Image semantic segmentation and object detection are two key tasks in computer vision. Semantic segmentation classifies each pixel in an image into a specific category, while object detection identifies objects and determines their locations. This guide demonstrates how to implement both tasks using...
System Environment and Required Packages CentOS 7 Anaconda3-5.1.0 TensorFlow 2.1.0 Keras 2.3.1 PyTorch 1.8.0 (CPU) TorchVision 0.9.0 Install Anaconda, TensorFlow/Keras on Internet-Connected Systems 2.1 Anaconda Installation on Linux For Linux systems (e.g., CentOS7 on VMware), ensure VMware-related...
Paper Overview The paper can be found at: https://arxiv.org/abs/1711.06396 Code Execution Multiple implementasions exist: A TensorFlow 2.0.0 implementation of VoxelNet. An unofficial TensorFlow version (selected here). A TensorFlow-based VoxelNet system for autonomous driving. The chosen repository...
Saving and restoring in TensorFlow depends on the API level you use. In graph-mode TensorFlow 1.x, checkpoints capture Variable values; graph structure can be reloaded from a MetaGraph. In TensorFlow 2.x/Keras, the recommended format is SavedModel (or H5 for Keras-only models), and object-based chec...