Try it out

The examples brought in for our trials are NVIDIA Inferencing library which includes TensorRT-accelerated deep learning networks. These networks are built to complete taks such as

• Image Recognition

• Object Detection with Localization (i.e. bounding boxes)

• Semantic Segmentation

• Pose Estimation

• Depth Estimation

For this section we will run Command Line Instruction to run some of the pre-trained models with the example dataset.

(Note!) All the sample programs will be based on python language.

• Image Recognition
  • Launching the Program
  • Examples through Jupyter Notebook
    • Recognizing Oranges with GoogleNet network (image input)
    • Recognizing Oranges with Alex network (image input)
• Object Detection
  • Launching the Program
  • Examples through Jupyter Notebook
    • Detecting and Locating a car using SSD network (video input)
    • Detecting Pedestrians in a Video
    • Various Object Detection through a Camera
    • Detecting Faces through a Camera
    • Detecting Dogs through a Camera
• Object Detection
  • Launching the Program
  • Examples through Jupyter Notebook
    • Object Segmentation through a Camera
• Pose Estimation with PoseNet
  • Launching the Program
  • Examples through Jupyter Notebook
    • Hand Gesture Recognition through a Camera
• Monocular Depth with DepthNet
  • Launching the Program
  • Examples through Jupyter Notebook
    • Depth Estimation through a Camera