Picsellia
  • Picsellia
  • Getting started
    • Start using Picsellia
    • Create, annotate, review a Dataset
    • Create a new Dataset Version with merged labels
    • Train a custom Object Detection model
    • Train a custom Classification model
    • Deploy model in production (Tensorflow only)
    • Feedback loop - Send predictions from models to Datalake or Datasets
  • Data Management
    • Upload assets to your Lake
    • Edit Tags for Pictures
    • Create a Dataset
    • Add data to a Dataset
    • Create a new Dataset version
    • Configure your Labels
    • Import annotation from other Dataset version
  • Experiment Tracking
    • Initialize an experiment
    • Checkout an experiment
    • Log your results to Picsell.ia
    • Store your files to Picsell.ia
    • Evaluate your models
    • Retrieve and update your assets
    • Publish your model
    • Namespace
  • Hyperparameter tuning
    • Overview
    • Install Picsell CLI
    • Config
    • Launch your Hyperparameters tuning
  • Models
    • Model HUB
  • References
    • API Reference
    • Python SDK Reference
    • Python Training Reference
  • Organization
  • Website
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On this page
  • Architecture list
  • Tensorflow 2
  • Pytorch

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  1. Models

Model HUB

On Picsellia, you willl found what we call the Model HUB which is a place where we put every available pre-trained architectures from SOTA benchmarks and where YOU can also upload the trained models you want to share with the community.

Architecture list

Here we have listed all the available architectures that we are responsible of for different frameworks.

Tensorflow 2

  • efficientdet-d0

  • efficientdet-d1

  • efficientdet-d2

  • efficientdet-d3

  • efficientdet-d4

  • efficientdet-d5

  • faster-rcnn-inception-resnet-v2-640x640

  • faster-rcnn-inception-resnet-v2-1024x1024

  • faster-rcnn-resnet50-v1-640x640

  • faster-rcnn-resnet50-v1-800x1333

  • faster-rcnn-resnet50-v1-1024x1024

  • faster-rcnn-resnet101-v1-640x640

  • faster-rcnn-resnet101-v1-800x1333

  • faster-rcnn-resnet101-v1-1024x1024

  • faster-rcnn-resnet152-v1-640x640

  • faster-rcnn-resnet152-v1-800x1333

  • faster-rcnn-resnet152-v1-1024x1024

  • ssd-mobilenet-v1-fpn-640

  • ssd-mobilenet-v2-fpnlite-320

  • ssd-mobilenet-v2-fpnlite-640

  • ssd-resnet50-v1-640x640

  • ssd-resnet50-v1-1024-1024

  • ssd-resnet101-v1-640x640

  • ssd-resnet101-v1-1024-1024

  • ssd-resnet152-v1-640x640

  • ssd-resnet152-v1-1024-1024

Pytorch

  • YOLOv5-s

  • YOLOv5-m

  • YOLOv5-l

  • YOLOv5-xl

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Last updated 3 years ago

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