monetjoe/cv_backbones

Dataset Card for "monetjoe/cv_backbones"

This repository consolidates the collection of backbone networks for pre-trained computer vision models available on the PyTorch official website. It mainly includes various Convolutional Neural Networks (CNNs) and Vision Transformer models pre-trained on the ImageNet1K dataset. The entire collection is divided into two subsets, V1 and V2, encompassing multiple classic and advanced versions of visual models. These pre-trained backbone networks provide users with a robust foundation for transfer learning in tasks such as image recognition, object detection, and image segmentation. Simultaneously, it offers a convenient choice for researchers and practitioners to flexibly apply these pre-trained models in different scenarios.

Data structure

Usage

ImageNet V1

from datasets import load_dataset

backbones = load_dataset(
    "monetjoe/cv_backbones",
    name="default",
    split="train",
    cache_dir="./__pycache__",
)
for weights in backbones:
    print(weights)

ImageNet V2

from datasets import load_dataset

backbones = load_dataset(
    "monetjoe/cv_backbones",
    name="default",
    split="test",
    cache_dir="./__pycache__",
)
for weights in backbones:
    print(weights)

Maintenance

git clone git@hf.co:datasets/monetjoe/cv_backbones
cd cv_backbones

Update tool

<https://huggingface.co/spaces/monetjoe/cv_backbones>

Param counts of different backbones

IMAGENET1K_V1

IMAGENET1K_V2

Mirror

<https://www.modelscope.cn/datasets/monetjoe/cv_backbones>

References

• —<https://pytorch.org/vision/main/_modules>
• —<https://pytorch.org/vision/main/models.html>