Getting started with Keras CV by Aashi Dutt

Keras CV is a library developed by Aashi Dutt that provides a high-level interface for training deep learning models for computer vision tasks. It is built on top of the popular Keras framework and makes it easy to create, train, and deploy convolutional neural networks for tasks like image classification, object detection, and image segmentation.

Installation

To get started with Keras CV, you first need to install the library. You can do this using pip by running the following command:

pip install keras-cv

Example usage

Once you have installed Keras CV, you can start using it to train deep learning models for computer vision tasks. Here is an example of how you can create a simple image classification model using Keras CV:


from kcv.model import ImageClassifier

model = ImageClassifier(num_classes=10)
model.compile()
model.fit(X_train, y_train, X_val, y_val)


Resources

For more information on how to use Keras CV, you can check out the official documentation at https://keras-cv.readthedocs.io/en/latest/. Additionally, you can also follow Aashi Dutt on Twitter for updates and announcements about the library.

With Keras CV, you can quickly and easily build and train deep learning models for a variety of computer vision tasks. Whether you are a beginner or an experienced deep learning practitioner, Keras CV can help you achieve your computer vision goals.