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Dogs Video - Object Detection Dataset
The dataset contains frames extracted from videos with dogs on the streets. Each frame is accompanied by bounding box that specifically tracks the dog 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
The dataset provides a valuable resource for advancing computer vision tasks, enabling the development of more accurate and effective solutions for monitoring and understanding dog behavior in urban settings.
Dataset structure
The dataset consists of 3 folders with frames from the video with dogs on the streets. 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, created for the original frames
💴 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
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 dogs tracking. For each point, the x and y coordinates are provided.
Example of the XML-file
.png?generation=1695994709378514&alt=media)
Object tracking might be made in accordance with your requirements.
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-datamarket/TrainingData_All_datasets
keywords: object movements, dogs behavoir, pets object detection, motion tracking, domestic dogs, stray dogs, object detection, multiple-object tracking, image dataset, labeled web tracking dataset, 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, classification, image recognition
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