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model.py
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model.py
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from tensorflow.keras.models import model_from_json
from tensorflow.python.keras.backend import set_session
<<<<<<< HEAD
import numpy as np
=======
>>>>>>> e5151adb4 (final)
import tensorflow as tf
config = tf.compat.v1.ConfigProto()
config.gpu_options.per_process_gpu_memory_fraction = 0.15
session = tf.compat.v1.Session(config=config)
set_session(session)
class FacialExpressionModel(object):
<<<<<<< HEAD
EMOTIONS_LIST = ["Angry", "Disgust",
"Fear", "Happy",
"Neutral", "Sad",
"Surprise"]
=======
# EMOTIONS_LIST = ['happy','surprise','neutral','fear','angry','sad','disgust']
>>>>>>> e5151adb4 (final)
def __init__(self, model_json_file, model_weights_file):
# load model from JSON file
with open(model_json_file, "r") as json_file:
loaded_model_json = json_file.read()
self.loaded_model = model_from_json(loaded_model_json)
# load weights into the new model
self.loaded_model.load_weights(model_weights_file)
#self.loaded_model.compile()
#self.loaded_model._make_predict_function()
def predict_emotion(self, img):
global session
set_session(session)
self.preds = self.loaded_model.predict(img)
<<<<<<< HEAD
return FacialExpressionModel.EMOTIONS_LIST[np.argmax(self.preds)]
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return self.preds
>>>>>>> e5151adb4 (final)