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Minimal, well-documented CNN models for image classification. Great for beginners!

Project description

MiniCNN

MiniCNN is a minimal, well-documented Python package with beginner-friendly Convolutional Neural Network (CNN) models using PyTorch.
Great for learning, tutorials, and fast prototyping.

Installation

pip install MiniCNN

Usage

import torch
from MiniCNN import SimpleCNN, TinyCNN Example: Create a SimpleCNN model for MNIST (10 classes) model = SimpleCNN(num_classes=10)
print(model) Random input (batch=1, channel=1, size=28x28) x = torch.randn(1, 1, 28, 28)
y = model(x)
print(y.shape) # torch.Size()

Features

  • SimpleCNN: Standard small CNN, 2 conv layers + 2 FC layers.
  • TinyCNN: Extremely small model for quick tests.

Requirements

  • Python 3.8+
  • PyTorch >= 2.0.0

License

MIT License

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