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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-segmentation |
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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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dataset_info: |
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features: |
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- name: image_id |
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dtype: int32 |
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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: annotations |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 614230158 |
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num_examples: 100 |
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download_size: 580108296 |
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dataset_size: 614230158 |
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--- |
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# Cars Tracking |
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The collection of overhead video frames, capturing various types of vehicles traversing a roadway. The dataset inculdes light vehicles (cars) and heavy vehicles (minivan). |
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# Get the Dataset |
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### This is just an example of the data |
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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?utm_source=huggingface)** to discuss your requirements, learn about the price and buy the dataset |
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# Data Format |
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Each video frame from `images` folder is paired with an `annotations.xml` file that meticulously defines the tracking of each vehicle using polygons. |
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These annotations not only specify the location and path of each vehicle but also differentiate between the vehicle classes: |
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- cars, |
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- minivans. |
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The data labeling is visualized in the `boxes` folder. |
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# Example of the XML-file |
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# Object tracking is made in accordance with your requirements. |
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## **[TrainingData](https://trainingdata.pro/data-market?utm_source=huggingface)** 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** |
