changing a mistake
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@ -6,6 +6,7 @@ Per dumpster we assume that:
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* there is from 0 to 2 incorrectly sorted trash
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Before running the program it is need to unzip the "Garbage classifier.rar" file in the place where the rest of the files is.
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The assessment of correctness is performed by a Convolutional Neural network. From the initial idea the types of trash changed. Now the Garbage truck will recognize between the following five kinds of debris:
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* paper
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* plastic
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@ -28,7 +29,7 @@ classifier.add(MaxPooling2D(pool_size=(2, 2)))
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classifier.add(Flatten())
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classifier.add(Dense(activation = "relu", units = 64 ))
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classifier.add(Dense(activation = "softmax", units = 5))
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classifier.compile(optimizer = "adam", loss = "binary_crossentropy", metrics = ["accuracy"])
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classifier.compile(optimizer = "adam", loss = "categorical_crossentropy", metrics = ["accuracy"])
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```
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After that I did some work with preprocessing the images I was working with. Made sure that the size is still (110, 110). set a batch size, allowed for flips and such.
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@ -48,13 +49,16 @@ Later I trained my classifier and saved it's weights for future use in the proje
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**UPDATE:**
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I tried running it once again with more epochs and steps per epoch and get a better resulat and I think a better validation loss than before.
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**UPDATE:**
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Fixing my mistake of choosing an incorrect loss function which produced false accuracy.
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```
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classifier.fit_generator( train_generator, steps_per_epoch = 165, epochs = 32, validation_data = test_generator )
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classifier.save_weights('model_ver_5.h5')
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classifier.save_weights('model_ver_6.h5')
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```
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Training:
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![Example](https://i.imgur.com/HBBvWCM.png)
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![Example](https://i.imgur.com/9dsg5ZN.png)
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## Changes in the common part
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