Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
10K - 100K
License:
Update README.md
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README.md
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pretty_name: Intel Image Classification
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- 10K<n<100K
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---
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pretty_name: Intel Image Classification
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size_categories:
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- 10K<n<100K
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---
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# Intel Image Classification
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The **Intel Image Classification** dataset contains images of natural scenes categorized into six classes:
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- Buildings
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- Forest
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- Glacier
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- Mountain
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- Sea
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- Street
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---
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## π Content
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- The dataset contains **~25,000 images** of size **150x150 pixels**.
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- Images are evenly distributed across **6 categories**:
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```
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{'buildings' -> 0,
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'forest' -> 1,
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'glacier' -> 2,
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'mountain' -> 3,
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'sea' -> 4,
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'street' -> 5 }
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```
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- It is divided into three parts:
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- **Training set**: ~14,000 images
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- **Test set**: ~3,000 images
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- **Prediction set**: ~7,000 images
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The train, test, and prediction images are stored in separate folders.
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---
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## π§ͺ Structure
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```
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data/
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βββ seg_train/
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β βββ buildings/
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β βββ forest/
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β βββ glacier/
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β βββ mountain/
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β βββ sea/
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β βββ street/
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βββ seg_test/
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β βββ ...
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βββ seg_pred/
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βββ ...
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```
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---
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## π Source & Acknowledgements
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- Originally published by **Intel** as part of a challenge on **Analytics Vidhya**:
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[https://datahack.analyticsvidhya.com](https://datahack.analyticsvidhya.com/)
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- Rehosted on Kaggle:
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[Intel Image Classification | Kaggle](https://www.kaggle.com/datasets/puneet6060/intel-image-classification)
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---
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## π» Usage
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You can load this dataset using Hugging Face's `datasets` library:
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```python
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from datasets import load_dataset
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dataset = load_dataset("sfarrukhm/intel-image-classification")
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```
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