swin-tiny-patch4-window7-224¶

Use Case and High-Level Description¶

The swin-tiny-patch4-window7-224 model is a tiny version of the Swin Transformer image classification models pre-trained on ImageNet dataset. Swin Transformer is Hierarchical Vision Transformer whose representation is computed with shifted windows. Each patch is treated as a token with size of 4 and its feature is set as a concatenation of the raw pixel RGB values. The model has 7 patches in each window. Stages of tiny version of model have 2, 2, 6, 2 layers respectively. Number of channels of the hidden layers in the first stage for tiny variant is 96.

More details provided in the paper and repository.

Specification¶

Metric	Value
Type	Classification
GFlops	9.0280
MParams	28.8173
Source framework	PyTorch*

Accuracy¶

Metric	Value
Top 1	81.38%
Top 5	95.51%

Input¶

Original Model¶

Image, name: input, shape: 1, 3, 224, 224, format: B, C, H, W, where:

B - batch size
C - number of channels
H - image height
W - image width

Expected color order: RGB. Mean values - [123.675, 116.28, 103.53], scale values - [58.395, 57.12, 57.375].

Converted Model¶

Image, name: input, shape: 1, 3, 224, 224, format: B, C, H, W, where:

B - batch size
C - number of channels
H - image height
W - image width

Expected color order: BGR.

Output¶

Original Model¶

Object classifier according to ImageNet classes, name: probs, shape: 1, 1000, output data format is B, C, where:

B - batch size
C - predicted probabilities for each class in [0, 1] range

Converted Model¶

Object classifier according to ImageNet classes, name: probs, shape: 1, 1000, output data format is B, C, where:

B - batch size
C - predicted probabilities for each class in [0, 1] range

Download a Model and Convert it into OpenVINO™ IR Format¶

You can download models and if necessary convert them into OpenVINO™ IR format using the Model Downloader and other automation tools as shown in the examples below.

An example of using the Model Downloader:

omz_downloader --name <model_name>

An example of using the Model Converter:

omz_converter --name <model_name>

Demo usage¶

The model can be used in the following demos provided by the Open Model Zoo to show its capabilities:

Legal Information¶

The original model is distributed under the Apache License, Version 2.0. A copy of the license is provided in <omz_dir>/models/public/licenses/APACHE-2.0-PyTorch-Image-Models.txt.

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