TensorFlow 2.x

This section outlines all computer-vision training and finetuning pipelines that are implemented with TensorFlow 2.x.

The source code for these networks are hosted on GitHub.

• Image Classification (TF2)
  
  • Preparing the Input Data Structure
  • Creating an Experiment Spec File - Specification File for Classification
  • Training the model
  • Evaluating the Model
  • Running Inference on a Model
  • Pruning the Model
  • Re-training the Pruned Model
  • Exporting the model
  • TensorRT Engine Generation, Validation, and int8 Calibration
  • Deploying to DeepStream
• EfficientDet (TF2)
  
  • Data Input for EfficientDet
  • Pre-processing the Dataset
  • Creating a Configuration File
  • Training the Model
  • Evaluating the Model
  • Running Inference with an EfficientDet Model
  • Pruning the Model
  • Re-training the Pruned Model
  • Exporting the Model
  • TensorRT Engine Generation, Validation, and int8 Calibration
  • Deploying to DeepStream