Metadata-Version: 2.4
Name: falseresmem
Version: 0.1.0
Summary: A pip-installable PyTorch model package for False Image Memorability prediction.
Author-email: Anastasiia Mikhailova <amikhailova@uchicago.edu>
License-Expression: MIT
License-File: LICENSE
Requires-Python: >=3.7
Requires-Dist: pillow
Requires-Dist: torch
Requires-Dist: torchvision
Description-Content-Type: text/markdown

# FalseResMem Model Package

A pip-installable Python package containing a custom PyTorch model (`FalseResMem`) for prediction of false alarms in visual memory recognition tasks.

## Contact

Author: Anastasiia Mikhailova  
Email: amikhailova@uchicago.edu  

## Installation

You can install the package via pip from source (or PyPI once published):

pip install .

or

pip install FalseResMem
## Usage

Here's a basic example of how to import and use the model after installation:

**Low-level (raw tensors):**
```python
import torch
from FalseResMem import load_model

model = load_model()
model.eval()
input_tensor = torch.randn(1, 3, 224, 224)
output = model(input_tensor)
print(output)
```

**High-level (image file):**
```python
from FalseResMem import predict_image

prob = predict_image("test.jpg").item()
print(f"False alarm probability: {prob:.3f}")
```

## License
MIT
