akmadan / emotion_detection_cnn Goto Github PK

Hello, can you tell me your tensorflow version and keras version, thank you very much

I am running main.py on mac and getting below error.

/Users/Name/PycharmProjects/MyProject/venv/bin/python /Users/Name/PycharmProjects/MyProject/Emotion_Detection_CNN-main/main.py
1.face_classifier= <CascadeClassifier 0x7ff35297ee50>
Traceback (most recent call last):
File "/Users/Name/PycharmProjects/MyProject/Emotion_Detection_CNN-main/main.py", line 25, in
classifier = load_model('model.h5')
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/saving/save.py", line 184, in load_model
return hdf5_format.load_model_from_hdf5(filepath, custom_objects, compile)
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/saving/hdf5_format.py", line 177, in load_model_from_hdf5
model = model_config_lib.model_from_config(model_config,
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/saving/model_config.py", line 55, in model_from_config
return deserialize(config, custom_objects=custom_objects)
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/layers/serialization.py", line 105, in deserialize
return deserialize_keras_object(
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/utils/generic_utils.py", line 369, in deserialize_keras_object
return cls.from_config(
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/engine/sequential.py", line 397, in from_config
layer = layer_module.deserialize(layer_config,
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/layers/serialization.py", line 105, in deserialize
return deserialize_keras_object(
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/utils/generic_utils.py", line 375, in deserialize_keras_object
return cls.from_config(cls_config)
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/engine/base_layer.py", line 655, in from_config
return cls(**config)
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/layers/convolutional.py", line 592, in init
kernel_initializer=initializers.get(kernel_initializer),
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/initializers.py", line 194, in get
return deserialize(identifier)
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/initializers.py", line 182, in deserialize
return deserialize_keras_object(
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/utils/generic_utils.py", line 361, in deserialize_keras_object
(cls, cls_config) = class_and_config_for_serialized_keras_object(
File "/Users/Name/PycharmProjects/MyProject/venv/lib/python3.8/site-packages/tensorflow/python/keras/utils/generic_utils.py", line 321, in class_and_config_for_serialized_keras_object
raise ValueError('Unknown ' + printable_module_name + ': ' + class_name)
ValueError: Unknown initializer: HeNormal

Process finished with exit code 1

Hi,

That's really impressive work. I have been following the steps from your youtube video to train a CNN custom model on the Face-recognition dataset.
However, I am facing a problem while saving and downloading the model's weights from the Kaggle notebook.

I know this issue has nothing to do with your code but I would appreciate it if you could help me solving this issue.
I am attaching a screenshot and a code snippet for reference. My output file is always empty, doesn't matter whatever I do. I am new to Kaggle and don't have much knowledge of its UI. Please have a look and let me know where I am going wrong to save and download model `weights.
Note: Maybe I am not defining the right path to save model weight.

checkpoint = ModelCheckpoint("./alok.h5", monitor='val_acc', verbose=1, save_best_only=True, mode='max')