# Default - 0
randParams         = 0 

# 0: Caffe, 1: TensorFlow, Default - 0
modelType          = 0 

# 0: Fixed quantization By tarininng Framework, 1: Dyanamic quantization by TIDL, Default - 1
quantizationStyle  = 1 

# quantRoundAdd/100 will be added while rounding to integer, Default - 50
quantRoundAdd      = 25

numParamBits       = 8
# 0 : 8bit Unsigned, 1 : 8bit Signed Default - 1
inElementType      = 0 

inputNetFile       = "d:\work\adas\TI\work_space\tidl\model\caffe_jacinto_models\trained\object_detection\voc0712\JDetNet\ssd768x320_ds_PSP_dsFac_32_hdDS8_0\sparse\deploy.prototxt"
inputParamsFile       = "d:\work\adas\TI\work_space\tidl\model\caffe_jacinto_models\trained\object_detection\voc0712\JDetNet\ssd768x320_ds_PSP_dsFac_32_hdDS8_0\sparse\voc0712_ssdJacintoNetV2_iter_120000.caffemodel"
outputNetFile      = "..\..\test\testvecs\config\tidl_models\jdetnet\tidl_net_jdetNet_ssd.bin"
outputParamsFile   = "..\..\test\testvecs\config\tidl_models\jdetnet\tidl_param_jdetNet_ssd.bin"

rawSampleInData = 0
preProcType   = 4

sampleInData = "..\..\test\testvecs\input\768_320_114.jpg"

tidlStatsTool = "..\quantStatsTool\eve_test_dl_algo.out.exe"

layersGroupId = 0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	2	0
conv2dKernelType = 0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1	1