Datasets:
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---
license: apache-2.0
task_categories:
- image-classification
language:
- en
tags:
- image
- shoe-type
- classification
- video
- 10k
- rgb
size_categories:
- 1K<n<10K
---
# Shoe-Net-10K Dataset
The **Shoe-Net-10K** dataset is a curated collection of 10,000 shoe images annotated for multi-class image classification. This dataset is suitable for training deep learning models to recognize different types of shoes from images.
## Dataset Details
* **Total Images**: 10,000
* **Image Size**: Varies (typical width range: 94 px to 519 px)
* **Format**: Parquet
* **Split**:
* `train`: 10,000 images
* **Modality**: Image
* **License**: Apache 2.0
## Labels
The dataset includes 5 distinct shoe categories:
```python
labels_list = [
'Ballet Flat',
'Boat',
'Brogue',
'Clog',
'Sneaker'
]
```
Each image is labeled with one of the above shoe types.
## Usage
You can load this dataset using the Hugging Face `datasets` library:
```python
from datasets import load_dataset
dataset = load_dataset("prithivMLmods/Shoe-Net-10K")
```
Access individual samples as follows:
```python
sample = dataset["train"][0]
image = sample["image"]
label = sample["label"]
```
## Applications
This dataset can be used for:
* Image classification
* Shoe-type detection
* Retail recommendation systems
* Style and fashion recognition models |