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---
language:
- en
license: cc-by-nc-nd-4.0
task_categories:
- image-to-image
- object-detection
tags:
- electric scooter
- e-scooter
- vehicle tracking
- object detection
- multiple-object vehicle tracking
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:
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dtype: int32
- name: name
dtype: string
- name: image
dtype: image
- name: mask
dtype: image
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sequence:
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dtype: uint32
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dtype:
class_label:
names:
'0': electric_scooter
- name: type
dtype: string
- name: points
sequence:
sequence: float32
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dtype: float32
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- config_name: video_03
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dtype:
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'0': electric_scooter
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dtype: string
- name: points
sequence:
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dtype: float32
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dtype: string
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dtype: string
splits:
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num_bytes: 8466
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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 **[our website](https://unidata.pro/datasets/?utm_source=huggingface-td&utm_medium=referral&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*.
# 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
# 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 **[our website](https://unidata.pro/datasets/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=electric-scooters-tracking)** to discuss your requirements, learn about the price and buy the dataset
Leave a request on [our website](https://unidata.pro/datasets/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=electric-scooters-tracking) to discuss your requirements, learn about the price and buy the dataset.
## [Our Team](https://unidata.pro/datasets/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=electric-scooters-tracking) provides high-quality data annotation tailored to your needs
*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* |