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