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| title: Analogic Watch Detector | |
| emoji: ⌚ | |
| colorFrom: red | |
| colorTo: gray | |
| sdk: gradio | |
| sdk_version: 5.9.1 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| short_description: Automatic time reading from analog clock images using AI. | |
| # Analog Watch Detector | |
| A computer vision application that automatically reads time from images of analog clocks. This project uses a **YOLOv8** model to detect clock components (hands, center, digits) and geometrically calculates the time. | |
| ## 🚀 Application Features | |
| * **Time Detection**: Upload an image of a watch or clock, and the AI will predict the time. | |
| * **Visual Feedback**: Displays the detected components (Hour hand, Minute hand, Second hand) overlaid on the image. | |
| * **Test Examples**: Includes a set of test images to try out immediately. | |
| ## 🛠️ How it Works | |
| The model detects: | |
| 1. **Clock Face/Circle** | |
| 2. **Hour Hand** | |
| 3. **Minute Hand** | |
| 4. **Second Hand** (if present) | |
| 5. **The Number 12** (for orientation) | |
| Using the coordinates of these components, the application calculates the angles of the hands relative to the center and the 12 o'clock position to determine the exact time. | |
| ## 📦 Dataset & Model | |
| * **Model**: YOLOv8s custom trained on a diverse dataset of watches and clocks. | |
| * **Training**: Optimized using hyperparameter tuning (`tune4 - best.pt`). | |
| ## 👨💻 Credits | |
| Developed by **Ana Pinto** and **Pedro Leitão**. | |
| Project developed for a Computer Vision course. |