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9323d30
1
Parent(s):
88468ae
Update app.py
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app.py
CHANGED
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@@ -28,7 +28,8 @@ def predict(video):
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model = K.Sequential([
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layers.InputLayer(input_shape=(block_size, 136)),
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layers.Dropout(0.25),
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layers.Bidirectional(layers.GRU(RNN_UNIT)),
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layers.Dropout(DROPOUT_RATE),
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layers.Dense(64, activation='relu'),
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layers.Dropout(DROPOUT_RATE),
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@@ -37,7 +38,8 @@ def predict(video):
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model_diff = K.Sequential([
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layers.InputLayer(input_shape=(block_size - 1, 136)),
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layers.Dropout(0.25),
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layers.Bidirectional(layers.GRU(RNN_UNIT)),
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layers.Dropout(DROPOUT_RATE),
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layers.Dense(64, activation='relu'),
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layers.Dropout(DROPOUT_RATE),
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model = K.Sequential([
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layers.InputLayer(input_shape=(block_size, 136)),
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layers.Dropout(0.25),
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#layers.Bidirectional(layers.GRU(RNN_UNIT)),
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keras.layers.wrappers.Bidirectional(keras.layers.recurrent_v2.GRU(RNN_UNIT)),
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layers.Dropout(DROPOUT_RATE),
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layers.Dense(64, activation='relu'),
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layers.Dropout(DROPOUT_RATE),
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model_diff = K.Sequential([
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layers.InputLayer(input_shape=(block_size - 1, 136)),
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layers.Dropout(0.25),
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#layers.Bidirectional(layers.GRU(RNN_UNIT)),
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keras.layers.wrappers.Bidirectional(keras.layers.recurrent_v2.GRU(RNN_UNIT)),
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layers.Dropout(DROPOUT_RATE),
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layers.Dense(64, activation='relu'),
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layers.Dropout(DROPOUT_RATE),
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