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Vehicle App

App Overview

Detects vehicles and classifies vehicle types. The classification function will be updated soon.

Main Features

  1. Detects vehicles and classifies vehicle types.
  2. Events are generated by checking for reverse driving or speeding.

App Application Architecture

Architecture Overview

Det (Vehicle)─────Tracker (NvDCF)

VehicleDet : {0:vehicle}

Model Infomation

  • VehicleDet

    1. Description

      Detects vehicles.

    2. Version


    3. Dataset Properties

      Category name Number of Images Number of Instances
      vehicle 23287 194050
      Total 23287 194050
    4. Performance

      Category name Recall 50:95 Precision 50:95
      vehicle 86 93.1
      mean 86 93.1

Input / Output


Input Type : Image

Input Format : RGB

Input Resolution : 640 X 640 X 3 (W x H x C)




Output Type : Lable, Boundary-box(Bbox), Confidence Scores, Track ID

Output Type Data Type
Lable str
Bbox list: [x: float, y:float, w:float , h:float ]
Confidence Scores float
Track ID int
Event str

OUTPUT IMAGE (picture)

Software Integration

Runtime Engine:

  • Autocare Edge 1.7

Preferred System Spec:

  • OS : Ubuntu (debian)
  • GPU : NVIDIA RTX 3070, NVIDIA RTX 4090, etc(Nvidia).

Limitation & Warning

Small objects : The object size must be at least 5% of the total image size for detection.

Crowded objects : In the case of crowd objects, they can be recognized as a single object by the Iou algorithm.

Camera distortion : A skewed input may not fit the model's domain.

Dark or blurry objects : It may not pass the threshold and therefore go undetected.