Thresholds information

This section of the user-config file contains information about various thresholds required by Smart-NMS.

The Smart-NMS: user-config (ihresholds Information) parameters are:

  • score-threshold: Filters boxes with specified score-threshold.

    Optional. Default: 0.05

    Type: Float

  • nms-threshold: Filters boxes with specified threshold on IoU across various boxes.

    Optional. Default: 0.45

    Type: Float

  • max-detections-image: Limits the maximum detection per batch to specified number.

    Optional. Default: 100

    Type: Int

  • max-boxes-class: Limits the maximum filtered out boxes to specified number per class. This field will be used when do-class-specific is set to True, otherwise ignored.

    Optional. Default: 100

    Type: Int

A sample config file for resnet34-ssd that is required from a user to capture all the options.

###################################################################
#                   Architecture Parameters
##################################################################
model-architecture : "resnet34ssd"
# Options for model architecture :
# "resnet34ssd"
# "mv1ssd"
# "retinanet"
# "yolov3"
# "yolov4"
# "yolov5"
# "resnet18ssd"
# "retinaface"


num-classes : 81
num-landmark : 0
layout : "NCD"

# Input information
input-info:
    # Model input image's layout information
    input-layout : "NCHW"

# Options for layout :
# "NCD"
# "NDC"
# "NHWC"
# "NCHW"
# "NAWHC"
bbox-output-list : ["325"]
score-output-list : ["329"]
landmark-output-list : []
do-class-specific-nms : True
do-softmax : False
background-class-idx : 0
map-classes-coco-81-to-91 : False
# boolean value to tell which NMSABP is invokedmake


##################################################################
#                    I/O Configuration
##################################################################
model-output-dir : "./r34-aimet-model/onnx_output"
model-output-extension : ".bin"
model-num-outputs : 1
abp-output-dir : "./r34-new-output"
prior-filepath : "./data/resnet34ssd/priors_r34.bin"

# CPU or AIC
model-run-time : "AIC"

# Required if model-run-time is AIC
aic-model-info:
        model-binary-dir: "./r34-aimet-model/r34-binaries"
        # 1 = "On",
        # 2 = "Quantize",
        # 3 = "Transpose",
        # 4 = "Convert",
        # 5 = "Off",
        # Others : "Invalid"

        skip-transform-value      : 1
        model-output-suffix       : "-activation-0-inf-"

# Required if model-run-time is CPU
cpu-model-info:
        model-output-suffix : ""
        model-outputs :
                # Array of names
                names   : ["329" , "325" ]
                # 2D Array of shapes
                shapes  :
                         - [1, 81, 15130]
                         - [1, 4, 15130]
                # Supported types "float", "float16", "int8Q", "uint8Q", "int16Q", "int32Q", "int32I", "int64I", "bool"
                types   : ["float","float"]

                # offsets and scales are required for ["int8Q", "uint8Q", "int16Q", "int32Q"] types.
                # array of offsets
                offsets : [0,0]
                # array of scales
                scales  : [1,1]

        # Model input config
        # All are parallel arrays of input config
        model-inputs:
                # array of names
                names  : ["input_1"]
                # 2D Array of shapes
                shapes :
                        - [1, 3, 1200, 1200]

##################################################################
#                   Thresholding Parameters
##################################################################
score-threshold : 0.05
# score threshold to be used in classwise and classagnostic abp-nms
nms-threshold : 0.5
# iou threshold to used in nms
max-detections-image : 600
# overall threshold on one data point/ image
max-boxes-class : 100
# maxBoxesPerClass may be limited to be used with class specific abp-nms