Identify the color of a pair of sunglasses
using AI
Below is a free classifier to identify the color of a pair of sunglasses. Just upload your image, and our AI will predict the color of a pair of sunglasses - in just seconds.
Contact us for API access
Or, use Nyckel to build highly-accurate custom classifiers in just minutes. No PhD required.
Get started
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("the-color-of-a-pair-of-sunglasses", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/the-color-of-a-pair-of-sunglasses/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/the-color-of-a-pair-of-sunglasses/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict the color of a pair of sunglasses.
This pretrained image model uses a Nyckel-created dataset and has 14 labels, including Black, Blue, Brown, Gradient, Gray, Green, Multi-Color, Orange, Pink and Purple.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the color of a pair of sunglasses).
Whether you're just curious or building the color of a pair of sunglasses detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify the color of a pair of sunglasses at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Online Retail Customization: This function can be embedded in e-commerce platforms to help customers visualize how various colored sunglasses would pair with their outfits. By analyzing the color of clothing items uploaded by customers, the system can recommend complementary sunglass colors, enhancing user experience and potentially increasing sales.
- Inventory Management Optimization: Retailers can employ the function to automatically classify and analyze the color distribution of sunglasses in stock. This allows businesses to identify trends in color popularity, enabling more data-driven decisions regarding restocking and inventory turnover.
- Personalized Marketing Campaigns: By integrating color classification into customer databases, brands can tailor marketing campaigns based on individual color preferences. This targeted approach can increase engagement rates, as customers receive promotions and suggestions closely aligned with their style.
- Social Media Content Tagging: The false image classification function can assist social media platforms in automatically tagging and categorizing posts containing sunglasses, identifying their colors for enhanced searchability. This would enable influencers and brands to reach their target audience more effectively through color-focused hashtags.
- Style Recommendation Systems: Fashion and accessory apps can leverage this function to provide users with personalized style recommendations based on the color of sunglasses they prefer. By analyzing user-uploaded photos, the app can suggest outfits or accessories that match their sunglasses, thereby creating a complete look.
- Trend Forecasting Solutions: Market analysts can use this technology to track color trends in sunglasses over time, assisting brands in forecasting future consumer preferences. This data can guide design choices, ensuring that companies remain competitive by producing the most desirable color options.
- Quality Control in Manufacturing: Sunglass manufacturers can implement the classification system to automatically detect color discrepancies during production. By ensuring that the sunglasses match the intended colors reported in design specifications, manufacturers can reduce waste and increase customer satisfaction with consistent product offerings.