Multi-class object detection and bounding box regression with Keras, TensorFlow, and Deep Learning

Description

Summary

• In order to create a multi-class object detector from scratch with Keras and TensorFlow, we’ll need to modify the network head of our architecture.
• With the optimizer initialized, we compile the model and display a summary of the model architecture to our terminal (Lines 155 and 156) — we’ll review the output of the model summary when we execute the train.py script later in this tutorial.
• Detecting where the object is in the input image Correctly labeling what the detected object is You can use the code and methods discussed in this tutorial as a starting point for training your own custom multi-class object detectors using bounding box regression and Keras/TensorFlow.
• How to train CNNs on your own datasets.