Gestures Unlocked: AI Recognizes Emojis in Real-Time
Imagine a world where you can communicate with your computer using nothing but gestures. No more typing or clicking – just a wave of your hand or a flick of your finger, and your AI assistant will understand exactly what you mean. Sounds like science fiction, but it’s not. Thanks to the incredible work of Nick Bourdakos, a programmer from IBM, we can now control our computers with gestures, and it’s all thanks to a clever AI that can recognize emojis in real-time.
The AI that Can Read Your Mind
Nick’s AI is a master of gesture recognition, and it’s not just limited to a simple “hello” or “goodbye.” It can recognize a wide range of gestures, from simple hand movements to more complex actions like drawing in the air. And the best part? It’s all done in real-time, with almost no delay. This is made possible by the use of TensorFlow.js, an open-source machine learning framework that allows developers to build AI models that can run directly in the browser.
The Model that Can See Your Hand
Nick’s AI model is based on a simple yet powerful architecture called SSD-MobileNet. This model uses a combination of convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to identify gestures and convert them into emojis. The model is trained on a dataset of annotated gesture drawings, which are used to teach the AI what different gestures look like.
Training the Model
To train the model, Nick used a combination of conventional methods and deep learning algorithms. The model was trained on a GPU (Graphics Processing Unit) in IBM’s cloud, and it took just half an hour to train. Before training, Nick had to prepare the data by annotating gesture drawings, which involved labeling each gesture with a corresponding emoji. This was done using a tool called Cloud Annotations, which allows developers to annotate data and train models in the cloud.
Getting Started with Gesture Recognition
If you want to try gesture recognition for yourself, you can start by installing the Cloud Annotations CLI (Command-Line Interface) tool. This will allow you to interactively create a config.yaml file, start a training run, monitor the logs of a training run, and more. To get started, simply run the following command:
$ npm install -g cloud-annotations
Then, you can begin the training process by running the following command:
$ cacli
This will launch the Cloud Annotations CLI tool, which will guide you through the process of training the model.
Running the Model in the Browser
Once the model is trained, you can run it in the browser using a conversion script that comes with the GitHub project. This will allow you to control your computer with gestures, and it’s a truly magical experience. To get started, simply add the model to a React App, and then run the following command:
$ npm start
This will launch the model in the browser, and you can begin experimenting with gestures. Simply draw in the air, and your AI assistant will recognize your gestures and display the corresponding emojis.
Beyond Emojis: Recognizing Soft Drinks
But what if you want the AI to recognize more complex gestures, like identifying soft drinks? Nick’s model can do just that, and it’s a great example of the power of gesture recognition. In this example, the AI is trained to recognize two different soft drinks: Sprite and Canada Dry. The model is then tested with a series of gestures, and it’s able to accurately identify the soft drinks every time.
Conclusion
Gesture recognition is a rapidly evolving field, and Nick’s AI is a great example of the incredible progress that’s being made. With the ability to recognize emojis in real-time, we can now control our computers with gestures, and it’s a truly magical experience. So, what are you waiting for? Get started with gesture recognition today, and discover the incredible possibilities that this technology has to offer.