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 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 https://trainingdata.pro/datasets to discuss your requirements, learn about the price and buy the dataset
TrainingData 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
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