PC Parts Images Dataset Classification
Dataset of images of computer parts classified into 14 categories, organized according to the ImageNet structure, ideal for classifying computer objects.
3279 JPG images, 14 classes, 256x256 pixel resolution
ODC Attribution License (ODC-by)
Description
The dataset PC Parts Images Dataset Classification includes 3279 images of computer parts divided into 14 distinct classes. The images are in JPG, with a resolution of 256x256 pixels, and organized by folders according to the classic ImageNet structure.
What is this dataset for?
- Train PC component image classification models
- Develop systems for the automatic recognition of computer parts
- Testing CNN architectures on a modest but varied dataset
Can it be enriched or improved?
This dataset can be supplemented by additional annotations on the condition of the parts, or enriched by images from other sources to increase the diversity and robustness of the models.
🔎 In summary
🧠 Recommended for
- Computer vision students
- ML developers
- Image classification researchers
🔧 Compatible tools
- TensorFlow
- PyTorch
- Keras
- FastAI
💡 Tip
Use the ImageNet framework for easy loading via traditional vision libraries.
Frequently Asked Questions
How many PC part classes are there in this dataset?
The dataset contains 14 different classes representing various computer parts.
What is the resolution of the images?
All images are 256x256 pixels, JPG format.
Is this dataset suitable for beginning classification projects?
Yes, its moderate size and clear structure make it a great choice for computer vision beginners.
