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--- |
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license: mit |
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tags: |
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- vision |
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- image-segmentation |
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datasets: |
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- LEVIR-CD |
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--- |
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# AdaptFormer model fine-tuned on LEVIR-CD |
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AdaptFormer model fine-tuned on LEVIR-CD at resolution 512x512. It was introduced in the paper [AdaptFormer: An Adaptive Hierarchical Semantic Approach for Change Detection on Remote Sensing Images](https://ieeexplore.ieee.org/document/10497147) by Pang et al. and first released in [this repository](https://github.com/aigzhusmart/AdaptFormer). |
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## Model description |
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AdaptFormer, uniquely designed to adaptively interpret hierarchical semantics. Instead of a one-size-fits-all approach, it strategizes differently across three semantic depths: employing straightforward operations for shallow semantics, assimilating spatial data for medium semantics to emphasize detailed interregional changes, and integrating cascaded depthwise attention for in-depth semantics, focusing on high-level representations |
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Here is how to use this model to classify an image: |
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```python |
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from transformers import AutoImageProcessor, AutoModel |
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from PIL import Image |
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import requests |
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image_processor = AutoImageProcessor.from_pretrained("deepang/adaptformer-LEVIR-CD") |
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model = AutoModel.from_pretrained("deepang/adaptformer-LEVIR-CD") |
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image_A = Image.open(requests.get('https://raw.githubusercontent.com/aigzhusmart/AdaptFormer/main/figures/test_2_1_A.png', stream=True).raw) |
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image_B = Image.open(requests.get('https://raw.githubusercontent.com/aigzhusmart/AdaptFormer/main/figures/test_2_1_B.png', stream=True).raw) |
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label = Image.open(requests.get('https://raw.githubusercontent.com/aigzhusmart/AdaptFormer/main/figures/test_2_1_label.png', stream=True).raw) |
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inputs = preprocessor(images=(image_A, image_B), return_tensors="pt") |
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outputs = adaptfromer_model(**inputs) |
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logits = outputs.logits # shape (batch_size, num_labels, height, width) |
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pred = logits.argmax(dim=1)[0] |
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``` |
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### License |
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The license for this model can be found [here](https://github.com/aigzhusmart/AdaptFormer). |
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### BibTeX entry and citation info |
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```bibtex |
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@article{huang2024adaptformer, |
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title={AdaptFormer: An Adaptive Hierarchical Semantic Approach for Change Detection on Remote Sensing Images}, |
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author={Huang, Teng and Hong, Yile and Pang, Yan and Liang, Jiaming and Hong, Jie and Huang, Lin and Zhang, Yuan and Jia, Yan and Savi, Patrizia}, |
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journal={IEEE Transactions on Instrumentation and Measurement}, |
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year={2024}, |
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publisher={IEEE} |
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} |
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``` |
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