Identify composition balance
using AI
Below is a free classifier to identify composition balance. Just upload your image, and our AI will predict the visual harmony and symmetry of various compositions - 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("composition-balance", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/composition-balance/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/composition-balance/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict the visual harmony and symmetry of various compositions.
This pretrained image model uses a Nyckel-created dataset and has 26 labels, including Asymmetrical, Background Emphasis, Balanced, Centered, Chaotic, Cluttered, Color Balance, Contrasting Elements, Converging Lines and Disjointed.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the visual harmony and symmetry of various compositions).
Whether you're just curious or building composition balance detection into your application, we hope our classifier proves helpful.
Related Classifiers
Need to identify composition balance at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Quality Control in Manufacturing: This function can be employed in a manufacturing setting to automatically identify defects in visual representations of products. By analyzing the balance in composition, it can flag images that do not meet quality standards, ensuring consistent product aesthetics.
- Content Moderation for Social Media: Platforms can use the function to classify images that may promote misleading content. By identifying false images based on composition balance, moderators can efficiently filter out harmful posts, improving user safety and content integrity.
- E-commerce Image Verification: E-commerce businesses can utilize this identifier to verify that product images uploaded by sellers meet specific quality criteria. By flagging images that lack balance in composition, the system supports a more professional and trustworthy online shopping experience for consumers.
- Advertising Compliance: Marketing agencies can implement this function to ensure that marketing materials adhere to visual guidelines. By examining the composition of images, the system can confirm whether the advertisements maintain brand consistency and are visually engaging without misrepresentation.
- Image Curation for Galleries: Art galleries and curators can apply this identifier to assist in the selection of artwork for exhibitions. By evaluating composition balance, the tool can help identify pieces that convey the intended aesthetic and thematic messages, enhancing the overall exhibition quality.
- Academic Research in Visual Perception: Researchers studying human perception of images can use this function to classify images in their experiments. By identifying variations in composition balance, they can analyze how these visual elements impact viewer interpretation and emotional response.
- Automated Photography Enhancement: Photography software can integrate this function to provide real-time feedback during shooting or editing. By identifying false images based on composition balance, photographers can make adjustments promptly, ensuring optimal image quality before finalizing their work.