---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy

model-index:
- name: brand-detector
  results:
  - task:
      name: Image Classification
      type: image-classification
    metrics:
      - name: Accuracy
        type: accuracy
        value: 0.8428270220756531
---

# brand-detector

Brand detector is a particular case of image classification, since these may contain only text, images, or a combination of both. 

In this work, we trained a system for the brand classification of shoes available at https://www.shooos.com/.

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. 

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.

How to test:
- find on Google Images any image related to shoe brands below and test it!

This model is not fully trained yet :D

## Example Images


#### adidas

![adidas](images/adidas.jpg)

#### arkk-copenhagen

![arkk-copenhagen](images/arkk-copenhagen.jpg)

#### asics

![asics](images/asics.jpg)

#### birkenstock

![birkenstock](images/birkenstock.jpg)

#### bjorn-borg

![bjorn-borg](images/bjorn-borg.jpg)

#### by-garment-makers

![by-garment-makers](images/by-garment-makers.jpg)

#### camper

![camper](images/camper.jpg)

#### carhartt-wip

![carhartt-wip](images/carhartt-wip.jpg)

#### caterpillar

![caterpillar](images/caterpillar.jpg)

#### champion

![champion](images/champion.jpg)

#### chpo

![chpo](images/chpo.jpg)

#### clae

![clae](images/clae.jpg)

#### colorful-standard

![colorful-standard](images/colorful-standard.jpg)

#### converse

![converse](images/converse.jpg)

#### dc-shoes

![dc-shoes](images/dc-shoes.jpg)

#### dedicated

![dedicated](images/dedicated.jpg)

#### dickies

![dickies](images/dickies.jpg)

#### doughnut

![doughnut](images/doughnut.jpg)

#### dr-martens

![dr-martens](images/dr-martens.jpg)

#### fila

![fila](images/fila.jpg)

#### fjallraven

![fjallraven](images/fjallraven.jpg)

#### hanwag

![hanwag](images/hanwag.jpg)

#### happy-socks

![happy-socks](images/happy-socks.jpg)

#### havaianas

![havaianas](images/havaianas.jpg)

#### herschel-supply

![herschel-supply](images/herschel-supply.jpg)

#### iriedaily

![iriedaily](images/iriedaily.jpg)

#### keepcup

![keepcup](images/keepcup.jpg)

#### lefrik

![lefrik](images/lefrik.jpg)

#### loqi

![loqi](images/loqi.jpg)

#### makia

![makia](images/makia.jpg)

#### maloja

![maloja](images/maloja.jpg)

#### new-balance

![new-balance](images/new-balance.jpg)

#### new-era

![new-era](images/new-era.jpg)

#### nike

![nike](images/nike.jpg)

#### norba-clothing

![norba-clothing](images/norba-clothing.jpg)

#### on-running

![on-running](images/on-running.jpg)

#### onitsuka-tiger

![onitsuka-tiger](images/onitsuka-tiger.jpg)

#### palladium

![palladium](images/palladium.jpg)

#### rains

![rains](images/rains.jpg)

#### reebok

![reebok](images/reebok.jpg)

#### saucony

![saucony](images/saucony.jpg)

#### secrid

![secrid](images/secrid.jpg)

#### sneaky

![sneaky](images/sneaky.jpg)

#### stance

![stance](images/stance.jpg)

#### superfeet

![superfeet](images/superfeet.jpg)

#### the-north-face

![the-north-face](images/the-north-face.jpg)

#### timberland

![timberland](images/timberland.jpg)

#### toms

![toms](images/toms.jpg)

#### triwa

![triwa](images/triwa.jpg)

#### under-armour

![under-armour](images/under-armour.jpg)

#### vans

![vans](images/vans.jpg)

#### veja

![veja](images/veja.jpg)