Car vs Bike Classification Dataset
Dataset composed of images of various cars and bicycles, intended for binary classification. The images are not pre-processed, allowing specific enhancements to be applied.
2,000 unique images, JPEG/PNG formats, not preprocessed to allow custom enhancements
CC0: Public Domain
Description
The Car vs Bike Classification Dataset brings together 2,000 unique images of cars and bikes covering a variety of variants and types. The dataset is not preprocessed, which offers the possibility of applying custom increases to enrich the data set.
What is this dataset for?
- Train binary classification models to differentiate cars and bikes.
- Practice data augmentation techniques in computer vision.
- Test classification algorithms in various contexts with high intra-class diversity.
Can it be enriched or improved?
Yes, by applying varied increases and possibly integrating additional images to improve the diversity and robustness of the model.
🔎 In summary
🧠 Recommended for
- Computer vision students
- Classification model developers
- Educational projects
🔧 Compatible tools
- Keras
- TensorFlow
- PyTorch
- OpenCV
💡 Tip
Use Keras image generators to automate increases and improve model robustness.
Frequently Asked Questions
Are the images pre-processed or ready for direct use?
The images are provided raw, without preprocessing, allowing for customized increases as required.
Does this dataset cover different types of cars and bikes?
Yes, it includes a variety of models and types to reflect intra-class diversity.
Can this dataset be used for tasks other than binary classification?
Primarily designed for binary classification, but it can be used as a basis for supervised learning projects related to these classes.
