Identify what material a picture frame is made from
using AI
Below is a free classifier to identify what material a picture frame is made from. Just upload your image, and our AI will predict what material the picture frame is made from - 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("what-material-a-picture-frame-is-made-from", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/what-material-a-picture-frame-is-made-from/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/what-material-a-picture-frame-is-made-from/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict what material the picture frame is made from.
This pretrained image model uses a Nyckel-created dataset and has 13 labels, including Acrylic, Aluminum, Bamboo, Cardboard, Ceramic, Composite, Fabric, Foam, Glass and Metal.
We'll also show a confidence score (the higher the number, the more confident the AI model is around what material the picture frame is made from).
Whether you're just curious or building what material a picture frame is made from detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify what material a picture frame is made from at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Online Retail Enhancement: This function can be used by e-commerce platforms to provide detailed information about the materials of picture frames listed for sale. By enabling customers to filter their searches based on material, retailers can enhance user experience and increase customer satisfaction by meeting specific preferences.
- Art Gallery Management: Art galleries can utilize the image classification function to manage their inventory more effectively. By identifying the materials used in frames, galleries can classify and organize artwork displays while ensuring that frame materials complement the art style and value.
- Home Decor Applications: Interior design and home decor apps can incorporate this functionality to recommend the best picture frames based on users' aesthetic preferences. By analyzing uploaded images, the app can suggest frames that match the user's choice of materials, colors, and styles for cohesive room decor.
- Insurance Valuation: Insurance companies can use this function to accurately assess and value framed artwork and collectibles. By identifying the frame material, they can provide better quotes and terms for coverage, protecting customers’ investments and mitigating risks.
- Sustainable Material Sourcing: Companies focused on sustainability can use this function to identify and promote eco-friendly picture frame materials. By integrating this feature into their platforms, they can help consumers make more informed choices, track material sourcing provenance, and highlight environmentally responsible options.
- Quality Assessment for Framing Services: Framing service providers can employ this function to evaluate incoming materials for quality assurance. By classifying frames based on their material composition, providers can determine the appropriate handling method and recommend suitable frame types for specific artworks.
- Authenticity Verification: This function can assist in verifying the authenticity of high-value art pieces that come with specific frame materials associated with an artist or era. By identifying the frame material through images, galleries or auction houses can authenticate the artwork and provide provenance details to potential buyers.