Identify photo exposure balance
using AI
Below is a free classifier to identify photo exposure balance. Just upload your image, and our AI will predict the optimal exposure settings for your photos - 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("photo-exposure-balance", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/photo-exposure-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/photo-exposure-balance/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict the optimal exposure settings for your photos.
This pretrained image model uses a Nyckel-created dataset and has 24 labels, including Artificial Lighting, Balanced, Bright, Dark, Dim, Excessive Highlights, Excessive Shadows, Harsh Lighting, High Contrast and Low Contrast.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the optimal exposure settings for your photos).
Whether you're just curious or building photo exposure balance detection into your application, we hope our classifier proves helpful.
Need to identify photo exposure balance at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Social Media Content Optimization: This function can help social media managers identify and adjust the exposure balance in user-generated photos before they are shared. By ensuring that images have optimal lighting, posts can receive higher engagement rates, contributing to brand visibility and audience growth.
- E-commerce Product Photography: E-commerce platforms can utilize this function to assess product photos for exposure balance. Consistently well-lit images enhance product appeal, reduce return rates, and improve customer purchasing decisions based on perceived quality.
- Real Estate Listings Enhancement: Real estate agencies can employ this classification function to evaluate listing photos for proper exposure. High-quality images with balanced exposure attract more potential buyers by showcasing properties in their best light, resulting in faster sales.
- Photography Training Tools: Photography schools and online courses can integrate this function into their teaching tools to help students learn about exposure balance. By classifying images, students receive real-time feedback on their photography skills, ultimately improving their skill set.
- Brand Consistency in Marketing Materials: Companies can utilize this function to maintain a consistent look across their marketing materials by classifying photo exposures. Ensuring that all images have similar lighting effects strengthens brand identity and can lead to a more professional appearance.
- Automated Image Editing Software: Software developers can integrate this false image classification function into automated image editing applications. By accurately identifying images with poor exposure, the software can suggest or automatically apply enhancements, saving users time and effort in editing.
- AI-Driven Photo Curation: Automated curation services for personal photo libraries can leverage this function to sort and recommend images based on exposure quality. Users can quickly enjoy their best memories, without manually filtering through poorly balanced photos for social sharing or printing.