Identify if image has jpeg artifacts
using AI
Below is a free classifier to identify if image has jpeg artifacts. Just upload your image, and our AI will predict if the image has JPEG artifacts - 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("if-image-has-jpeg-artifacts-identifier", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/if-image-has-jpeg-artifacts-identifier/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/if-image-has-jpeg-artifacts-identifier/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict if the image has JPEG artifacts.
This pretrained image model uses a Nyckel-created dataset and has 2 labels, including Clean and Jpeg Artifacts.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if the image has JPEG artifacts).
Whether you're just curious or building if image has jpeg artifacts detection into your application, we hope our classifier proves helpful.
Related Classifiers
Need to identify if image has jpeg artifacts at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Image Quality Assessment: Companies in photography and media can use the JPEG artifacts identifier to automatically assess the quality of images before publication. By filtering out images with low quality due to compression artifacts, they can ensure that only high-quality visuals are presented to their audience.
- Content Moderation: Social media platforms can leverage this function to flag or filter out user-uploaded images that display JPEG artifacts, which often indicate low-quality, edited, or spammy content. This helps maintain community standards and improves overall user experience by reducing the amount of poor-quality imagery.
- Print Media Optimization: Print quality assurance teams can employ this identifier during the pre-press stage to ensure that images intended for print do not suffer from JPEG compression artifacts. By doing so, they can enhance the quality of printed materials and avoid unnecessary reprints due to image quality issues.
- Image Compression Tools: Software developers of image editing tools can implement this function to inform users about potential quality loss due to JPEG compression artifacts. This feature can guide users in choosing optimal settings for saving images, ultimately improving their work's visual fidelity.
- Machine Learning Training Data Validation: Organizations using machine learning for image recognition can utilize the artifact identifier to curate high-quality training datasets. Removing images with JPEG artifacts ensures that the model learns from clear and uncompressed examples, enhancing its accuracy in recognizing patterns.
- Digital Asset Management Solutions: Digital asset management (DAM) systems can integrate this functionality to automate the evaluation of images being uploaded to their platforms. This ensures that assets maintained in the system are of high quality, crucial for brands that rely on consistent visual integrity across their marketing materials.
- E-Commerce Quality Control: E-commerce platforms can use this identifier to evaluate product images uploaded by sellers, filtering out those with evident JPEG artifacts. This ensures that potential customers view only high-quality images, enhancing the shopping experience and potentially increasing conversion rates.