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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