Posted by Jen Person, Senior Developer Relations Engineer
I’m the type of person to say I don’t like to make New Year’s resolutions, but then I still quietly resolve to make some changes anyway. After overindulging over the holidays, I resolve to eat healthier, exercise more, spend more time with friends and family, and prioritize my mental health…but they’re not *New Year’s* resolutions I swear! Because whether you like to make New Year’s resolutions or not, the start of a new year can give you a feeling of inspiration. It’s like a blank slate full of possibilities!
What kind of changes are you resolving to make this year? If you’re looking to create an exciting new web project or take your work to the next level, then I recommend adding machine learning (ML)!
Near year, new solutions
MediaPipe has been a great go-to solution for web developers interested in adding ML to their web applications. In 2022, the MediaPipe hands NPM package had around 70K downloads, the pose package had about 90K downloads, and the selfie segmentation package had over 130K downloads!
This year, MediaPipe has expanded to include MediaPipe Tasks, Model Maker, and Studio! Tasks are aptly named because they can be used to perform common ML tasks like image classification and object detection. Model Maker is a low-code solution for customizing your MediaPipe Tasks to fit your app’s needs. With MediaPipe Studio, you can view interactive demos of MediaPipe Tasks. In the future, you will be able to customize your tasks in MediaPipe Studio without writing any code.
When compared to server-side ML, web ML has some unique benefits:
Lower latency – Predictions are done right on your users’ devices, so there is no waiting for server calls to complete. This is essential for applications that use a streaming component like the webcam.
User privacy – With predictions taking place on-device, your users’ data never leaves their device.
Click and go – Your users don’t have to download any additional applications or plugins. Just navigate to the desired URL and your ML experience is good to go!
MediaPipe is updating its offerings, including more solutions and opportunities for customization. Check out these new MediaPipe Tasks:
Image Classification – identify what an image represents among a set of categories defined at training time.
Object Detection – detect the presence and location of multiple classes of object.
Text Classification – classify text into a set of defined categories, such as positive or negative sentiment.
Gesture Recognition – recognize specific hand gestures from a user, and invoke application features that correspond to those gestures.
Hand Landmark Detection – localize key points of the hands and render visual effects over the hands.
MediaPipe is adding more exciting solutions in 2023, so keep an eye out for what’s next!
Customize for your needs
Many of these solutions offer customization using MediaPipe Model Maker. The MediaPipe Model Maker package is a simple, low-code solution for customizing on-device ML models, including models for the web. And with MediaPipe Studio, you can prototype and benchmark solutions in-browser!
Resolve to make something great!
By now, a lot of our New Year’s resolutions have already been abandoned. But it’s definitely not too late to make a new one! Why not resolve to build something amazing with MediaPipe solutions for the web?
Create a rock paper scissors game
At the Women in ML Symposium, the MediaPipe team hosted a workshop walking through creating a rock paper scissors game using the MediaPipe solutions Gesture Recognizer task. Learn how to train a custom gesture recognizer by following along with the workshop on YouTube using the corresponding Colab notebook. You can also view a complete version of the game on Codepen.
Categorize your images
When uploading images, run image classification to automatically add relevant tags. Check out the image classification task documentation and the Codepen demo to see how to get started. You can even customize your model to add your own tags to suit your needs.
Run sentiment analysis
Want to get an idea how your users are feeling? Run sentiment analysis on text to classify it as positive or negative. See the documentation and the Codepen demo to find out how it’s done. The best part is that you can also customize your model to classify text in whatever category you need!