Identify lash effect
using AI
Below is a free classifier to identify lash effect. Just upload your image, and our AI will predict the type of lash effect you would like to achieve - 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("lash-effect", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/lash-effect/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/lash-effect/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict the type of lash effect you would like to achieve.
This pretrained image model uses a Nyckel-created dataset and has 30 labels, including Bold, Cat-Eye, Curling, Defined, Dolphin, Downturned, Dramatic, Evening, Everyday and False.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the type of lash effect you would like to achieve).
Whether you're just curious or building lash effect detection into your application, we hope our classifier proves helpful.
Need to identify lash effect at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Cosmetic Authenticity Verification: The 'lash effect' identifier can be employed by cosmetic brands and retailers to verify the authenticity of mascara products in the market. By using the function to detect misleading advertising images, companies can prevent counterfeit products from impersonating their brand's quality.
- Augmented Reality Filters Assessment: Social media platforms can integrate the 'lash effect' identifier to assess the realism of augmented reality filters related to eye makeup. This function can help maintain user trust by flagging filters that create an exaggerated lash effect that doesn't reflect real-world outcomes.
- Influencer Marketing Compliance: Brands can utilize the identifier to ensure influencers are not misrepresenting their products with altered or heavily edited images showing lash effects. This helps to maintain ethical standards in advertising and protects consumers from unrealistic expectations.
- E-commerce Image Quality Control: Online retailers can implement the function to assess product images uploaded by sellers. This ensures that product listings display accurate lash effects, supporting customer satisfaction and reducing return rates caused by misleading visuals.
- Makeup Tutorial Validity: Content creators can use the 'lash effect' identifier to evaluate the authenticity of the techniques shown in their makeup tutorials. By aligning the desired lash effects with real-world results, creators enhance their credibility and viewer engagement.
- Dermatological Research Consistency: Researchers in dermatology can apply the identifier in studies focused on cosmetic product efficacy. By categorizing images based on realistic lash effects, they can gather more reliable data on product impacts and consumer perceptions.
- Brand Reputation Management: Companies can monitor social media platforms for user-generated content that may misrepresent their products' lash effects. The identifier can flag these misleading images for swift brand reputation management, ensuring that consumer perceptions remain aligned with product quality.