testing added with fix lint issues

.github/workflows/lint.yml

@@ -0,0 +1,39 @@
+name: Lint
+
+on:
+  push:
+    branches: [ main, walid-branch, cnn ]
+  pull_request:
+    branches: [ main, walid-branch, cnn ]
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v4
+
+    - name: Set up Python
+      uses: actions/setup-python@v5
+      with:
+        python-version: '3.12'
+
+    - name: Install linting dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install black flake8 isort
+
+    - name: Check code formatting with Black
+      run: |
+        black --check --diff models/ utils/ tests/
+
+    - name: Check import sorting with isort
+      run: |
+        isort --check-only --diff models/ utils/ tests/
+
+    - name: Lint with flake8
+      run: |
+        # Stop the build if there are Python syntax errors or undefined names
+        flake8 models/ utils/ tests/ --count --select=E9,F63,F7,F82 --show-source --statistics
+        # Exit-zero treats all errors as warnings. Max line length set to 100
+        flake8 models/ utils/ tests/ --count --max-line-length=100 --statistics --extend-ignore=E203,W503

.github/workflows/test.yml

@@ -0,0 +1,40 @@
+name: Tests
+
+on:
+  push:
+    branches: [ main, walid-branch, cnn ]
+  pull_request:
+    branches: [ main, walid-branch, cnn ]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.11', '3.12']
+
+    steps:
+    - uses: actions/checkout@v4
+
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v5
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -r requirements.txt
+        pip install pytest pytest-cov
+
+    - name: Run tests with pytest
+      run: |
+        pytest tests/ -v --cov=models --cov=utils --cov-report=term-missing
+
+    - name: Upload coverage reports
+      if: matrix.python-version == '3.12'
+      uses: codecov/codecov-action@v4
+      with:
+        fail_ci_if_error: false
+      env:
+        CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}

.gitignore

@@ -11,3 +11,6 @@ wheels/
 computer-vision/
 
 *.png
+.DS_Store
+
+.coverage

Makefile

@@ -0,0 +1,45 @@
+
+
+.PHONY: help install install-dev test test-cov lint format format-check type-check train clean pre-commit all
+
+help:
+	@echo "Available commands:"
+	@echo "  make install          Install production dependencies"
+	@echo "  make install-dev      Install development dependencies"
+	@echo "  make test             Run tests ith coverage report"
+	@echo "  make lint             Run linting (flake8)"
+	@echo "  make format           Format code with black and isort"
+	@echo "  make train            Train model (use SCRIPT=path/to/script.py)" 
+	@echo "  make type-check       Run type checking with mypy"
+	@echo "  make clean            Remove build artifacts and cache files"
+	@echo "  make all              Run format, lint, type-check, and test"
+
+install:
+	pip install -r requirements.txt
+
+install-dev:
+	pip install -r requirements-dev.txt
+
+test:
+	pytest --cov --cov-report=html --cov-report=term
+
+lint:
+	flake8 models utils tests
+
+format:
+	black models utils tests
+	isort models utils tests
+
+type-check:
+	mypy models utils
+
+
+clean:
+	find . -type f -name '*.pyc' -delete
+	find . -type d -name '__pycache__' -delete
+	find . -type d -name '*.egg-info' -exec rm -rf {} +
+	find . -type d -name '.pytest_cache' -exec rm -rf {} +
+	find . -type d -name '.mypy_cache' -exec rm -rf {} +
+	rm -rf build dist htmlcov .coverage
+
+all: format lint type-check test

README.md

@@ -0,0 +1,143 @@
+# Computer Vision Project
+
+![Tests](https://github.com/alexisvannson/computer-vision/actions/workflows/test.yml/badge.svg)
+![Lint](https://github.com/alexisvannson/computer-vision/actions/workflows/lint.yml/badge.svg)
+![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)
+![Python](https://img.shields.io/badge/python-3.12+-blue.svg)
+
+A PyTorch-based computer vision project implementing various neural network architectures including CNNs, MLPs, and exploring advanced topics like attention mechanisms, transfer learning, and generative models.
+
+## Features
+
+- **Flexible CNN Implementation**: Convolutional Neural Network for image classification tasks
+- **Customizable MLP**: Multi-layer Perceptron with configurable hidden layers, activations, and normalization
+- **Training Utilities**: Modular training pipeline for model development
+- **CI/CD Integration**: Automated testing and linting with GitHub Actions
+- **Code Quality**: Enforced code formatting with Black, import sorting with isort, and type checking with mypy
+
+## Project Structure
+
+```
+computer-vision/
+├── models/              # Neural network architectures
+│   ├── CNN.py          # Convolutional Neural Network
+│   └── MLP.py          # Multi-layer Perceptron
+├── utils/              # Training and utility functions
+│   └── train_model.py  # Model training utilities
+├── tests/              # Unit and integration tests
+│   ├── test_models.py
+│   └── test_training.py
+├── data/               # Dataset directory
+│   ├── train/
+│   ├── test/
+│   └── train_labels.csv
+├── notebooks/          # Jupyter notebooks for experiments
+├── .github/workflows/  # CI/CD configuration
+│   ├── test.yml       # Automated testing
+│   └── lint.yml       # Code quality checks
+└── Makefile           # Development commands
+```
+
+## Installation
+
+### Prerequisites
+
+- Python 3.12+
+- pip or uv package manager
+
+### Basic Installation
+
+```bash
+# Clone the repository
+git clone <repository-url>
+cd computer-vision
+
+# Install dependencies
+pip install -r requirements.txt
+```
+
+### Development Installation
+
+```bash
+# Install development dependencies (includes testing and linting tools)
+make install-dev
+# or
+pip install -r requirements-dev.txt
+```
+
+## Usage
+
+
+## Development
+
+### Available Make Commands
+
+```bash
+# Install development dependencies
+make install-dev
+
+# Run tests
+make test
+
+# Run tests with coverage report
+make test-cov
+
+# Lint code
+make lint
+
+# Format code
+make format
+
+# Check formatting without changes
+make format-check
+
+# Type checking
+make type-check
+
+# Train a model
+make train SCRIPT=your_script.py
+
+# Clean build artifacts
+make clean
+```
+
+### Code Quality
+
+This project enforces code quality through:
+
+- **Black**: Code formatting (line length: 100)
+- **isort**: Import sorting
+- **flake8**: Linting
+- **mypy**: Static type checking
+- **pytest**: Unit and integration testing
+
+### Running Tests
+
+```bash
+# Run all tests
+make test
+
+# Run tests with coverage
+make test-cov
+
+# Run specific test file
+pytest tests/test_models.py
+```
+
+## CI/CD
+
+The project includes GitHub Actions workflows for:
+
+- **Automated Testing**: Runs on every push and pull request
+- **Code Linting**: Ensures code quality standards
+- **Type Checking**: Validates type annotations
+
+
+### Code Style
+
+- Follow PEP 8 guidelines
+- Use type hints for function arguments and return values
+- Write docstrings for classes and functions
+- Maintain test coverage for new features
+
+

gameplan.md

@@ -14,3 +14,6 @@ Generative Adversarial Network (GAN)
 
 
 Diffusion
+
+
+DENO 

models/CNN.py

@@ -1,11 +1,10 @@
-import torch 
+import torch
 import torch.nn as nn
 import torch.nn.functional as F
 
 
 class CNN(nn.Module):
     def __init__(self):
-
         """
         Flexible Convolutional Neural Network.
         """
@@ -21,61 +20,8 @@ def __init__(self):
     def forward(self, x):
         x = self.pool(F.relu(self.conv1(x)))
         x = self.pool(F.relu(self.conv2(x)))
-        x = torch.flatten(x, 1) # flatten all dimensions except batch
+        x = torch.flatten(x, 1)  # flatten all dimensions except batch
         x = F.relu(self.fc1(x))
         x = F.relu(self.fc2(x))
         x = self.fc3(x)
         return x
-
-
-net = Net()
-
-
-
-import torch.nn as nn
-from torch import Tensor
-
-# Definition of a MLP
-class MLP(nn.Module):
-    def __init__(
-        self,
-        in_dim: int,
-        out_dim: int,
-        hidden_dim: int = 128,
-        hidden_layers: int = 2,
-        activation: str = "ReLU",
-        initializer: None | str = None,
-        norm_type: None | str = "LayerNorm",
-    ):
-        """
-        Flexible Multi-layer perceptron.
-        """
-
-        super(MLP, self).__init__()
-        self.activation = getattr(nn, activation)()
-        if initializer is not None:
-            self.initializer = getattr(nn.init, initializer)
-        layers = [nn.Linear(in_dim, hidden_dim), self.activation]
-        for _ in range(hidden_layers - 1):
-            layers += [nn.Linear(hidden_dim, hidden_dim), self.activation]
-        layers.append(nn.Linear(hidden_dim, out_dim))
-
-        if norm_type is not None:
-            assert norm_type in [
-                "LayerNorm",
-                "BatchNorm1d",
-            ]
-            norm_layer = getattr(nn, norm_type)
-            layers.append(norm_layer(out_dim))
-
-        self.model = nn.Sequential(*layers)
-
-        if initializer is not None:
-            params = self.model.parameters()
-            for param in params:
-                if param.requires_grad and len(param.shape) > 1:
-                    self.initializer(param)
-
-    def forward(self, x: Tensor):
-        x = x.view(x.size(0), -1)  # Flatten: (batch, channels*height*width)
-        return self.model(x.float())

models/MLP.py

@@ -1,6 +1,7 @@
 import torch.nn as nn
 from torch import Tensor
 
+
 # Definition of a MLP
 class MLP(nn.Module):
     def __init__(
@@ -44,4 +45,4 @@ def __init__(
 
     def forward(self, x: Tensor):
         x = x.view(x.size(0), -1)  # Flatten: (batch, channels*height*width)
-        return self.model(x.float())
+        return self.model(x.float())