Identify if image has motion blur
using AI
Below is a free classifier to identify if image has motion blur. Just upload your image, and our AI will predict if the image has motion blur - in just seconds.
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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-motion-blur-identifier", "your_image_url", credentials)
fetch('https://www.nyckel.com/v1/functions/if-image-has-motion-blur-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-motion-blur-identifier/invoke
How this classifier works
To start, upload your image. Our AI tool will then predict if the image has motion blur.
This pretrained image model uses a Nyckel-created dataset and has 2 labels, including Motion Blur and No Motion Blur.
We'll also show a confidence score (the higher the number, the more confident the AI model is around if the image has motion blur).
Whether you're just curious or building if image has motion blur detection into your application, we hope our classifier proves helpful.
Related Classifiers
Need to identify if image has motion blur at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Quality Control in Photography: Photography businesses can utilize the motion blur identifier to automatically filter out low-quality images before delivery to clients. This process saves time and maintains the high standards expected in professional photography.
- Sports Analytics: Sports teams and analysts can apply this function to evaluate performance by analyzing game footage. It helps identify critical moments with blurred images, allowing for the assessment of player movement and action dynamics.
- Autonomous Vehicles: Motion blur detection can be integrated into the imaging systems of self-driving cars to enhance object recognition capabilities. By identifying and compensating for motion blur, the vehicle’s systems can better interpret real-time data from the environment for safer navigation.
- Video Surveillance: Security cameras can employ motion blur identification to determine whether incidents are accurately recorded. This technology could enhance incident reporting and evidence collection by ensuring quality visuals during critical moments.
- Augmented Reality Applications: In augmented reality (AR) apps, detecting motion blur can help improve user experience by ensuring real-time overlays appear clear and stable. The application can adjust the rendering based on motion analysis to deliver a smoother visual experience.
- Automated Content Moderation: Social media platforms can utilize the motion blur function to filter out potentially disruptive content that lacks clarity. Identifying motion-blurred images allows for automated moderation processes that ensure only suitable, high-quality content is displayed.
- E-commerce Product Listings: Online retailers can use motion blur detection to enhance their image quality control processes. By flagging images with blur, retailers can encourage sellers to upload clearer photos, improving the overall shopping experience and reducing product return rates.