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README.md
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license: cc-by-nc-nd-4.0
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---
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---
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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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language:
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- en
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tags:
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- code
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- finance
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---
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# Pose Estimation
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The dataset is primarly intended to dentify and predict the positions of major joints of a human body in an image. It consists of people's photographs with body part labeled with keypoints.
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# Get the Dataset
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This is just an example of the data. If you need access to the entire dataset, contact us via **[sales@trainingdata.pro](mailto:sales@trainingdata.pro)** or leave a request on **[https://trainingdata.pro/data-market](https://trainingdata.pro/data-market)**
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# Data Format
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Each image from `EP` folder is accompanied by an XML-annotation in the `annotations.xml` file indicating the coordinates of the key points. For each point, the x and y coordinates are provided, and there is a `Presumed_Location` attribute, indicating whether the point is presumed or accurately defined.
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# Example of XML file structure
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.png?generation=1684358333663868&alt=media)
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# Labeled body parts
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Each keypoint is ordered and corresponds to the concrete part of the body:
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0. **Nose**
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1. **Neck**
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2. **Right shoulder**
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3. **Right elbow**
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4. **Right wrist**
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5. **Left shoulder**
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6. **Left elbow**
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7. **Left wrist**
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8. **Right hip**
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9. **Right knee**
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10. **Right foot**
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11. **Left hip**
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12. **Left knee**
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13. **Left foot**
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14. **Right eye**
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15. **Left eye**
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16. **Right ear**
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17. **Left ear**
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# Keypoint annotation is made in accordance with your requirements.
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## **[TrainingData](https://trainingdata.pro/data-market)** 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-pro**
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