Skip to main content

Computer Vision models and training

Project description

Quickvision

  • Faster Computer Vision.

GitHub issues GitHub forks GitHub stars GitHub license codecov

PEP8 CI Tests Docs PyPi Release

Slack Downloads Downloads Downloads

demo

Install Quickvision

  • Install from PyPi.

  • Current stable release 0.1.1 needs PyTorch 1.7.1 and torchvision 0.8.2.

    pip install quickvision
    

What is Quickvision?

  • Quickvision makes Computer Vision tasks much faster and easier with PyTorch.

    It provides: -

    1. Easy to use PyTorch native API, for fit(), train_step(), val_step() of models.
    2. Easily customizable and configurable models with various backbones.
    3. A complete PyTorch native interface. All models are nn.Module, all the training APIs are optional and not binded to models.
    4. A lightning API which helps to accelerate training over multiple GPUs, TPUs.
    5. A datasets API to convert common data formats very easily and quickly to PyTorch formats.
    6. A minimal package, with very low dependencies.
  • Train your models faster. Quickvision has already implemented the long learning in PyTorch.

Quickvision is just PyTorch!!

  • Quickvision does not make you learn a new library. If you know PyTorch, you are good to go!!!
  • Quickvision does not abstract any code from PyTorch, nor implements any custom classes over it.
  • It keeps the data format in Tensor so that you don't need to convert it.

Do you want just a model with some backbone configuration?

  • Use model made by us. It's just a nn.Module which has Tensors only Input and Output format.
  • Quickvision provides reference scripts too for training it!

Do you want to train your model but not write lengthy loops?

  • Just use our training methods such as fit(), train_step(), val_step().

Do you want multi GPU training but worried about model configuration?

  • Just subclass the PyTorch Lightning model!
  • Implement the train_step(), val_step().

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

quickvision-0.2.1.tar.gz (35.3 kB view details)

Uploaded Source

Built Distribution

quickvision-0.2.1-py3-none-any.whl (52.1 kB view details)

Uploaded Python 3

File details

Details for the file quickvision-0.2.1.tar.gz.

File metadata

  • Download URL: quickvision-0.2.1.tar.gz
  • Upload date:
  • Size: 35.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.4

File hashes

Hashes for quickvision-0.2.1.tar.gz
Algorithm Hash digest
SHA256 0e460201dd514b8df4b5085f12fb1c697a45b0813fea5dcffdec96493550a464
MD5 fac375f3396cffb972f13551fd0b44dd
BLAKE2b-256 4467d379949820d97655cd9e2c08184368985bb18c6b9ebea33a89a229ed3254

See more details on using hashes here.

File details

Details for the file quickvision-0.2.1-py3-none-any.whl.

File metadata

  • Download URL: quickvision-0.2.1-py3-none-any.whl
  • Upload date:
  • Size: 52.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.4

File hashes

Hashes for quickvision-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 adc10b339afa3e272ae1ffcdb9be50ef99bb84c8c28ea9fa92a4975e96e2d1a5
MD5 f28a4dac82ef9ce0f9e2df324f01cfab
BLAKE2b-256 69ec94263107146bd6928ba8d0a3509bdf4763829fe65257dffd7008a5ae74e5

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page