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according to the target size argument
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@ -154,7 +154,7 @@ demography = DeepFace.analyze(img_path = "img4.jpg", detector_backend = backends
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face = DeepFace.detectFace(img_path = "img.jpg", target_size = (224, 224), detector_backend = backends[4])
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```
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Face recognition models are actually CNN models and they expect standard sized inputs. So, resizing is required before representation. To avoid deformation, deepface adds black padding pixels after detection and alignment.
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Face recognition models are actually CNN models and they expect standard sized inputs. So, resizing is required before representation. To avoid deformation, deepface adds black padding pixels according to the target size argument after detection and alignment.
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<p align="center"><img src="https://raw.githubusercontent.com/serengil/deepface/master/icon/deepface-detectors-v2.jpg" width="90%" height="90%"></p>
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