英文:
Flutter TFLite model keeps outputting the same result
问题
在Flutter中，你的输出一直为0.0的问题可能是因为数据类型不匹配。在Python中，你已经注意到需要将输入数据转换为float32类型，以便正确运行模型并获得0到1范围内的输出值。在Flutter中，你尝试使用Float32List来转换数据，但结果仍然为0.0。
要解决这个问题，确保在Flutter中的数据类型与模型期望的数据类型匹配。你可以尝试在Flutter中将输入数据转换为float32类型，类似于你在Python中的操作。另外，确保输入数据的范围和标准化与在Python中训练模型时使用的相同，这也可能会影响输出结果。
此外，还要确保Flutter中的输入数据格式与模型的输入层匹配，包括形状和顺序。
如果问题仍然存在，可能需要进一步检查Flutter中的推理过程和数据预处理，以确保每一步都正确无误。
英文:
I am building a CNN classification model using tensorflow and python. The model has an input shape of [1, 50, 7] consisting the first column of timestamp, and sensor values for the rest of the columns. The output value is either 0 or 1 to specify motion of left or right. Then, I export the model as TFLite model and used it in Flutter using the tflite_flutter package (https://pub.dev/packages/tflite_flutter).
When I run using interpreter run, the output of the data is always 0.0. However, when I run using python, I noticed that after reading a csv data, I needed to add
input_data = input_data.astype('float32')
to properly run the model and it output a value in range of 0 to 1, which is what I wanted, or else it will output that it cannot get tensor due to getting FLOAT64 instead of FLOAT32.
So, I tried to convert my data into float32 using the Float32List in Flutter, but the result is still 0.0.
List<Float32List> group32Float = [];
for (var i = 0; i < 50; i++) {
group32Float.add(Float32List.fromList(group[i]));
}
interpreter!.run([group32Float], [output]);
My model is as such:
input_shape = (50, 7)
model = Sequential()
model.add(Conv1D(filters=32, kernel_size=3, activation='relu', padding='same', input_shape=input_shape))
model.add(BatchNormalization())
model.add(MaxPooling1D(pool_size=2))
model.add(Dropout(0.25))
model.add(Conv1D(filters=64, kernel_size=3, activation='relu', padding='same'))
model.add(BatchNormalization())
model.add(MaxPooling1D(pool_size=2))
model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dense(units=64, activation='relu', kernel_regularizer=regularizers.l2(0.001)))
model.add(BatchNormalization())
model.add(Dropout(0.5))
model.add(Dense(units=32, activation='relu', kernel_regularizer=regularizers.l2(0.001)))
model.add(BatchNormalization())
model.add(Dropout(0.5))
model.add(Dense(1, activation='sigmoid'))
optimizer = Adam(learning_rate=0.001)
model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=['accuracy'])
early_stop = EarlyStopping(monitor='val_loss', patience=100)
model.fit(X_train, y_train, epochs=1000, validation_data=(X_val, y_val), callbacks=[early_stop])
Then saved as TFLite:
model.save('model', save_format='tf')
converter = tf.lite.TFLiteConverter.from_saved_model('model')
tflite_model = converter.convert()
with open('model.tflite', 'wb') as f:
f.write(tflite_model)
My question is: Why is my output in Flutter always 0.0?
答案1
得分: 0
我找到了解决方案。我意识到我最初没有将我的输入数据设置为正确的类型，对我来说应该是：
List<List<double>> input
尝试检查你的输入和输出变量类型，确保其是正确的类型以发送到模型中。
英文:
For anyone having trouble with the same problem, I've found a solution. I realized that I haven't initially set my input data into the correct type which in my case is:
List<List<double>> input
Try checking your variable type of input and output and make sure it's the correct type to send into the model.
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