Dogs and Cats Breed Classifier

Dogs and Cats Breed Classifier

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Dogs and Cats Breed Classifier

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Dogs and Cats Breed Classifier

Use Case

Dogs and Cats Breed Classifier

Description

The Dogs and Cats Breed Classification Dataset by GTS provides pre-processed images for breed classification, detection, and fine-grained tasks with data augmentation and pre-split sets.

Dogs and Cats Breed Classifier

Description:

The Dogs and Cats Breed Classification Dataset by GTS offers pre-processed, annotated images for classifying and detecting dog and cat breeds. With data augmentation and a ready-to-use train-validation-test split, it’s ideal for image classification, object detection, and fine-grained classification tasks.

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The Dogs and Cats Breed Classification Dataset by Globose Technology Solutions (GTS) is designed to help with image classification and detection tasks, specifically aimed at identifying and categorizing various dog and cat breeds. This diverse dataset is well-organized into folders by breed, making it a perfect resource for developing and testing machine learning models.

Key Features

  • Pre-processed Data: All images in the dataset are pre-processed and resized to 224×224 pixels, ensuring faster model training and smoother processing.

  • Data Augmentation: To improve model performance and generalization, the dataset includes a range of data augmentation techniques:

    • 90-degree rotations (both clockwise and counter-clockwise)
    • Exposure adjustments (from -10% to +10%)
    • Blurring (up to 1.7 pixels)
  • Train-Validation-Test Split: The dataset is already split into training (80%), validation (12%), and testing (8%) sets. This division streamlines the process of model development, evaluation, and fine-tuning.

Potential Use Cases

  • Image Classification: This dataset enables you to build models that can accurately classify dog and cat breeds based on visual features. It’s useful for applications like pet identification and breed categorization.

  • Object Detection: In addition to classification, you can use the dataset to develop models that can detect and locate individual dogs and cats within images.

  • Fine-grained Classification: For more challenging tasks, such as distinguishing between similar breeds, this dataset helps create models that can identify subtle differences between closely related breeds.

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