--- language: - en license: cc-by-nc-nd-4.0 task_categories: - image-to-image - object-detection tags: - code - legal dataset_info: - config_name: video_01 features: - name: id dtype: int32 - name: name dtype: string - name: image dtype: image - name: mask dtype: image - name: shapes sequence: - name: track_id dtype: uint32 - name: label dtype: class_label: names: '0': electric_scooter - name: type dtype: string - name: points sequence: sequence: float32 - name: rotation dtype: float32 - name: occluded dtype: uint8 - name: attributes sequence: - name: name dtype: string - name: text dtype: string splits: - name: train num_bytes: 9312 num_examples: 22 download_size: 8409013 dataset_size: 9312 - config_name: video_02 features: - name: id dtype: int32 - name: name dtype: string - name: image dtype: image - name: mask dtype: image - name: shapes sequence: - name: track_id dtype: uint32 - name: label dtype: class_label: names: '0': electric_scooter - name: type dtype: string - name: points sequence: sequence: float32 - name: rotation dtype: float32 - name: occluded dtype: uint8 - name: attributes sequence: - name: name dtype: string - name: text dtype: string splits: - name: train num_bytes: 10583 num_examples: 25 download_size: 48396353 dataset_size: 10583 - config_name: video_03 features: - name: id dtype: int32 - name: name dtype: string - name: image dtype: image - name: mask dtype: image - name: shapes sequence: - name: track_id dtype: uint32 - name: label dtype: class_label: names: '0': electric_scooter - name: type dtype: string - name: points sequence: sequence: float32 - name: rotation dtype: float32 - name: occluded dtype: uint8 - name: attributes sequence: - name: name dtype: string - name: text dtype: string splits: - name: train num_bytes: 8466 num_examples: 20 download_size: 13600750 dataset_size: 8466 --- # Electric Scooters Tracking - Object Detection dataset The dataset contains frames extracted from videos with people riding electric scooters. Each frame is accompanied by **bounding box** that specifically **tracks the electric scooter** in the image. # 💴 For Commercial Usage: To discuss your requirements, learn about the price and buy the dataset, leave a request on **[TrainingData](https://trainingdata.pro/datasets/object-tracking?utm_source=huggingface&utm_medium=cpc&utm_campaign=electric-scooters-tracking)** to buy the dataset This dataset can be useful for *object detection, motion tracking, behavior analysis, autonomous vehicle development and smart city*. ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F413e8303b798767f9c30450e0ad8b19b%2Fezgif.com-gif-maker.gif?generation=1695151025014061&alt=media) # Dataset structure The dataset consists of 3 folders with frames from the video with people riding an electric scooter. Each folder includes: - **images**: folder with original frames from the video, - **boxes**: visualized data labeling for the images in the previous folder, - **.csv file**: file with id and path of each frame in the "images" folder, - **annotations.xml**: contains coordinates of the bounding boxes and labels, created for the original frames # Data Format Each frame from `images` folder is accompanied by an XML-annotation in the `annotations.xml` file indicating the coordinates of the bounding boxes for electric scooter tracking. For each point, the x and y coordinates are provided. # Example of the XML-file ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Ff7bf13348e01369a8ccab9d5bf2acac6%2Fcarbon.png?generation=1695994913297718&alt=media) # Object tracking might be made in accordance with your requirements. # 💴 Buy the Dataset: This is just an example of the data. Leave a request on **[https://trainingdata.pro/datasets](https://trainingdata.pro/datasets/object-tracking?utm_source=huggingface&utm_medium=cpc&utm_campaign=electric-scooters-tracking)** to discuss your requirements, learn about the price and buy the dataset # **[TrainingData](https://trainingdata.pro/datasets/object-tracking?utm_source=huggingface&utm_medium=cpc&utm_campaign=electric-scooters-tracking)** provides high-quality data annotation tailored to your needs More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets** TrainingData's GitHub: **https://github.com/trainingdata-pro** *keywords: electric scooter gps, e-scooter, e-bike, navigation, vehicle tracking algorithm, vehicle tracking dataset, object detection, multiple-object vehicle tracking, vehicle image dataset, labeled web tracking dataset, image dataset, classification, computer vision, machine learning, cctv, camera detection, surveillance, security camera, security camera object detection, video-based monitoring, smart city, smart city development, smart city vision, smart city deep learning, smart city management*