Skip to main content

Image classification models for PyTorch

Project description

Large-scale image classification networks

Collection of large-scale image classification models on PyTorch, pretrained on the ImageNet-1k dataset.

Installation

To install, use:

pip install pytorchcv torch>=0.4.1

To enable/disable different hardware supports such as GPUs, check out PyTorch installation instructions.

Usage

Example of using the pretrained ResNet-18 model:

from pytorchcv.model_provider import get_model as ptcv_get_model
net = ptcv_get_model("resnet18", pretrained=True)

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

pytorchcv-0.0.26.tar.gz (74.4 kB view details)

Uploaded Source

Built Distribution

pytorchcv-0.0.26-py2.py3-none-any.whl (158.2 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file pytorchcv-0.0.26.tar.gz.

File metadata

  • Download URL: pytorchcv-0.0.26.tar.gz
  • Upload date:
  • Size: 74.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.18.4 setuptools/39.1.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.6.5

File hashes

Hashes for pytorchcv-0.0.26.tar.gz
Algorithm Hash digest
SHA256 c4e2f8ccfa3714237eefb077b9f09a5976a64c8fa95d9448130bdf94db0645bb
MD5 f85d597dd37bc4dd1708ff8b6329fc64
BLAKE2b-256 567e8e75cca0dcbae736877c06e6db5551ce8a0e80c4ad586370bdae5f6e95e5

See more details on using hashes here.

File details

Details for the file pytorchcv-0.0.26-py2.py3-none-any.whl.

File metadata

  • Download URL: pytorchcv-0.0.26-py2.py3-none-any.whl
  • Upload date:
  • Size: 158.2 kB
  • Tags: Python 2, Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.18.4 setuptools/39.1.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.6.5

File hashes

Hashes for pytorchcv-0.0.26-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 cc771f712578a484d345458773d5264713ddb762e09f6efab4dc6b6f2d94c04d
MD5 1fb39e1093eb4108929723605b6759fc
BLAKE2b-256 25d5abc3f9c98f6a59f1da67262251f0466e720dc916210fa630b0f4a45dc217

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