Implemented core modules, CI/CD and basic test.

.github/workflows/python-ci.yml

@@ -0,0 +1,32 @@
+name: Python CI
+
+on:
+  push:
+    branches:
+      - main
+    pull_request:
+      branches:
+        - main
+
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v3
+
+    - name: Set up Python
+      uses: actions/setup-python@v3
+      with:
+        python-version: '3.10'
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install -r requirements.txt
+
+    - name: Run tests
+      run: |
+        pytest

.gitignore

@@ -1,3 +1,4 @@
 artify.egg-info
 src/__pycache__
-test
+test
+.pytest_cache

README.md

@@ -1,25 +1,2 @@
 # Artify
-**Artify** is an AI-powered image style transfer bot that transforms ordinary photos into unique artworks inspired by famous artists. This project aims to provide a seamless, user-friendly experience for converting images into stylized renditions with a choice of well-known art styles.
-
-## Project Features:
-1. **Core Functionality**:
-   - **Famous Art Styles**: Apply styles from famous artists (e.g., Van Gogh, Picasso).
-   - **Image Upload and Download**: Users can easily upload images and download the stylized results.
-   - **Style Selection**: Choose from a variety of art styles for each transformation.
-   - **High-Quality Output**: Produces high-resolution, stylized images.
-
-2. **Additional Capabilities** (Future Phases):
-   - **Custom Style Upload**: Allows users to upload and apply their own custom styles.
-   - **Style Recommendations**: Suggest styles based on the characteristics of the uploaded image.
-
-## Technical Structure:
-   - **Backend**: Built using FastAPI or Flask to handle image processing and style application.
-   - **Frontend**: A simple, intuitive interface (HTML/CSS or React) for image uploads, style selection, and result previews.
-   - **Deployment**: Includes Docker setup and GitHub Actions for continuous integration and deployment.
-   - **Comprehensive Documentation**: User guidelines, sample images, and troubleshooting support.
-
-3. **Future Enhancements**:
-   - Expanding the style library and custom user options.
-   - Real-time processing for faster, optimized results.
-   - A mobile-friendly interface or dedicated app for broader accessibility.
-
+Artify is a modular AI-powered project to apply artistic styles to images.

core/ImageProcessor.py

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+from PIL import Image 
+
+class ImageProcessor:
+    @staticmethod
+    def preprocess_image(image_path, size=512):
+        image = Image.open(image_path).convert("RGB")
+        image = image.resize((size, size))
+        return image 
+
+    @staticmethod
+    def save_image(image, output_path):
+        image.save(output_path)
+
+

core/StyleTransferModel.py

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+import torch 
+import torchvision.transforms as transforms
+from PIL import Image 
+
+class StyleTransferModel:
+    def __init__(self, model_path):
+        self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+        self.model = torch.load(model_path).to(self.device)
+
+    def apply_style(self, content_image, style_image):
+        '''Style transfer logic'''
+        ...
+

requirements.txt

@@ -1,5 +1,7 @@
-fastapi
-uvicorn
-torch  
-pillow
-python-multipart
+torch 
+torchvision 
+numpy 
+pillow 
+matplotlib 
+streamlit 
+pytest

tests/test_sample.py

@@ -0,0 +1,2 @@
+def test_example():
+    assert 2 + 2 == 4