31 lines
915 B
Python
31 lines
915 B
Python
from keras.models import load_model
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import numpy as np
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import cv2
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class GenderPrediction:
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def __init__(self):
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self.model = load_model("gender_v1.0.h5")
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def predict_gender(self, image):
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# chuyển ảnh về mức xám
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gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
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# resize ảnh phủ hợp với model
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target_size = (48, 48)
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resized_face = cv2.resize(gray, target_size)
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# normalize ảnh
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normalize_face = resized_face / 255.0
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# chuyển về cùng shape với input tensror (1,48,48)
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normalize_face = np.expand_dims(normalize_face, axis=0)
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# model output 'probabilities': array([[0.019824,0.98018]], dtype=float32)
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predictions = self.model.predict(normalize_face)
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threshold = 0.5
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predicted_class = 'Male' if predictions[0][1] >= threshold else 'Female'
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return predicted_class
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