Automatically assess image quality with AI. Detect blur, low resolution, poor lighting, noise, and other technical issues. Get actionable quality scores to filter low-quality uploads and maintain platform standards.
Try Quality DetectionOur quality detection API analyzes multiple dimensions of image quality and provides both an overall score and individual metrics for each aspect. Set thresholds that match your platform's quality standards.
Detect motion blur, focus issues, and overall sharpness
Assess if resolution meets minimum requirements
Evaluate exposure, brightness, and lighting quality
Measure contrast levels and dynamic range
Detect JPEG artifacts and over-compression
Identify image noise and grain levels
Assess color accuracy and saturation
Evaluate framing and composition quality
Automatically reject low-quality uploads before they reach your platform. Set minimum quality thresholds for blur, resolution, and overall score.
Use quality scores to rank and prioritize content. Show higher quality images in search results and featured sections.
Ensure profile photos meet quality standards. Reject blurry selfies, underexposed photos, or low-resolution uploads.
Enforce quality standards for e-commerce product photos. Ensure consistent, professional product imagery.
{
"quality": {
"overall_score": 78,
"metrics": {
"sharpness": 85,
"resolution": 92,
"lighting": 72,
"contrast": 80,
"noise": 88,
"compression": 65,
"color_quality": 75
},
"issues": [
{"type": "underexposed", "severity": "mild"},
{"type": "compression_artifacts", "severity": "moderate"}
],
"recommendations": ["Increase lighting", "Use less compression"]
},
"processing_time_ms": 18
}
The overall score (0-100) is a weighted combination of all quality metrics. A score above 70 is generally considered good quality, while scores below 50 indicate significant quality issues.
Yes, you can set custom thresholds for each metric via the API. For example, you might require higher sharpness for profile photos but be more lenient with user-generated content.
Our quality metrics are calibrated for photographs. While they work on illustrations and graphics, some metrics like noise and sharpness are most meaningful for photographic content.
Yes, we can detect intentional degradation like excessive filtering, extreme compression, and suspicious processing that might indicate screenshot recycling or image manipulation.
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