Image Classification Tools
User guide
Installation
Install from PyPI
Requirements
Optional dependencies
Install from source
Verify installation
GPU support
Next steps
Quick start guide
Basic workflow
Example: MNIST classification
1. Prepare data
2. Define model
3. Train model
4. Evaluate model
5. Visualize results
Working with custom datasets
Convolutional neural networks
Data augmentation
Hyperparameter optimization
Next steps
API reference
API reference
Core modules
Data loading
Classes
Overview
Example usage
Training
train_one_epoch()
evaluate()
train_model()
Functions
Overview
Example usage
Evaluation
evaluate_model()
Functions
Overview
Example usage
Plotting
Overview
Example usage
Hyperparameter optimization
Overview
Key components
Example usage
Multi-GPU optimization
Search space format
Notes
Module overview
Complete module index
Project links
GitHub Repository
PyPI Package
Issue Tracker
Image Classification Tools
Index
Index
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B
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C
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D
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E
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G
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I
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M
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T
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V
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__init__() (image_classification_tools.pytorch.data.DataLoaders method)
(image_classification_tools.pytorch.data.DataPipeline method)
B
batch_size (image_classification_tools.pytorch.data.DataLoaders attribute)
,
[1]
C
compute_dataset_stats() (image_classification_tools.pytorch.data.DataPipeline static method)
D
DataLoaders (class in image_classification_tools.pytorch.data)
DataPipeline (class in image_classification_tools.pytorch.data)
device (image_classification_tools.pytorch.data.DataLoaders attribute)
,
[1]
E
evaluate() (in module image_classification_tools.pytorch.training)
evaluate_model() (in module image_classification_tools.pytorch.evaluation)
,
[1]
G
get_batch_sizes() (image_classification_tools.pytorch.data.DataLoaders method)
get_loaders() (image_classification_tools.pytorch.data.DataPipeline method)
I
image_classification_tools.pytorch.evaluation
module
image_classification_tools.pytorch.training
module
M
memory_estimate() (image_classification_tools.pytorch.data.DataLoaders method)
module
image_classification_tools.pytorch.evaluation
image_classification_tools.pytorch.training
T
test (image_classification_tools.pytorch.data.DataLoaders attribute)
,
[1]
test_size (image_classification_tools.pytorch.data.DataLoaders attribute)
,
[1]
total_samples() (image_classification_tools.pytorch.data.DataLoaders method)
train (image_classification_tools.pytorch.data.DataLoaders attribute)
,
[1]
train_model() (in module image_classification_tools.pytorch.training)
,
[1]
train_one_epoch() (in module image_classification_tools.pytorch.training)
train_size (image_classification_tools.pytorch.data.DataLoaders attribute)
,
[1]
V
val (image_classification_tools.pytorch.data.DataLoaders attribute)
,
[1]
val_size (image_classification_tools.pytorch.data.DataLoaders attribute)
,
[1]