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in_memory: false does not work with images

See original GitHub issue

Describe the bug the preprocesing setting in_memory: false for images as input features does not seem to work. The hdf5 file is still loaded into the RAM during training.

To Reproduce a .yaml file like this one:

input_features:
    -   
        name: image_path
        type: image
        preprocessing:
          in_memory: false
        encoder: stacked_cnn
        conv_layers:
            -   
                num_filters: 32
                filter_size: 15
                pool_size: 2
                pool_stride: 2
            -   
                num_filters: 64
                filter_size: 15
                pool_size: 2
                pool_stride: 2
                dropout: true
        fc_layers:
            -   
                fc_size: 128
                dropout: true



output_features:
    -   
        name: class
        type: category

training:
    reduce_learning_rate_on_plateau: 10
    early_stop: 10
    learning_rate: 0.0004
    batch_size: 40

Same is true when I use preprocessing as a separate section at the end of the .yaml file.

Issue Analytics

State:
Created 4 years ago
Comments:12

Top GitHub Comments

1reaction

tboocommented, Oct 11, 2019

A related project. I am trying to identify individuals from the same worm species based on their pigmentation pattern. Face recognition for worms so to speak.

1reaction

w4nderlustcommented, Sep 3, 2019

@tboo can you provide more details please? Otherwise it would be difficult for us to reproduce and solve. @ydudin3 can you look into this?

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