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Prediction.py
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Prediction.py
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import pickle
import numpy as np
from keras_facenet import FaceNet
from utils_training_and_prediction import get_embedding
from utils_face import ExtractFaces
def Load_Prediction_Object():
# Load the model and encoder from their respective files using pickle
with open('SerializedObjects/svc_model.pkl', 'rb') as file:
model = pickle.load(file)
with open('SerializedObjects/encoder.pkl', 'rb') as file:
encoder = pickle.load(file)
embedder = FaceNet()
return model,encoder,embedder
def predict_face(model, encoder, embedder, img_file_path):
T = []
if not isinstance(img_file_path, np.ndarray):
TEST_EMBEDDING = get_embedding(embedder,ExtractFaces(img_file_path))
else:
TEST_EMBEDDING = get_embedding(embedder, img_file_path)
if TEST_EMBEDDING is not None:
T.append(TEST_EMBEDDING)
T_EMBEDDING = np.asarray(T)
probabilities = model.predict_proba(T_EMBEDDING)
prob_score = (np.max(probabilities, axis=1))
pred_test = model.predict(T_EMBEDDING)
if prob_score[0] < 0.49:
return 0,'Unknown'
else:
return prob_score[0] ,encoder.inverse_transform(pred_test)[0]
else:
return 0,'No face was detected'
#model, encoder, embedder = Load_Prediction_Object()
#print('Billy:::')
#predict_face(model, encoder, embedder, 'Test/IMG_20221004_235312_695.jpg')
#print('Jenna:::')
#predict_face(model, encoder, embedder, 'Test/jenna-ortega-2.png')
#print('Jenna:::')
#predict_face(model, encoder, embedder, 'Test/jenna_valid.jpg')
#print('Billy:::')
#predict_face(model, encoder, embedder, 'Test/Photo.jpg')
#print('Elon:::')
#predict_face(model, encoder, embedder, 'Test/elon_valid.jpeg')
#print('Elon:::')
#predict_face(model, encoder, embedder ,'Test/elon-musk3.jpeg')
#print('Eric:::')
#predict_face(model, encoder, embedder ,'Test/visu_1515061157.jpg')