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
arkk-copenhagen
asics
birkenstock
bjorn-borg
by-garment-makers
camper
carhartt-wip
caterpillar
champion
chpo
clae
colorful-standard
converse
dc-shoes
dedicated
dickies
doughnut
dr-martens
fila
fjallraven
hanwag
happy-socks
havaianas
herschel-supply
iriedaily
keepcup
lefrik
loqi
makia
maloja
new-balance
new-era
nike
norba-clothing
on-running
onitsuka-tiger
palladium
rains
reebok
saucony
secrid
sneaky
stance
superfeet
the-north-face
timberland
toms
triwa
under-armour
vans
veja
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Inference Providers
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This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Evaluation results
- Accuracyself-reported0.843