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-0.0.29.tar.gz (81.0 kB view details)

Uploaded Source

Built Distribution

pytorchcv-0.0.29-py2.py3-none-any.whl (176.9 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file pytorchcv-0.0.29.tar.gz.

File metadata

  • Download URL: pytorchcv-0.0.29.tar.gz
  • Upload date:
  • Size: 81.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.12.1 pkginfo/1.4.2 requests/2.18.4 setuptools/40.6.3 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.6.5

File hashes

Hashes for pytorchcv-0.0.29.tar.gz
Algorithm Hash digest
SHA256 62411287d37b11ec2bf2534ae817c9aeffcfdb5604fc1e75505f0e53027cec98
MD5 a91f2d6b3f357bd330c84d3400e299b6
BLAKE2b-256 4eb51a06c0d4bd83b8c266412bad3facd923aec3e9e3b3e9552d56f15596b42f

See more details on using hashes here.

File details

Details for the file pytorchcv-0.0.29-py2.py3-none-any.whl.

File metadata

  • Download URL: pytorchcv-0.0.29-py2.py3-none-any.whl
  • Upload date:
  • Size: 176.9 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/40.6.3 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.6.5

File hashes

Hashes for pytorchcv-0.0.29-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 5c33d7af1c8d37d337372d09cc9522937f8d96f6fba5d6869e974d906c910fbf
MD5 1c6f03be3345ab2547a11edc6621c3c3
BLAKE2b-256 edf77f102c2b188b3e787b632ef4c5bb61fa5a53494c3968aed6fe992c02d5c6

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