Comments (4)
@dkozlov We have Dockerfile that you can use to build docker containers of MediaPipe.
Typically, MediaPipe graph runtime is one to one machine instance (i.e. parallel independent machines running multiple independent MediaPipe graphs). There is currently no support for MediaPipe in distributed mode (one graph on several machines).
What is the distributed mode you are looking for? and what use case? Media processing of lots of video files
from mediapipe.
For example if you have a pipeline which should be executed in the real time and consist of large neural network models which could not be placed on the single instance. Model parallelism, lower-latency parallel inference (at batch size 1). As I remember Tensorflow could be runned in distributed mode for model parallelism. Do you have any example of integration mediapipe with https://github.com/tensorflow/mesh?
from mediapipe.
@dkozlov Unfortunately we don't have such an example working with TensorFlow Mesh. Is your model that big that it you need model parallelism? What's the use cast?
from mediapipe.
Thank you for response @mgyong! I have several different models which depend on each other and connected into single complicated pipeline and do not fit in single node. My workload is low-latency parallel inference with batch size equals to single image. Full pipeline latency should be less than 1 second. Actually I am not using the model parallelism it is just separately connected models but I am curious if mediapipe could help me.
from mediapipe.
Related Issues (20)
- Add Jetpack Compose Support HOT 1
- crash at libimagegenerator_gpu.so lib HOT 1
- Add support for latest protobuf HOT 1
- How change graph vertical_fov_degrees value with input_side_packet or other way [python] HOT 2
- Pose Landmarks model not working as expected on iOS HOT 2
- Multiple Person Pose Detection HOT 1
- mediapipe cannot correctly identify landmark HOT 1
- How to set a system prompt for RAG implementation for Inference for Gemma 2b on IOS ? HOT 3
- Installation Issue HOT 2
- MediaPipe python 3.12 not working HOT 1
- Landmarks for FaceMesh model HOT 4
- tasks-vision does not appear to be compatible with opencv.js HOT 3
- ImageProcessingOptions package is not correct in docs HOT 7
- CanvasRenderingContext2D is not defined in DrawingUtils constructor
- Broken links in docs/getting_started
- Broken links in docs/getting_started
- ImageEmbedderOption quantize behavior HOT 1
- Reuse video texture for mask mixing HOT 4
- Mediapipe tasks-vision iOS 17+ inside Web Workers not working, despite iOS 17+ already support it. HOT 2
- HandLandmarker's min_hand_detection_confidence is not consistent HOT 2
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from mediapipe.