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--- |
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language: |
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- en |
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license: cc-by-nc-nd-4.0 |
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task_categories: |
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- image-classification |
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- object-detection |
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tags: |
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- code |
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dataset_info: |
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features: |
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- name: id |
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dtype: int32 |
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- name: name |
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dtype: string |
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- name: image |
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dtype: image |
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- name: mask |
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dtype: image |
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- name: width |
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dtype: uint16 |
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- name: height |
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dtype: uint16 |
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- name: shapes |
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sequence: |
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- name: label |
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dtype: |
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class_label: |
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names: |
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'0': Miner |
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- name: type |
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dtype: string |
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- name: points |
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sequence: |
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sequence: float32 |
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- name: rotation |
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dtype: float32 |
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- name: occluded |
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dtype: uint8 |
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- name: attributes |
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sequence: |
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- name: name |
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dtype: string |
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- name: text |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 5907438 |
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num_examples: 8 |
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download_size: 5795853 |
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dataset_size: 5907438 |
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--- |
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# Miners Detection dataset |
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The dataset consists of of photos captured within various mines, focusing on **miners** engaged in their work. Each photo is annotated with bounding box detection of the miners, an attribute highlights whether each miner is sitting or standing in the photo. |
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The dataset's diverse applications such as computer vision, safety assessment and others make it a valuable resource for *researchers, employers, and policymakers in the mining industry*. |
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# Get the dataset |
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### This is just an example of the data |
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Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=miners-detection) to discuss your requirements, learn about the price and buy the dataset. |
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# Dataset structure |
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- **images** - contains of original images of miners |
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- **boxes** - includes bounding box labeling for the original images |
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- **annotations.xml** - contains coordinates of the bounding boxes and labels, created for the original photo |
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# Data Format |
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Each image from `images` folder is accompanied by an XML-annotation in the `annotations.xml` file indicating the coordinates of the bounding boxes for miners detection. For each point, the x and y coordinates are provided. The position of the miner is also provided by the attribute **is_sitting** (true, false). |
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# Example of XML file structure |
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.png?generation=1695040600108833&alt=media) |
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# Miners detection might be made in accordance with your requirements. |
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## [TrainingData](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=miners-detection) provides high-quality data annotation tailored to your needs |
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More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets** |
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TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets** |