add flatten solves all my problems :')

kmhosny · Jun 21, 2019 · 47b4c4c · 47b4c4c
1 parent 2cddec7
commit 47b4c4c
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Showing 2 changed files with 2 additions and 4 deletions.
diff --git a/feature_data_generator.py b/feature_data_generator.py
@@ -74,7 +74,6 @@ def __data_generation(self, list_IDs_temp):
             static = self.static_model.predict(ID)
             c3d = self.c3d_model.predict(self.work_directory + ID)
             # Store sample
-            print(X[i, ].shape)
             X[i, ] = self.fusion_method(static, c3d, self.fusion_technique)
 
             # Store class

diff --git a/merge_streams.py b/merge_streams.py
@@ -1,6 +1,6 @@
 import keras.backend as K
 from keras.models import Model, Sequential
-from keras.layers import Dense, Dropout
+from keras.layers import Dense, Dropout, Flatten
 import numpy as np
 from feature_data_generator import FeatureDataGenerator
 from sklearn.model_selection import train_test_split
@@ -89,6 +89,7 @@ def deep_model():
     model.add(Dropout(0.5))
     model.add(Dense(200, activation='relu'))
     model.add(Dropout(0.5))
+    model.add(Flatten())
     model.add(Dense(NUM_OF_CLASSES, activation='softmax'))
     model.compile(
         loss='mean_squared_error', optimizer='sgd', metrics=['accuracy'])
@@ -98,8 +99,6 @@ def deep_model():
 
 def merge_streams_output(static_stream, c3d_stream, technique):
     func = merge_technique[technique]
-    print("static stream shape", static_stream.shape)
-    print("c3d stream shape", c3d_stream.shape)
     return func(static_stream, c3d_stream)