MLExchange File Manager

Simple data management system with Dash UI and Tiled.

Running simple example

1. Create a new Python environment and install dependencies:

conda create -n new_env python==3.11
conda activate new_env
pip install .

2. Create a .env file using .env.example as reference. Update this file accordingly.

3. Start example app:

python fronty.py

Ingest data with MLExchange File Manager

The MLExchange File Manager supports data access through:

1. Loading data from file system: You can access image data located at DATA_DIR. Currently, the supported formats are: PNG, JPG/JPEG, and TIF/TIFF.

2. Loading data from Tiled: Alternatively, you can access data through Tiled by providing a DEFAULT_TILED_URI, (optionally) a DEFAULT_TILED_SUB_URI, and the TILED_KEY associated with this server. Please note that you can set up default values for these variables in the environment file. An example environment file is defined in .env.example

3. Browse directories or Tiled nodes and IMPORT the data sets of interest.

How to set up MLExchange File Manager in your application

1. Define your ploty app with a long_callback_manager

   app = dash.Dash(__name__,
                   long_callback_manager=long_callback_manager)
   

2. Define your file explorer, initialize its callbacks, and set up the upload data path considering the following parameters:

   • data_folder_root: [str] Root folder to data directory for local loading
   • open_explorer: [bool] Open/close the file explorer at start up
   • api_key: [str] Tiled API key
   • logger: [object] An instance of a logging object

   An example code to set this up is shown bellow:

   # Create the file manager dash object
   dash_file_explorer = FileManager(data_folder_root,
                                    open_explorer,
                                    api_key,
                                    logger)
   # Init callbacks
   dash_file_explorer.init_callbacks(app)
   

3. Incorporate the following dash components to your callbacks to load the data:

   • Input({'base_id': 'file-manager', 'name': 'data-project-dict'}, 'data')

     Contains a dictionary with the definition of a DataProject:

       root_uri:           Root (file or tiled) URI
       data_type:          Data type, file or tiled
       datasets:           List of datasets
       project_id:         Project ID
     

   • [Optional] Output({'base_id': 'file-manager', 'name': 'confirm-update-data'}, 'data'),

     Bool flag that indicates if the dataset can be updated. If this flag is set to False, the CLEAR DATA button in the frontend application will not allow importing new data until the flag is set to True. This prevents users from accidently clearing the data without saving their results.

4. Accessing data:

   from file_manager.data_project import DataProject
   
   data_project = DataProject.from_dict(data_project_dict, api_key=YOUR_API_KEY)
   

   In the previous example, data_project_dict correspond to the dictionary stored in {'base_id': 'file-manager', 'name': 'data-project-dict'}. Once the data is loaded in the corresponding object, we can access the 6th and 10th (index=[5, 9]) elements of this project by using:

   base64_image, image_uri = data_project.read_datasets(
       [5,9],
       export='base64',
       resize=True
       )
   

   The parameters of read_data are described as follows: - export: 'base64', 'pillow', or 'raw' (if tiled), default 'base64' - resize: True/False, defaults to True. When True, the image is resized to 200x200 pixels approximately while keeping the aspect ratio of the original image

Copyright

MLExchange Copyright (c) 2024, The Regents of the University of California, through Lawrence Berkeley National Laboratory (subject to receipt of any required approvals from the U.S. Dept. of Energy). All rights reserved.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

(1) Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

(2) Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

(3) Neither the name of the University of California, Lawrence Berkeley National Laboratory, U.S. Dept. of Energy nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.