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  1. .gitattributes +1 -0
  2. README.md +38 -0
  3. model/Screw_Best_Model.pth +3 -0
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  ---
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  license: cc-by-nc-4.0
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: cc-by-nc-4.0
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+ base_model:
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+ - Ultralytics/YOLOv8
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+ pipeline_tag: image-segmentation
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+ datasets:
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+ - industoai/PackDet
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+ tags:
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+ - object-segmentation
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+ - YOLO
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+ - Package-Detection
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+ library_name: pytorch
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  ---
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+
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+ # Description
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+ This model is the pretrained model for few shot deep approach used for counting screws and nuts in [ScrewCount](https://huggingface.co/datasets/industoai/ScrewCount).
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+
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+ ## Code
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+ The complete code can be found [here](https://github.com/industoai/ScrewCount).
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+
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+
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+ ## License
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+ This model is licensed under the Attribution–NonCommercial 4.0 International License (CC BY-NC 4.0).
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+
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+ ## Citation
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+ If you find this model useful, please consider citing the following paper:
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+ ```
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+ @conference{visapp26,
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+ author={Farnaz Delirie and Afshin Dini and Amirmasoud Molaei and Leila Sadeghi},
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+ title={ScrewCount: A Dataset and Benchmark for Exemplar Efficiency and Text-Guided Few-Shot Object Counting},
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+ booktitle={Proceedings of the 21st International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP},
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+ year={2026},
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+ pages={306-313},
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+ publisher={SciTePress},
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+ organization={INSTICC},
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+ doi={10.5220/0014236300004084},
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+ isbn={978-989-758-804-4},
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+ issn={2184-4321},
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+ }
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+ ```
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+
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+ size 3048438