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--- |
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license_name: server-side-public-license |
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license_link: https://www.mongodb.com/licensing/server-side-public-license |
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tags: |
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- fashion |
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- cloth-retrieval |
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- e-commerce |
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- segmentation |
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datasets: |
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- rizavelioglu/fashionfail |
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- detection-datasets/fashionpedia |
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pipeline_tag: object-detection |
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--- |
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## Facere |
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The models proposed in the paper ["FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation"](https://arxiv.org/abs/2404.08582) |
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Also, check out the [Project Page](https://rizavelioglu.github.io/fashionfail/). |
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## Usage |
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```python |
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from torchvision.io import read_image |
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from torchvision.models.detection import MaskRCNN_ResNet50_FPN_Weights |
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from huggingface_hub import hf_hub_download |
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path_onnx = hf_hub_download( |
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repo_id="rizavelioglu/fashionfail", |
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filename="facere_base.onnx", # or "facere_plus.onnx" |
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) |
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# Load pre-trained model transformations. |
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weights = MaskRCNN_ResNet50_FPN_Weights.DEFAULT |
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transforms = weights.transforms() |
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# Load image and apply original transformation to the image. |
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img = read_image("path/to/image") |
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img_transformed = transforms(img) |
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# Create an inference session. |
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ort_session = onnxruntime.InferenceSession( |
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path_onnx, providers=["CUDAExecutionProvider", "CPUExecutionProvider"] |
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) |
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# Run inference on the input. |
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ort_inputs = { |
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ort_session.get_inputs()[0].name: img_transformed.unsqueeze(dim=0).numpy() |
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} |
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ort_outs = ort_session.run(None, ort_inputs) |
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# Parse the model output. |
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boxes, labels, scores, masks = ort_outs |
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``` |
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> Check out the demo code on [HuggingFace Spaces][ff-hf_spaces] for visualizing the output. |
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> Also, check out [FashionFail's GitHub repository](https://github.com/rizavelioglu/fashionfail) to get more information on |
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> training, inference, and evaluation. |
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### License |
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TL;DR: Not available for commercial use, unless the FULL source code is shared! \ |
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This project is intended solely for academic research. No commercial benefits are derived from it. |
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Models are licensed under [Server Side Public License (SSPL)](https://www.mongodb.com/legal/licensing/server-side-public-license) |
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### Citation |
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If you find this repository useful in your research, please consider giving a star ⭐ and a citation: |
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``` |
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@inproceedings{velioglu2024fashionfail, |
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author = {Velioglu, Riza and Chan, Robin and Hammer, Barbara}, |
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title = {FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation}, |
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journal = {IJCNN}, |
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eprint = {2404.08582}, |
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year = {2024}, |
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} |
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``` |
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[ff-hf_spaces]: https://huggingface.co/spaces/rizavelioglu/fashionfail |
