_loc_flat | 0| 1| 1| 48 x x x x x x x | 56 | 1 16 2 2 | 1 1 1 64 | 64 | 57|TIDL_FlattenLayer |ctx_output2/sep/relu_mbox_conf_flat | 0| 1| 1| 49 x x x x x x x | 57 | 1 12 16 16 | 1 1 1 3072 | 3072 | 58|TIDL_FlattenLayer |ctx_output3/sep/relu_mbox_conf_flat | 0| 1| 1| 50 x x x x x x x | 58 | 1 12 8 8 | 1 1 1 768 | 768 | 59|TIDL_FlattenLayer |ctx_output4/sep/relu_mbox_conf_flat | 0| 1| 1| 51 x x x x x x x | 59 | 1 8 4 4 | 1 1 1 128 | 128 | 60|TIDL_FlattenLayer |ctx_output5/sep/relu_mbox_conf_flat | 0| 1| 1| 52 x x x x x x x | 60 | 1 8 2 2 | 1 1 1 32 | 32 | 61|TIDL_ConcatLayer |mbox_loc | 0| 5| 1| 31 53 54 55 56 x x x | 61 | 1 1 1 16384 | 1 1 1 24384 | 81920 | 62|TIDL_ConcatLayer |mbox_conf_flatten | 0| 5| 1| 32 57 58 59 60 x x x | 62 | 1 1 1 8192 | 1 1 1 12192 | 40960 | 63|TIDL_DetectionOutputLayer |detection_out | 0| 2| 1| 61 62 x x x x x x | 63 | 1 1 1 24384 | 1 1 1 144 | 0 | 64|TIDL_DataLayer |detection_out | 0| 1| -1| 63 x x x x x x x | 0 | 1 1 1 144 | 0 0 0 0 | 0 | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Total Giga Macs : 1.2031 --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Please let me know if there is any issue in import/inference config file.
Kindly provide some suggestions too.
Thanks and Regards,
Vyom Mishra