Fruits by YOLO - Fruits Detection

Fruits by YOLO - Fruits Detection


Fruits by YOLO - Fruits Detection


Fruits by YOLO

Use Case

Computer Vision


Fruits by YOLO Image Dataset

Fruits by YOLO - Fruits Detection

About Dataset - Fruit Detection

The dataset includes Fruit Detection 2974 images.

Fruits are annotated in Multi-Class Classification format.

Explore the realm of fruits detection with our comprehensive YOLO Fruits Detection Dataset at Globose Technology Solutions. This dataset is specially curated to enhance machine learning models focused on accurately identifying and classifying various types of fruits in real-time. Whether you’re a researcher, a tech enthusiast, or a professional in the agricultural sector, our dataset provides the essential data needed for robust algorithms.

At, we understand the importance of high-quality, precise data for developing effective AI solutions. Our YOLO Dataset features a diverse range of fruit images captured under different conditions, ensuring versatility and adaptability of your models. Each image is meticulously annotated to provide not only the fruit type but also precise bounding box information for better object localization.

The following pre-processing was applied to each image:

Auto-orientation of pixel data (with EXIF-orientation stripping)
Resize to 640×640 (Stretch)

The following augmentation was applied to create 3 versions of each source image:

  • 50% probability of horizontal flip
  • 50% probability of vertical flip
  • Random rotation of between -15 and +15 degrees
  • Random shear of between -15° to +15° horizontally and -15° to +15° vertically
  • Random Gaussian blur of between 0 and 3.5 pixels

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