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--- |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
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- name: label |
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dtype: |
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class_label: |
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names: |
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'0': Boot |
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'1': Sandal |
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'2': Shoe |
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splits: |
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- name: train |
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num_bytes: 45518549.0 |
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num_examples: 15000 |
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download_size: 44156942 |
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dataset_size: 45518549.0 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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## Context |
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This Shoe vs Sandal vs Boot Image Dataset contains 15,000 images of shoes, sandals and boots. 5000 images for each category. The images have a resolution of 136x102 pixels in RGB color model. |
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## Content |
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There are three classes here. |
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- Shoe |
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- Sandal |
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- Boot |
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## Inspiration |
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This dataset is ideal for performing multiclass classification with deep neural networks like CNNs. |
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You can use Tensorflow, Keras, Sklearn, PyTorch or other deep/machine learning libraries to build a model from scratch or as an alternative, you can fetch pretrained models as well as fine-tune them. |
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