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-0.0.22.tar.gz (61.0 kB view details)

Uploaded Source

Built Distribution

pytorchcv-0.0.22-py2.py3-none-any.whl (123.7 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file pytorchcv-0.0.22.tar.gz.

File metadata

  • Download URL: pytorchcv-0.0.22.tar.gz
  • Upload date:
  • Size: 61.0 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-0.0.22.tar.gz
Algorithm Hash digest
SHA256 8788b9598ad055961760a49f35f41f172a7b8db5dc6bdf4fb5836c8f9373d1da
MD5 2b256de929a1a61c477d097093775eb1
BLAKE2b-256 353ca164cc7c30e66410565f5c95ce86b1555c9b315ae49f99fbcec1e9e101f2

See more details on using hashes here.

File details

Details for the file pytorchcv-0.0.22-py2.py3-none-any.whl.

File metadata

  • Download URL: pytorchcv-0.0.22-py2.py3-none-any.whl
  • Upload date:
  • Size: 123.7 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-0.0.22-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 c28d95c9dd14f73d7a0f5411095272e7c22467ea955269d270331a18908384d8
MD5 717885eb2f07877f936062ecc4e27966
BLAKE2b-256 1a81d1374797020464424fbabbb68d9b44712d6707836e098cfb58dc9ff74a7a

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