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--- |
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datasets: |
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- detection-datasets/coco |
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license: gpl-3.0 |
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--- |
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# Introduction |
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This repository stores the model for YOLOv7, compatible with Kalray's neural network API. </br> |
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Please see www.github.com/kalray/kann-models-zoo for details and proper usage. </br> |
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# Contents |
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- ONNX: yolov7-tiny.optimized.onnx |
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# Lecture note reference |
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+ YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors, https://arxiv.org/abs/2207.02696 |
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# Repository or links references |
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- https://github.com/WongKinYiu/yolov7 |
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- config / weights: https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-tiny.pt |
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BibTeX entry and citation info |
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``` |
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@inproceedings{wang2023yolov7, |
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title={{YOLOv7}: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors}, |
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author={Wang, Chien-Yao and Bochkovskiy, Alexey and Liao, Hong-Yuan Mark}, |
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booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, |
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year={2023} |
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} |
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@article{wang2023designing, |
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title={Designing Network Design Strategies Through Gradient Path Analysis}, |
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author={Wang, Chien-Yao and Liao, Hong-Yuan Mark and Yeh, I-Hau}, |
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journal={Journal of Information Science and Engineering}, |
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year={2023} |
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} |
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``` |
