Datasets:
Modalities:
Text
Formats:
text
Size:
< 1K
Tags:
humanoid-robotics
fall-prediction
machine-learning
sensor-data
robotics
temporal-convolutional-networks
License:
Dominik Brämer
commited on
Commit
·
ea1a1e5
1
Parent(s):
5563519
add RAM utilization note
Browse files
README.md
CHANGED
@@ -83,7 +83,7 @@ python -m pip install --upgrade pip
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### 3. Run the Example Script
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To load and use the plain csv dataset for training a simple LSTM model, run the `plain_dataset_usage_example.py` script:
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```bash
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python plain_dataset_usage_example.py
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@@ -96,7 +96,7 @@ This script demonstrates how to:
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- Train a basic LSTM model to predict falls
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- Evaluate the model on the test set
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To load and use a already prepared dataset, with reduced RAM utilisation, for training a simple LSTM model, run the `lightweight_dataset_usage_example.py` script:
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```bash
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python lightweight_dataset_usage_example.py
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### 3. Run the Example Script
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To load and use the plain csv dataset for training a simple LSTM model, run the `plain_dataset_usage_example.py` script (RAM utilisation exceeds 16 GB):
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```bash
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python plain_dataset_usage_example.py
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- Train a basic LSTM model to predict falls
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- Evaluate the model on the test set
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+
To load and use a already prepared dataset, with reduced RAM utilisation, for training a simple LSTM model, run the `lightweight_dataset_usage_example.py` script (RAM utilisation less than 2 GB):
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```bash
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python lightweight_dataset_usage_example.py
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