mediapipe

This isn't really true. They are different offerings. CoreML is specific to the Apple ecosystem and lets you convert a PyTorch model to a CoreML .mlmodel that will run with acceleration on iOS/Mac. Google Mediapipe is a giant C++ library for running ML flows on any device (iOS/Android/Web). It includes Tensorflow Lite (now LiteRT) but is also a graph processor that helps with common ML preprocessing tasks like image resizing, annotating, etc. Google killing products early is a good meme but Mediapipe is open source so you can at least credit them with that. https://github.com/google-ai-edge/mediapipe I used a fork of Mediapipe for a contract iOS/Android computer vision product and it was very complex but worked well. A cross-platform solution would not have been possible with CoreML.

More information here: https://ai.google.dev/edge/mediapipe/solutions/guide (It seems to be open source: https://github.com/google-ai-edge/mediapipe) I think this is a unified way of deploying AI models that actually run on-device ("edge"). I guess a sort of "JavaScript of AI stacks"? I wonder who the target audience is for this technology?

To be clear does it mean access on Apple devices and not like an Apache 2 licensed Github repository? https://twitter.com/yeemachine/status/1656391928223768576?s=... https://mediapipe-studio.webapps.google.com/demo/face_landma... https://github.com/google/mediapipe

I believe Google already released transformers under an apache 2 license with a patent grant: https://github.com/google/mediapipe/blob/master/mediapipe/mo...

I was going to say that I like the MediaPipe Selfie Segmentation model for doing this sort of thing in a web page, but I've just noticed (when getting the GitHub link[1]) that Google have marked the code as legacy[2] ... no idea if the new solution is better/easier to use[3]. For what it's worth, my CodePen using the old model is here: https://codepen.io/kaliedarik/pen/PopBxBM [1] - https://github.com/google/mediapipe/blob/master/docs/solutio... [2] - "Attention: Thank you for your interest in MediaPipe Solutions. As of April 4, 2023, this solution was upgraded to a new MediaPipe Solution." [3] - https://developers.google.com/mediapipe/solutions/vision/ima...

Google/Mediapipe has a better performing models here https://github.com/google/mediapipe/tree/master/mediapipe/mo...

This architecture was also used in the link referenced when bringing up alternative implementations: https://github.com/google/mediapipe/issues/877#issuecomment-...

This looks similar to Google's Mediapipe [0] [0] https://github.com/google/mediapipe

Not exactly as powerful but something similar and that can run on a browser, opening up to a lot of creative applications, handpose powered by tf.js(similar model exists for tflite) Demo: https://storage.googleapis.com/tfjs-models/demos/handpose/in... Repo: https://github.com/tensorflow/tfjs-models/blob/master/handpo... Tflite model: https://github.com/google/mediapipe/tree/master/mediapipe/mo... there is lighter 2d model as well

In other news, there's a Google MediaPipe hand tracking example.[1][2] It's still documented as iOS/Android only, but there's now a hand_tracking directory under linux desktop examples![3] Results have been mixed.[4] [1] https://ai.googleblog.com/2019/08/on-device-real-time-hand-t... [2] https://github.com/google/mediapipe/blob/master/mediapipe/do... [3] https://github.com/google/mediapipe/tree/master/mediapipe/ex... [4] https://www.youtube.com/watch?v=ZwgjgT9hu6A (Aug 31)

Something iOS/Android developers might play with, is Google's recent TensorFlow/MediaPipe optical hand pose example: https://ai.googleblog.com/2019/08/on-device-real-time-hand-t... https://github.com/google/mediapipe/blob/master/mediapipe/do... But real-world performance can be poor: https://www.youtube.com/watch?v=ZwgjgT9hu6A The hand pose example doesn't support Linux at present.

The underlying project MediaPipe looks pretty cool: https://github.com/google/mediapipe/blob/master/mediapipe/do... I wonder why they didn't build it on top of one of the gazillion flow-based visual programming languages instead?