visdrone
visdrone
Datasets
visdrone
File
visdrone
Use Case
visdrone
Description
Explore the Compact VisDrone Dataset, optimized from VisDrone2019 with merged classes for improved AI model performance in object detection, traffic analysis, and drone surveillance.
Description:
This dataset simplifies the VisDrone2019 dataset by merging classes into compact categories for better classification performance. Key mappings include Person (Pedestrian + People), Car (Car + Van), and Long Vehicle (Truck + Bus), while redundant classes like Bicycle, Tricycle, and Motor are removed. Ideal for drone-based object detection, traffic analysis, and surveillance AI models.
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This dataset is a refined version of the original VisDrone2019 dataset, featuring optimized class mappings to enhance classification accuracy. By merging and reclassifying the original dataset’s categories, it provides a more compact and focused representation, ideal for machine learning and computer vision tasks.
Original Class Mappings:
The original dataset included the following classes:
- 0: Pedestrian
- 1: People
- 2: Bicycle
- 3: Car
- 4: Van
- 5: Truck
- 6: Tricycle
- 7: Awning-Tricycle
- 8: Bus
- 9: Motor
New Class Mappings:
To improve performance and simplify analysis, the classes were restructured as follows:
- 0: Person (merged classes: Pedestrian [0] + People [1])
- 1: Car (merged classes: Car [3] + Van [4])
- 2: Long Vehicle (merged classes: Truck [5] + Bus [8])
This dataset is sourced from Kaggle.
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