🥑 Start by installing the Picsellia python package in your best dev environnement 🥑
pip install picsellia
Our mission is to give you all the necessary tools to relief the burden of AI projects off of your shoulders. As a data scientist / ML engineer / Researcher, you shouldn't have to worry about the following topics :
- 💾 Data Management
- 📈 Experiment Tracking
- 🔬 Hyperparameters Tuning
- 📘 Model Management
- 🚀 Model Deployment
- 👀 Model Monitoring
Picsellia is the one-stop place for all the life-cycle of your Computer Vision projects, from ideation to production in a single platform 🚀.
As we know, you are most likely to like your IDE and having full control over your training code, that's why all the component from Picsellia are accessible from our Python SDK or through our APIs.
But sometimes, the R&D team need to pass the ball 🏀 to the product team that won't be confortable with manipulating huge code. That's why you can also manipulate everything done on Picsellia with a simple and intuitive platform, that way, everyone is happy! We like happy people :)
From uploading data to model deployment, you can do everything either from the platform, or from your code.
We really hope you will find everything you need for your projects, if you have any feature request, please write us on one of our channels. (You can talk with us in English or French, we prefer English though so everybody on the channels can understand 😌)
To help you figure out what you can or can't do with Picsell.ia, here are the main features that we developed that can cover many aspects of your projects, but don't hesitate to dig into each feature to see how you can achieve what you want or just ask us !
Isn't it a pain to find a way to store all your data and share it with your team in a way that it is accessible easily for all your experiments and projects ?
That's why we created the Datalake , where you can :
All your data
To learn more about the Datalake : 👉 Browse full doc
To let you iterate over your data while being sure you don't lose everything in the way, we provide datasets management solution which is a powerful versioning tool where you can :
- Create different version of datasets
- Annotate your data
- Clone images / labels / annotations from one dataset to another in a granular way
- Merge your annotations in one click
To learn more about Datasets : Learn how to Create a Dataset
If you stored some data in your Datalake and created one or several Datasets, you can now annotate your images with geometric shapes for object detection, segmentation, keypoints and classification.
To see all the possible way to annotate your data, please refer to this piece of documentation :
Have you ever feel that you are a notebook collector ? That they lack interactivity or on the contrary that you have no way to collect your logs, results efficiently for your algorithms when they run on remote machines ?
Well that's why we have designed a full-fledged experiment tracking system that allows you to perform a lot of things :
You can export your experiments and add them to your models registry in order to:
- Use them to kickstart your experiments (for example fine-tuning a model on your own data)
- Deploy them for inference with an API endpoint
- Add some documentation so everyone knows what your model does and how to use it
- Share them with your team or organization
Now that you have trained your own custom model or using one from the model HUB, you might want to expose it to the world (or at least your company or client) with an API endpoint, hopefully you can do it with one click only from the Picsell.ia interface, or from the Python SDK and then make predictions using your API token.
You can log all your predictions to Picsellia in order to visualize it and access a lot of monitoring metrics like KS Drift, AE Outlier or just inference time :)
Updated 6 months ago