I’m pretty new to TF and just started by working around this tutorial: “pose classification in keras”.
I am using my own dataset for training/testing and I adjusted the model config :
model.compile( optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'] ) # Add a checkpoint callback to store the checkpoint that has the highest # validation accuracy. checkpoint_path = "weights.best.hdf5" checkpoint = keras.callbacks.ModelCheckpoint(checkpoint_path, monitor='val_accuracy', verbose=1, save_best_only=True, mode='max') earlystopping = keras.callbacks.EarlyStopping(monitor='val_accuracy', patience=20) # Start training history = model.fit(X_train, y_train, epochs=200, batch_size=16, validation_data=(X_val, y_val), callbacks=[checkpoint, earlystopping]) tfjs.converters.save_keras_model(model,'./path')
when importing the tfjs converted model with this command:
model = await tf.loadLayersModel('./path');
I get the following error :
I’m not post processing or rescaling the layers. If you know what the issue might be and have any suggestions, I’ll much appreciate it.