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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: brand-detector |
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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: 0.8428270220756531 |
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--- |
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# brand-detector |
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Brand detector is a particular case of image classification, since these may contain only text, images, or a combination of both. |
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In this work, we trained a system for the brand classification of shoes available at https://www.shooos.com/. |
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The method allows obtaining the most similar brands on the basis of their shape, color, business sector, semantics, general characteristics, or a combination of other features. |
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The proposed approach is evaluated using 15% of unseen images of the dataset. The experimentation carried out attained reliable performance results, both quantitatively and qualitatively. |
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How to test: |
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- find on Google Images any image related to shoe brands below and test it! |
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This model is not fully trained yet :D |
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## Example Images |
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#### adidas |
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#### arkk-copenhagen |
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#### asics |
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#### birkenstock |
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#### bjorn-borg |
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#### by-garment-makers |
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#### camper |
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#### carhartt-wip |
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#### caterpillar |
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#### champion |
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#### chpo |
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#### clae |
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#### colorful-standard |
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#### converse |
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#### dc-shoes |
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#### dedicated |
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#### dickies |
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#### doughnut |
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#### dr-martens |
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#### fila |
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#### fjallraven |
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#### hanwag |
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#### happy-socks |
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#### havaianas |
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#### herschel-supply |
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#### iriedaily |
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#### keepcup |
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#### lefrik |
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#### loqi |
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#### makia |
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#### maloja |
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#### new-balance |
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#### new-era |
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#### nike |
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#### norba-clothing |
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#### on-running |
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#### onitsuka-tiger |
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#### palladium |
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#### rains |
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#### reebok |
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#### saucony |
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#### secrid |
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#### sneaky |
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#### stance |
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#### superfeet |
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#### the-north-face |
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#### timberland |
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#### toms |
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#### triwa |
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#### under-armour |
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#### vans |
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#### veja |
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