Develop a model that performs a reverse image search and identifies the objects present in the image. The user will upload an image, and the model will classify the content of the image based on different classes such as:
- Plant/flower/bird
- Academic buildings/offices/infrastructure
The code trains a convolutional neural network (CNN) using the VGG19 architecture to classify images into different categories. The model is trained using a dataset of images and their corresponding labels. After training, the model is saved and can be used for prediction.
The code also includes an example of how to use the trained model to predict the class of an input image.
