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Duplicate from monetjoe/cv_backbones

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  1. .gitattributes +54 -0
  2. .gitignore +2 -0
  3. README.md +167 -0
  4. test.jsonl +24 -0
  5. train.jsonl +78 -0
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+ *.7z filter=lfs diff=lfs merge=lfs -text
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+ *.arrow filter=lfs diff=lfs merge=lfs -text
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+ *.ckpt filter=lfs diff=lfs merge=lfs -text
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+ *.lz4 filter=lfs diff=lfs merge=lfs -text
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+ *.mlmodel filter=lfs diff=lfs merge=lfs -text
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+ *.model filter=lfs diff=lfs merge=lfs -text
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+ *.onnx filter=lfs diff=lfs merge=lfs -text
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+ *.pickle filter=lfs diff=lfs merge=lfs -text
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+ *.pkl filter=lfs diff=lfs merge=lfs -text
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+ *.pt filter=lfs diff=lfs merge=lfs -text
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+ *.pth filter=lfs diff=lfs merge=lfs -text
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+ *.rar filter=lfs diff=lfs merge=lfs -text
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+ *.safetensors filter=lfs diff=lfs merge=lfs -text
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+ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+ *.tar.* filter=lfs diff=lfs merge=lfs -text
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+ *.tflite filter=lfs diff=lfs merge=lfs -text
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+ *.tgz filter=lfs diff=lfs merge=lfs -text
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+ *.wasm filter=lfs diff=lfs merge=lfs -text
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+ *.zst filter=lfs diff=lfs merge=lfs -text
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+ *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - uncompressed
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+ *.pcm filter=lfs diff=lfs merge=lfs -text
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+ *.sam filter=lfs diff=lfs merge=lfs -text
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+ *.raw filter=lfs diff=lfs merge=lfs -text
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+ # Audio files - compressed
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+ *.aac filter=lfs diff=lfs merge=lfs -text
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+ *.flac filter=lfs diff=lfs merge=lfs -text
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+ *.mp3 filter=lfs diff=lfs merge=lfs -text
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+ *.ogg filter=lfs diff=lfs merge=lfs -text
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+ *.wav filter=lfs diff=lfs merge=lfs -text
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+ # Image files - uncompressed
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+ *.bmp filter=lfs diff=lfs merge=lfs -text
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+ *.gif filter=lfs diff=lfs merge=lfs -text
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+ *.png filter=lfs diff=lfs merge=lfs -text
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+ *.tiff filter=lfs diff=lfs merge=lfs -text
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+ # Image files - compressed
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+ *.jpg filter=lfs diff=lfs merge=lfs -text
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+ *.jpeg filter=lfs diff=lfs merge=lfs -text
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+ *.webp filter=lfs diff=lfs merge=lfs -text
.gitignore ADDED
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+ rename.sh
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+ test.py
README.md ADDED
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+ ---
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+ license: mit
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+ task_categories:
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+ - image-classification
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+ - feature-extraction
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+ language:
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+ - en
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+ tags:
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+ - code
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+ pretty_name: Vi-Backbones
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+ size_categories:
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+ - n<1K
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+ ---
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+
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+ # Dataset Card for "monetjoe/cv_backbones"
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+ 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.
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+
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+ ## Data structure
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+ | ver | type | input_size | url |
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+ | :-----------: | :-----------: | :--------------: | :-------------------------------: |
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+ | backbone name | backbone type | input image size | url of pretrained model .pth file |
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+
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+ ## Usage
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+ ### ImageNet V1
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+ ```python
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+ from datasets import load_dataset
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+
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+ backbones = load_dataset("monetjoe/cv_backbones", name="default", split="train")
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+ for weights in backbones:
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+ print(weights)
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+ ```
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+
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+ ### ImageNet V2
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+ ```python
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+ from datasets import load_dataset
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+
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+ backbones = load_dataset("monetjoe/cv_backbones", name="default", split="test")
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+ for weights in backbones:
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+ print(weights)
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+ ```
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+
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+ ## Maintenance
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+ ```bash
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+ git clone git@hf.co:datasets/monetjoe/cv_backbones
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+ cd cv_backbones
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+ ```
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+
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+ ### Update tool
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+ <https://huggingface.co/spaces/monetjoe/cv_backbones>
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+
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+ ## Param counts of different backbones
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+ ### IMAGENET1K_V1
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+ | Backbone | Params(M) |
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+ | :----------------: | :-------: |
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+ | SqueezeNet1_0 | 1.2 |
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+ | SqueezeNet1_1 | 1.2 |
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+ | ShuffleNet_V2_X0_5 | 1.4 |
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+ | MNASNet0_5 | 2.2 |
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+ | ShuffleNet_V2_X1_0 | 2.3 |
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+ | MobileNet_V3_Small | 2.5 |
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+ | MNASNet0_75 | 3.2 |
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+ | MobileNet_V2 | 3.5 |
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+ | ShuffleNet_V2_X1_5 | 3.5 |
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+ | RegNet_Y_400MF | 4.3 |
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+ | MNASNet1_0 | 4.4 |
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+ | EfficientNet_B0 | 5.3 |
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+ | MobileNet_V3_Large | 5.5 |
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+ | RegNet_X_400MF | 5.5 |
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+ | MNASNet1_3 | 6.3 |
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+ | RegNet_Y_800MF | 6.4 |
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+ | GoogLeNet | 6.6 |
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+ | RegNet_X_800MF | 7.3 |
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+ | ShuffleNet_V2_X2_0 | 7.4 |
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+ | EfficientNet_B1 | 7.8 |
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+ | DenseNet121 | 8 |
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+ | EfficientNet_B2 | 9.1 |
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+ | RegNet_X_1_6GF | 9.2 |
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+ | RegNet_Y_1_6GF | 11.2 |
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+ | ResNet18 | 11.7 |
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+ | EfficientNet_B3 | 12.2 |
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+ | DenseNet169 | 14.1 |
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+ | RegNet_X_3_2GF | 15.3 |
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+ | EfficientNet_B4 | 19.3 |
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+ | RegNet_Y_3_2GF | 19.4 |
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+ | DenseNet201 | 20 |
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+ | EfficientNet_V2_S | 21.5 |
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+ | ResNet34 | 21.8 |
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+ | ResNeXt50_32X4D | 25 |
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+ | ResNet50 | 25.6 |
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+ | Inception_V3 | 27.2 |
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+ | Swin_T | 28.3 |
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+ | Swin_V2_T | 28.4 |
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+ | ConvNeXt_Tiny | 28.6 |
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+ | DenseNet161 | 28.7 |
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+ | EfficientNet_B5 | 30.4 |
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+ | MaxVit_T | 30.9 |
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+ | RegNet_Y_8GF | 39.4 |
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+ | RegNet_X_8GF | 39.6 |
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+ | EfficientNet_B6 | 43 |
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+ | ResNet101 | 44.5 |
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+ | Swin_S | 49.6 |
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+ | Swin_V2_S | 49.7 |
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+ | ConvNeXt_Small | 50.2 |
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+ | EfficientNet_V2_M | 54.1 |
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+ | RegNet_X_16GF | 54.3 |
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+ | ResNet152 | 60.2 |
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+ | AlexNet | 61.1 |
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+ | EfficientNet_B7 | 66.3 |
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+ | Wide_ResNet50_2 | 68.9 |
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+ | ResNeXt101_64X4D | 83.5 |
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+ | RegNet_Y_16GF | 83.6 |
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+ | ViT_B_16 | 86.6 |
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+ | Swin_B | 87.8 |
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+ | Swin_V2_B | 87.9 |
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+ | ViT_B_32 | 88.2 |
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+ | ConvNeXt_Base | 88.6 |
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+ | ResNeXt101_32X8D | 88.8 |
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+ | RegNet_X_32GF | 107.8 |
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+ | EfficientNet_V2_L | 118.5 |
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+ | Wide_ResNet101_2 | 126.9 |
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+ | VGG11_BN | 132.9 |
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+ | VGG11 | 132.9 |
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+ | VGG13 | 133 |
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+ | VGG13_BN | 133.1 |
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+ | VGG16_BN | 138.4 |
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+ | VGG16 | 138.4 |
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+ | VGG19_BN | 143.7 |
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+ | VGG19 | 143.7 |
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+ | RegNet_Y_32GF | 145 |
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+ | ConvNeXt_Large | 197.8 |
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+ | ViT_L_16 | 304.3 |
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+ | ViT_L_32 | 306.5 |
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+
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+ ### IMAGENET1K_V2
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+ | Backbone | Params(M) |
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+ | :----------------: | :-------: |
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+ | MobileNet_V2 | 3.5 |
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+ | RegNet_Y_400MF | 4.3 |
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+ | MobileNet_V3_Large | 5.5 |
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+ | RegNet_X_400MF | 5.5 |
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+ | RegNet_Y_800MF | 6.4 |
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+ | RegNet_X_800MF | 7.3 |
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+ | EfficientNet_B1 | 7.8 |
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+ | RegNet_X_1_6GF | 9.2 |
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+ | RegNet_Y_1_6GF | 11.2 |
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+ | RegNet_X_3_2GF | 15.3 |
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+ | RegNet_Y_3_2GF | 19.4 |
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+ | ResNeXt50_32X4D | 25 |
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+ | ResNet50 | 25.6 |
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+ | RegNet_Y_8GF | 39.4 |
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+ | RegNet_X_8GF | 39.6 |
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+ | ResNet101 | 44.5 |
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+ | RegNet_X_16GF | 54.3 |
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+ | ResNet152 | 60.2 |
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+ | Wide_ResNet50_2 | 68.9 |
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+ | RegNet_Y_16GF | 83.6 |
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+ | ResNeXt101_32X8D | 88.8 |
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+ | RegNet_X_32GF | 107.8 |
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+ | Wide_ResNet101_2 | 126.9 |
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+ | RegNet_Y_32GF | 145 |
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+
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+ ## Mirror
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+ <https://www.modelscope.cn/datasets/monetjoe/cv_backbones>
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+
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+ ## References
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+ - <https://pytorch.org/vision/main/_modules>
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+ - <https://pytorch.org/vision/main/models.html>
test.jsonl ADDED
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+ {"ver": "efficientnet_b1", "type": "efficientnet", "input_size": 240, "url": "https://download.pytorch.org/models/efficientnet_b1-c27df63c.pth"}
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+ {"ver": "mobilenet_v2", "type": "mobilenet", "input_size": 224, "url": "https://download.pytorch.org/models/mobilenet_v2-7ebf99e0.pth"}
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+ {"ver": "mobilenet_v3_large", "type": "mobilenet", "input_size": 224, "url": "https://download.pytorch.org/models/mobilenet_v3_large-5c1a4163.pth"}
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+ {"ver": "regnet_y_400mf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_400mf-e6988f5f.pth"}
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+ {"ver": "regnet_y_800mf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_800mf-58fc7688.pth"}
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+ {"ver": "regnet_y_1_6gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_1_6gf-0d7bc02a.pth"}
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+ {"ver": "regnet_y_3_2gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_3_2gf-9180c971.pth"}
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+ {"ver": "regnet_y_8gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_8gf-dc2b1b54.pth"}
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+ {"ver": "regnet_y_16gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_16gf-3e4a00f9.pth"}
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+ {"ver": "regnet_y_32gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_32gf-8db6d4b5.pth"}
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+ {"ver": "regnet_x_400mf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_400mf-62229a5f.pth"}
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+ {"ver": "regnet_x_800mf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_800mf-94a99ebd.pth"}
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+ {"ver": "regnet_x_1_6gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_1_6gf-a12f2b72.pth"}
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+ {"ver": "regnet_x_3_2gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_3_2gf-7071aa85.pth"}
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+ {"ver": "regnet_x_8gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_8gf-2b70d774.pth"}
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+ {"ver": "regnet_x_16gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_16gf-ba3796d7.pth"}
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+ {"ver": "regnet_x_32gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_32gf-6eb8fdc6.pth"}
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+ {"ver": "resnet50", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnet50-11ad3fa6.pth"}
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+ {"ver": "resnet101", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnet101-cd907fc2.pth"}
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+ {"ver": "resnet152", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnet152-f82ba261.pth"}
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+ {"ver": "resnext50_32x4d", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnext50_32x4d-1a0047aa.pth"}
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+ {"ver": "resnext101_32x8d", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnext101_32x8d-110c445d.pth"}
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+ {"ver": "wide_resnet50_2", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/wide_resnet50_2-9ba9bcbe.pth"}
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+ {"ver": "wide_resnet101_2", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/wide_resnet101_2-d733dc28.pth"}
train.jsonl ADDED
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+ {"ver": "alexnet", "type": "alexnet", "input_size": 224, "url": "https://download.pytorch.org/models/alexnet-owt-7be5be79.pth"}
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+ {"ver": "convnext_tiny", "type": "convnext", "input_size": 224, "url": "https://download.pytorch.org/models/convnext_tiny-983f1562.pth"}
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+ {"ver": "convnext_small", "type": "convnext", "input_size": 224, "url": "https://download.pytorch.org/models/convnext_small-0c510722.pth"}
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+ {"ver": "convnext_base", "type": "convnext", "input_size": 224, "url": "https://download.pytorch.org/models/convnext_base-6075fbad.pth"}
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+ {"ver": "convnext_large", "type": "convnext", "input_size": 224, "url": "https://download.pytorch.org/models/convnext_large-ea097f82.pth"}
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+ {"ver": "densenet121", "type": "densenet", "input_size": 224, "url": "https://download.pytorch.org/models/densenet121-a639ec97.pth"}
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+ {"ver": "densenet161", "type": "densenet", "input_size": 224, "url": "https://download.pytorch.org/models/densenet161-8d451a50.pth"}
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+ {"ver": "densenet169", "type": "densenet", "input_size": 224, "url": "https://download.pytorch.org/models/densenet169-b2777c0a.pth"}
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+ {"ver": "densenet201", "type": "densenet", "input_size": 224, "url": "https://download.pytorch.org/models/densenet201-c1103571.pth"}
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+ {"ver": "efficientnet_b0", "type": "efficientnet", "input_size": 224, "url": "https://download.pytorch.org/models/efficientnet_b0_rwightman-7f5810bc.pth"}
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+ {"ver": "efficientnet_b1", "type": "efficientnet", "input_size": 240, "url": "https://download.pytorch.org/models/efficientnet_b1_rwightman-bac287d4.pth"}
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+ {"ver": "efficientnet_b2", "type": "efficientnet", "input_size": 288, "url": "https://download.pytorch.org/models/efficientnet_b2_rwightman-c35c1473.pth"}
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+ {"ver": "efficientnet_b3", "type": "efficientnet", "input_size": 300, "url": "https://download.pytorch.org/models/efficientnet_b3_rwightman-b3899882.pth"}
14
+ {"ver": "efficientnet_b4", "type": "efficientnet", "input_size": 380, "url": "https://download.pytorch.org/models/efficientnet_b4_rwightman-23ab8bcd.pth"}
15
+ {"ver": "efficientnet_b5", "type": "efficientnet", "input_size": 456, "url": "https://download.pytorch.org/models/efficientnet_b5_lukemelas-1a07897c.pth"}
16
+ {"ver": "efficientnet_b6", "type": "efficientnet", "input_size": 528, "url": "https://download.pytorch.org/models/efficientnet_b6_lukemelas-24a108a5.pth"}
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+ {"ver": "efficientnet_b7", "type": "efficientnet", "input_size": 600, "url": "https://download.pytorch.org/models/efficientnet_b7_lukemelas-c5b4e57e.pth"}
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+ {"ver": "efficientnet_v2_s", "type": "efficientnet", "input_size": 384, "url": "https://download.pytorch.org/models/efficientnet_v2_s-dd5fe13b.pth"}
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+ {"ver": "efficientnet_v2_m", "type": "efficientnet", "input_size": 480, "url": "https://download.pytorch.org/models/efficientnet_v2_m-dc08266a.pth"}
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+ {"ver": "efficientnet_v2_l", "type": "efficientnet", "input_size": 480, "url": "https://download.pytorch.org/models/efficientnet_v2_l-59c71312.pth"}
21
+ {"ver": "googlenet", "type": "googlenet", "input_size": 224, "url": "https://download.pytorch.org/models/googlenet-1378be20.pth"}
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+ {"ver": "inception_v3", "type": "googlenet", "input_size": 299, "url": "https://download.pytorch.org/models/inception_v3_google-0cc3c7bd.pth"}
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+ {"ver": "maxvit_t", "type": "maxvit", "input_size": 224, "url": "https://download.pytorch.org/models/maxvit_t-bc5ab103.pth"}
24
+ {"ver": "mnasnet0_5", "type": "mnasnet", "input_size": 224, "url": "https://download.pytorch.org/models/mnasnet0.5_top1_67.823-3ffadce67e.pth"}
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+ {"ver": "mnasnet0_75", "type": "mnasnet", "input_size": 224, "url": "https://download.pytorch.org/models/mnasnet0_75-7090bc5f.pth"}
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+ {"ver": "mnasnet1_0", "type": "mnasnet", "input_size": 224, "url": "https://download.pytorch.org/models/mnasnet1.0_top1_73.512-f206786ef8.pth"}
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+ {"ver": "mnasnet1_3", "type": "mnasnet", "input_size": 224, "url": "https://download.pytorch.org/models/mnasnet1_3-a4c69d6f.pth"}
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+ {"ver": "mobilenet_v2", "type": "mobilenet", "input_size": 224, "url": "https://download.pytorch.org/models/mobilenet_v2-b0353104.pth"}
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+ {"ver": "mobilenet_v3_large", "type": "mobilenet", "input_size": 224, "url": "https://download.pytorch.org/models/mobilenet_v3_large-8738ca79.pth"}
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+ {"ver": "mobilenet_v3_small", "type": "mobilenet", "input_size": 224, "url": "https://download.pytorch.org/models/mobilenet_v3_small-047dcff4.pth"}
31
+ {"ver": "regnet_y_400mf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_400mf-c65dace8.pth"}
32
+ {"ver": "regnet_y_800mf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_800mf-1b27b58c.pth"}
33
+ {"ver": "regnet_y_1_6gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_1_6gf-b11a554e.pth"}
34
+ {"ver": "regnet_y_3_2gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_3_2gf-b5a9779c.pth"}
35
+ {"ver": "regnet_y_8gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_8gf-d0d0e4a8.pth"}
36
+ {"ver": "regnet_y_16gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_16gf-9e6ed7dd.pth"}
37
+ {"ver": "regnet_y_32gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_y_32gf-4dee3f7a.pth"}
38
+ {"ver": "regnet_x_400mf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_400mf-adf1edd5.pth"}
39
+ {"ver": "regnet_x_800mf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_800mf-ad17e45c.pth"}
40
+ {"ver": "regnet_x_1_6gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_1_6gf-e3633e7f.pth"}
41
+ {"ver": "regnet_x_3_2gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_3_2gf-f342aeae.pth"}
42
+ {"ver": "regnet_x_8gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_8gf-03ceed89.pth"}
43
+ {"ver": "regnet_x_16gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_16gf-2007eb11.pth"}
44
+ {"ver": "regnet_x_32gf", "type": "regnet", "input_size": 224, "url": "https://download.pytorch.org/models/regnet_x_32gf-9d47f8d0.pth"}
45
+ {"ver": "resnet18", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnet18-f37072fd.pth"}
46
+ {"ver": "resnet34", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnet34-b627a593.pth"}
47
+ {"ver": "resnet50", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnet50-0676ba61.pth"}
48
+ {"ver": "resnet101", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnet101-63fe2227.pth"}
49
+ {"ver": "resnet152", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnet152-394f9c45.pth"}
50
+ {"ver": "resnext50_32x4d", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnext50_32x4d-7cdf4587.pth"}
51
+ {"ver": "resnext101_32x8d", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnext101_32x8d-8ba56ff5.pth"}
52
+ {"ver": "resnext101_64x4d", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/resnext101_64x4d-173b62eb.pth"}
53
+ {"ver": "wide_resnet50_2", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/wide_resnet50_2-95faca4d.pth"}
54
+ {"ver": "wide_resnet101_2", "type": "resnet", "input_size": 224, "url": "https://download.pytorch.org/models/wide_resnet101_2-32ee1156.pth"}
55
+ {"ver": "shufflenet_v2_x0_5", "type": "shufflenet", "input_size": 224, "url": "https://download.pytorch.org/models/shufflenetv2_x0.5-f707e7126e.pth"}
56
+ {"ver": "shufflenet_v2_x1_0", "type": "shufflenet", "input_size": 224, "url": "https://download.pytorch.org/models/shufflenetv2_x1-5666bf0f80.pth"}
57
+ {"ver": "shufflenet_v2_x1_5", "type": "shufflenet", "input_size": 224, "url": "https://download.pytorch.org/models/shufflenetv2_x1_5-3c479a10.pth"}
58
+ {"ver": "shufflenet_v2_x2_0", "type": "shufflenet", "input_size": 224, "url": "https://download.pytorch.org/models/shufflenetv2_x2_0-8be3c8ee.pth"}
59
+ {"ver": "squeezenet1_0", "type": "squeezenet", "input_size": 224, "url": "https://download.pytorch.org/models/squeezenet1_0-b66bff10.pth"}
60
+ {"ver": "squeezenet1_1", "type": "squeezenet", "input_size": 224, "url": "https://download.pytorch.org/models/squeezenet1_1-b8a52dc0.pth"}
61
+ {"ver": "swin_t", "type": "swin_transformer", "input_size": 224, "url": "https://download.pytorch.org/models/swin_t-704ceda3.pth"}
62
+ {"ver": "swin_s", "type": "swin_transformer", "input_size": 224, "url": "https://download.pytorch.org/models/swin_s-5e29d889.pth"}
63
+ {"ver": "swin_b", "type": "swin_transformer", "input_size": 224, "url": "https://download.pytorch.org/models/swin_b-68c6b09e.pth"}
64
+ {"ver": "swin_v2_t", "type": "swin_transformer", "input_size": 256, "url": "https://download.pytorch.org/models/swin_v2_t-b137f0e2.pth"}
65
+ {"ver": "swin_v2_s", "type": "swin_transformer", "input_size": 256, "url": "https://download.pytorch.org/models/swin_v2_s-637d8ceb.pth"}
66
+ {"ver": "swin_v2_b", "type": "swin_transformer", "input_size": 256, "url": "https://download.pytorch.org/models/swin_v2_b-781e5279.pth"}
67
+ {"ver": "vgg11", "type": "vgg", "input_size": 224, "url": "https://download.pytorch.org/models/vgg11-8a719046.pth"}
68
+ {"ver": "vgg11_bn", "type": "vgg", "input_size": 224, "url": "https://download.pytorch.org/models/vgg11_bn-6002323d.pth"}
69
+ {"ver": "vgg13", "type": "vgg", "input_size": 224, "url": "https://download.pytorch.org/models/vgg13-19584684.pth"}
70
+ {"ver": "vgg13_bn", "type": "vgg", "input_size": 224, "url": "https://download.pytorch.org/models/vgg13_bn-abd245e5.pth"}
71
+ {"ver": "vgg16", "type": "vgg", "input_size": 224, "url": "https://download.pytorch.org/models/vgg16-397923af.pth"}
72
+ {"ver": "vgg16_bn", "type": "vgg", "input_size": 224, "url": "https://download.pytorch.org/models/vgg16_bn-6c64b313.pth"}
73
+ {"ver": "vgg19", "type": "vgg", "input_size": 224, "url": "https://download.pytorch.org/models/vgg19-dcbb9e9d.pth"}
74
+ {"ver": "vgg19_bn", "type": "vgg", "input_size": 224, "url": "https://download.pytorch.org/models/vgg19_bn-c79401a0.pth"}
75
+ {"ver": "vit_b_16", "type": "vit", "input_size": 224, "url": "https://download.pytorch.org/models/vit_b_16-c867db91.pth"}
76
+ {"ver": "vit_b_32", "type": "vit", "input_size": 224, "url": "https://download.pytorch.org/models/vit_b_32-d86f8d99.pth"}
77
+ {"ver": "vit_l_16", "type": "vit", "input_size": 224, "url": "https://download.pytorch.org/models/vit_l_16-852ce7e3.pth"}
78
+ {"ver": "vit_l_32", "type": "vit", "input_size": 224, "url": "https://download.pytorch.org/models/vit_l_32-c7638314.pth"}