Identify an ad's image quality
using AI
Below is a free classifier to identify an ad's image quality. Just upload your image, and our AI will predict the overall quality of the advertisement's image. - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("an-ad's-image-quality", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/an-ad's-image-quality/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/an-ad's-image-quality/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict the overall quality of the advertisement's image..
This pretrained image model uses a Nyckel-created dataset and has 8 labels, including Acceptable, High, Low, Medium, Moderate, Poor, Very High and Very Poor.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the overall quality of the advertisement's image.).
Whether you're just curious or building an ad's image quality detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify an ad's image quality at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Ad Quality Assessment: This function can be employed by marketing teams to automatically assess the quality of images used in advertisements. By classifying images as either high-quality or low-quality, teams can make data-driven decisions to optimize their campaigns and improve overall engagement.
- A/B Testing Optimization: Businesses can leverage the image quality identifier to enhance A/B testing of ad creatives. By ensuring that only high-quality images are selected for testing, companies can gain more accurate insights into consumer preferences and performance metrics.
- Automated Pre-Screening: E-commerce platforms can utilize this tool to pre-screen and approve images submitted by sellers or advertisers. By automatically flagging low-quality visuals, the platform can maintain a consistent standard of quality across all listings, enhancing the browsing experience for customers.
- Content Moderation: Social media platforms can use this function to enhance content moderation efforts. By identifying low-quality ad images, the system can help prevent deceptive or misleading ads from appearing on the platform, thereby improving user trust and satisfaction.
- Image Recommendation Engine: This identifier can be integrated into a recommendation engine for digital advertising. By analyzing the quality of images, the platform can suggest higher-quality alternatives to advertisers, improving the effectiveness of ad placements and increasing click-through rates.
- Brand Reputation Management: Companies can employ this classification function to monitor the quality of images associated with their brands in advertisements. By identifying subpar visuals, brands can proactively address potential negative associations that could impact their reputation in the market.
- Ad Spend Efficiency: Marketers can use the function to analyze the relationship between image quality and ad spend efficiency. By focusing on high-quality images that drive performance, businesses can allocate their budgets more effectively and achieve a better return on investment for their advertising campaigns.