Identify blush placement
using AI
Below is a free classifier to identify blush placement. Just upload your image, and our AI will predict the optimal placement for blush on various facial features - 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("blush-placement", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/blush-placement/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/blush-placement/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict the optimal placement for blush on various facial features.
This pretrained image model uses a Nyckel-created dataset and has 14 labels, including Across Cheeks, Around Eyes, Blush Above Cheekbones, Blush On Brow, Blush On Eyelids, Cheek, Chin, Entire Face, Forehead and Jawline.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the optimal placement for blush on various facial features).
Whether you're just curious or building blush placement detection into your application, we hope our classifier proves helpful.
Need to identify blush placement at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Social Media Content Moderation: This function can be used to automatically identify inappropriate blush placement in images shared on social media platforms. By flagging these images, platforms can enforce community guidelines and maintain a positive user environment.
- Virtual Makeup Applications: Cosmetic companies can leverage this function to enhance virtual makeup try-on applications by ensuring that the blush placement in the simulated images matches user preferences and anatomical realities. This results in more accurate representations and improved customer satisfaction.
- Beauty Influencer Analytics: Beauty brands collaborating with influencers can utilize this function to evaluate the effectiveness of blush application in influencer content. By analyzing blush placement, brands can determine which looks resonate best with audiences and adjust their marketing strategies accordingly.
- AI-Powered Beauty Coaching: Personal beauty coaching apps could integrate this function to provide feedback to users on their blush application techniques. By identifying poorly placed blush, the app can offer tailored tutorials and tips, helping users achieve a more flattering makeup look.
- E-commerce Product Recommendations: E-commerce sites specializing in cosmetics can use this identifier to recommend blush products based on common misapplications seen in customer-uploaded photos. By providing personalized product suggestions, sites can improve user engagement and increase sales.
- Makeup Masterclasses: Educational platforms offering makeup tutorials can use this function to analyze student-uploaded images and provide real-time feedback on blush application. Such assessments can enhance learning experiences and lead to better results for students.
- Augmented Reality Shopping Experience: Retailers can incorporate this function into AR shopping apps to ensure that virtual blush applications are accurately placed on users’ faces. By enhancing the realism of the AR experience, users will feel more confident in their purchases and have a higher likelihood of transactions.