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.gitattributes

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README.md

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+---
+license: cc-by-nc-nd-4.0
+task_categories:
+- object-detection
+- image-classification
+tags:
+- garbage
+- image
+- smart city
+- computer vision
+- environment
+size_categories:
+- 1K<n<10K
+---
+# Outdoor Garbage - Smart Cities Dataset
+
+Dataset comprises **5,000+** images of trash cans captured in various outdoor environments at different times of day and under diverse weather conditions. This extensive collection is designed for research in **waste classification** and **detection methods**, researchers can advance their capabilities in **deep learning** and **machine learning** applications, specifically in the areas of **image recognition** and **instance segmentation**.
+
+By utilizing this dataset, researchers can enhance **recommendation systems**, optimize processes, and automate the operations of community services in **smart cities**.  - **[Get the data](https://unidata.pro/datasets/outdoor-garbage/?utm_source=huggingface&utm_medium=referral&utm_campaign=outdoor-garbage)**
+# Example of the data
+![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2Fe69b1fb71e20bdb551691cf67106b7e8%2FFrame%20182%20(1).png?generation=1734355735483445&alt=media)
+Each image in the dataset is accompanied by an XML annotation that provides detailed information about the types of trash bins and their respective capacities: full, empty, or scattered. The dataset is particularly valuable for developing and testing segmentation models and detection performances in real-world scenarios.
+
+# Frequently Asked Questions
+
+## Who can benefit from this outdoor garbage dataset?
+
+This dataset can benefit computer vision researchers, smart-city developers, waste-management companies, and teams building automated garbage collection systems. It is especially relevant for projects that need to determine whether garbage containers are empty, full, or surrounded by scattered waste.
+
+## Can the dataset support automated garbage collection systems?
+
+Yes. The capacity labels can provide a useful visual signal for collection scheduling. A computer vision model could analyze images from cameras or mobile devices and identify containers that are full or have waste scattered around them.
+
+## Can the data be used for smart-city research?
+
+Yes. Visual monitoring of garbage containers is a relevant component of smart-city infrastructure. A trained model could potentially provide information about container status and help prioritize collection activities.
+
+# 💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at [https://unidata.pro](https://unidata.pro/datasets/outdoor-garbage/?utm_source=huggingface&utm_medium=referral&utm_campaign=outdoor-garbage) to discuss your requirements and pricing options.
+
+The dataset supports various image classification and object detection tasks, enabling researchers and developers to enhance their understanding of waste management systems and improve litter detection technologies.
+# 🌐 [UniData](https://unidata.pro/datasets/outdoor-garbage/?utm_source=huggingface&utm_medium=referral&utm_campaign=outdoor-garbage) provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects 

annotations.xml

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