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--- |
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tags: |
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- image-classification |
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- pytorch |
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- huggingpics |
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metrics: |
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- accuracy |
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model-index: |
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- name: gender_vender |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9375 |
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--- |
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# gender_vender |
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The difference between this and usual classifiers is, it is not limited to Man and woman. Rather, if you pass a chart, it would not classify as man or woman unlike other classifiers. |
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Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb). |
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Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics). |
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## Example Images |
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#### man |
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#### random things |
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#### woman |
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