Identify if has false lashes
using AI
Below is a free classifier to identify if has false lashes. Just upload your image, and our AI will predict if it has false lashes - 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("if-has-false-lashes", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/if-has-false-lashes/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/if-has-false-lashes/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict if it has false lashes.
This pretrained image model uses a Nyckel-created dataset and has 2 labels, including False Lashes and Natural.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if it has false lashes).
Whether you're just curious or building if has false lashes detection into your application, we hope our classifier proves helpful.
Need to identify if has false lashes at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Makeup Retail Analysis: This use case involves analyzing product images to determine whether models are wearing false lashes. Retailers can use this information to tailor their marketing strategies for mascara and other eye makeup products, helping to boost sales by highlighting complementary items.
- E-Commerce Product Recommendations: E-commerce platforms can employ this function to enhance their product recommendation engines. By identifying whether a product image features false lashes, the platform can suggest eye makeup products that match the availability of false lashes in the customer's purchase history.
- Influencer Marketing Optimization: Brands can utilize this classification tool to evaluate influencer campaign images for the presence of false lashes. This data can inform partnerships with influencers who align with the brand’s aesthetic, ensuring more effective targeting for beauty-related campaigns.
- Advertising Compliance Monitoring: Advertising agencies can use this function to check if promotional content adheres to specific guidelines regarding the depiction of beauty products. Ensuring that false lashes are correctly portrayed in advertisements can help maintain clarity and transparency with consumers.
- Social Media Content Analysis: Marketing teams can analyze user-generated content from social media to gauge trends in beauty preferences, particularly regarding false lashes. This insight can help brands develop informed marketing strategies and product lines that resonate with their audience.
- Training AI for Virtual Try-On: Companies developing virtual try-on solutions for beauty products can leverage this classification feature to improve accuracy. By recognizing false lashes in model images, the AI can better simulate how different lash styles will appear on virtual users, resulting in a more personalized shopping experience.
- Beauty Tutorials and Content Creation: Content creators can use this feature to ensure their tutorials highlight the application of false lashes effectively. By confirming whether false lashes are present in their videos, creators can enhance viewer engagement by focusing on popular techniques, promoting instructional content that resonates with beauty enthusiasts.