mirror of https://github.com/vladmandic/human
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@ -10,6 +10,8 @@ and calculate embedding vectors for both first and second image you want to comp
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To achieve quality results, it is also highly recommended to have `face.mesh` and `face.detection.rotation`
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enabled as calculating feature vectors on non-quality inputs can lead to false results
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Simmilarity match above 75% is considered good match while simmilarity match above 60% is considered best-guess
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For example,
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```js
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@ -92,7 +94,7 @@ To achieve optimal result, `Human` performs following operations on an image bef
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- Find precise face angle and again straighten face
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- Crop again with more narrow margins
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- Convert image to grayscale to avoid impact of different colorizations
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- Normalize brightness to common range for all images
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- Normalize brightness to full range for all images
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<br>
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@ -33,8 +33,9 @@ result = {
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emotion, // <string> 'angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'
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}
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],
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tensor: // if config.face.detector.return is set to true, detector will
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// return a raw tensor containing cropped image of a face
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tensor: // if config.face.detector.return is set to true, detector will return
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// a raw tensor containing cropped image of a face
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// note that tensors must be explicitly disposed to free memory by calling tensor.dispose();
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}
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],
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body: // <array of detected objects>
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