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model = load_model('./models/tr_model.h5')

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def has_new_triggerword(predictions, chunk_duration, feed_duration, threshold=0.5):
    """
    Function to detect new trigger word in the latest chunk of input audio.
    It is looking for the rising edge of the predictions data belongs to the
    last/latest chunk.
    
    Argument:
    predictions -- predicted labels from model
    chunk_duration -- time in second of a chunk
    feed_duration -- time in second of the input to model

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import pyaudio
from queue import Queue
from threading import Thread
import sys
import time


# Queue to communiate between the audio callback and main thread
q = Queue()

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from keras.applications import inception_v3 as inc_net
inet_model = inc_net.InceptionV3()

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images = transform_img_fn([os.path.join('data','asian-african-elephants.jpg')])
preds = inet_model.predict(images)
for x in decode_predictions(preds)[0]:
    print(x)

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import lime
from lime import lime_image
explainer = lime_image.LimeImageExplainer()
explanation = explainer.explain_instance(images[0], inet_model.predict, 
                                         top_labels=5, 
                                         hide_color=0, 
                                         num_samples=1000)

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Indian_elephant = get_class_index("Indian_elephant")

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from skimage.segmentation import mark_boundaries
temp, mask = explanation.get_image_and_mask(Indian_elephant, positive_only=True, num_features=5, hide_rest=True)
plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))

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African_elephant = get_class_index("African_elephant")
temp, mask = explanation.get_image_and_mask(African_elephant, positive_only=True, num_features=5, hide_rest=True)
plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))

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temp, mask = explanation.get_image_and_mask(Indian_elephant, positive_only=False, num_features=10, hide_rest=False)
plt.imshow(mark_boundaries(temp / 2 + 0.5, mask))