Garbage Dataset

Collection of images of garbages grouped into 10 classes (metal, glass, biological, paper, battery, trash, cardboard, shoes, clothes, and plastic). The number of files in respective classes is as follows:

- **Metal**: 994
- **Glass**: 3039
- **Biological**: 983
- **Paper**: 1650
- **Battery**: 944
- **Trash**: 772
- **Cardboard**: 1810
- **Shoes**: 1977
- **Clothes**: 5323
- **Plastic**: 1915

This dataset was also used in "[Managing Household Waste Through Transfer Learning](https://doi.org/10.53623/idwm.v4i1.408)" research paper.

# Feedbacks

Thank you for your interest in our waste dataset. Whether you have used the dataset or are considering its use, your feedback is crucial to help us understand your needs and improve the dataset. Please take a few minutes to share your thoughts and experiences through [this feedback form](https://sumn2u.typeform.com/to/DActRZpJ). Your input is greatly appreciated.

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We also welcome feedback and contributions to [our project](https://github.com/sumn2u/deep-waste-app) on GitHub. Your suggestions and collaboration can help us enhance the dataset and improve the model's performance. Let's work together to make a positive difference!

本数据集汇集了十类垃圾图像（金属、玻璃、生物、纸张、电池、废弃物、纸箱、鞋子、服装及塑料），各分类文件数量如下：

- **金属**：994
- **玻璃**：3039
- **生物**：983
- **纸张**：1650
- **电池**：944
- **废弃物**：772
- **纸箱**：1810
- **鞋子**：1977
- **服装**：5323
- **塑料**：1915

该数据集亦被应用于“[通过迁移学习管理家庭废弃物](https://doi.org/10.53623/idwm.v4i1.408)”研究论文中。

# 反馈

感谢您对我们废弃物数据集的关注。无论您已使用该数据集或正考虑使用，您的反馈对于我们理解您的需求并优化数据集至关重要。请您抽出几分钟时间，通过[此反馈表](https://sumn2u.typeform.com/to/DActRZpJ)分享您的想法和经验。您的宝贵意见将受到高度珍视。

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我们亦欢迎您在GitHub上[我们的项目](https://github.com/sumn2u/deep-waste-app)提供反馈和贡献。您的建议与合作将有助于我们完善数据集并提升模型性能。让我们携手共同为环境保护作出积极贡献！