API Access


import nyckel

credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("bicycle-brands-by-logo", "your_image_url", credentials)


fetch('https://www.nyckel.com/v1/functions/bicycle-brands-by-logo/invoke', {
    method: 'POST',
    headers: {
        'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
        'Content-Type': 'application/json',
    },
    body: JSON.stringify(
        {"data": "your_image_url"}
    )
})
.then(response => response.json())
.then(data => console.log(data));


curl -X POST \
    -H "Content-Type: application/json" \
    -H "Authorization: Bearer YOUR_BEARER_TOKEN" \
    -d '{"data": "your_image_url"}' \
    https://www.nyckel.com/v1/functions/bicycle-brands-by-logo/invoke

How this classifier works

To start, upload your image. Our AI tool will then predict what bicycle brand it is.

This pretrained image model uses a Nyckel-created dataset and has 33 labels, including Batavus, Bianchi, Bmc, Brompton, Cannondale, Cervelo, Colnago, Cube, Diamondback and Felt.

We'll also show a confidence score (the higher the number, the more confident the AI model is around what bicycle brand it is).

Whether you're just curious or building bicycle brands by logo detection into your application, we hope our classifier proves helpful.

Need to identify bicycle brands by logo at scale?

Get API or Zapier access to this classifier for free. It's perfect for:

Inventory Management: Retailers can utilize the logo identification function to automatically categorize and manage their bicycle inventory based on brands. This allows for more efficient stock tracking, reducing the chances of overstocking or understocking specific brands.

Market Analysis: Market research firms can analyze brand presence and consumer preferences by leveraging the logo recognition capabilities. This can aid in understanding competitive positioning and identifying brand loyalty trends within specific regions.

Brand Collaboration Opportunities: Bicycle manufacturers can use the classification functionality to identify potential collaboration opportunities with other brands whose logos frequently appear together. This insight can help in developing co-branded marketing strategies or product lines.

Counterfeit Detection: E-commerce platforms can implement the logo identification system to flag counterfeit bicycles or accessories. By verifying logos against known brands, platforms can enhance consumer trust and maintain brand integrity.

User-Generated Content Analysis: Social media companies can employ the function to analyze user-generated content related to bicycles. By identifying logos in posts, they can gain insights into brand popularity and consumer engagement on their platforms.

Personalized Marketing Campaigns: Marketing agencies can utilize the logo identification for targeted advertising. By recognizing the brands consumers engage with, agencies can personalize campaigns to promote complementary products and increase conversion rates.

Event Sponsorship Analysis: Event organizers can implement the classification function to assess brand visibility during cycling events. By analyzing logos on participant gear, vehicles, and merchandise, organizers can provide sponsors with valuable insights on exposure and brand impact.

Identify bicycle brands by logo using AI

API Access

How this classifier works

Need to identify bicycle brands by logo at scale?