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--- |
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license: apache-2.0 |
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tags: |
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- vision |
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- image-classification |
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datasets: |
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- imagenet-1k |
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widget: |
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/tiger.jpg |
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example_title: Tiger |
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/teapot.jpg |
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example_title: Teapot |
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- src: https://huggingface.co/datasets/mishig/sample_images/resolve/main/palace.jpg |
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example_title: Palace |
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--- |
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# ResNet |
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ResNet model trained on imagenet-1k. It was introduced in the paper [Deep Residual Learning for Image Recognition](https://arxiv.org/abs/1512.03385) and first released in [this repository](https://github.com/KaimingHe/deep-residual-networks). |
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Disclaimer: The team releasing ResNet did not write a model card for this model so this model card has been written by the Hugging Face team. |
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## Model description |
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ResNet introduced residual connections, they allow to train networks with an unseen number of layers (up to 1000). ResNet won the 2015 ILSVRC & COCO competition, one important milestone in deep computer vision. |
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## Intended uses & limitations |
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You can use the raw model for image classification. See the [model hub](https://huggingface.co/models?search=resnet) to look for |
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fine-tuned versions on a task that interests you. |
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### How to use |
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Here is how to use this model: |
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```python |
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>>> from transformers import AutoImageProcessor, AutoModelForImageClassification |
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>>> import torch |
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>>> from datasets import load_dataset |
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>>> dataset = load_dataset("huggingface/cats-image") |
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>>> image = dataset["test"]["image"][0] |
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>>> image_processor = AutoImageProcessor.from_pretrained("microsoft/resnet-18") |
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>>> model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-18") |
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>>> inputs = image_processor(image, return_tensors="pt") |
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>>> with torch.no_grad(): |
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... logits = model(**inputs).logits |
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>>> # model predicts one of the 1000 ImageNet classes |
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>>> predicted_label = logits.argmax(-1).item() |
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>>> print(model.config.id2label[predicted_label]) |
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tiger cat |
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``` |
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For more code examples, we refer to the [documentation](https://huggingface.co/docs/transformers/master/en/model_doc/resnet). |
