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| title: AI Plant Vision | |
| emoji: 🏆 | |
| colorFrom: yellow | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 5.17.1 | |
| app_file: app.py | |
| pinned: false | |
| license: apache-2.0 | |
| short_description: ' Plant Classifier AI - Integrated with Plant Info API ' | |
| Check out the configuration reference at https://huggingface.co./docs/hub/spaces-config-reference | |
| # AI Plant Vision | |
| ## 🌿 Overview | |
| AI Plant Vision is a Gradio-based web application that allows users to identify plants from images and retrieve detailed information about them in either English or Arabic. The system leverages a zero-shot image classification model and a text generation model to provide accurate plant identification and rich informational content. | |
| ## 🚀 Features | |
| - Upload an image to identify a plant. | |
| - Supports multiple plant types such as Lavender, Aloe Vera, Mint, and Orchids. | |
| - Provides detailed plant information, including scientific name, growing conditions, common uses, and care tips. | |
| - Supports English and Arabic languages. | |
| - Uses advanced AI models for classification and text generation. | |
| - Optimized for fast GPU-based inference to enhance performance. | |
| - Modular pipeline for easy scalability and future model improvements. | |
| ## 🛠️ Installation & Setup | |
| ### Prerequisites | |
| Ensure you have Python installed on your system (>=3.8). | |
| ### Step 1: Clone the Repository | |
| ```bash | |
| git clone https://huggingface.co./spaces/fadiyahalanazi/AI-plant-vision | |
| ``` | |
| ### Step 2: Create a Virtual Environment (Optional but Recommended) | |
| ```bash | |
| python -m venv venv | |
| source venv/bin/activate # On Windows use `venv\Scripts\activate` | |
| ``` | |
| ### Step 3: Install Dependencies | |
| The script automatically installs required packages. However, you can also install them manually: | |
| ```bash | |
| pip install -r requirements.txt | |
| ``` | |
| ### Step 4: Run the Application | |
| ```bash | |
| python app.py | |
| ``` | |
| ## 📜 How It Works | |
| 1. Upload a plant image. | |
| 2. Choose your preferred language (English/Arabic). | |
| 3. Click the **"Identify & Get Info"** button. | |
| 4. The app classifies the plant and fetches detailed information. | |
| ## 📌 Technologies Used | |
| - **Python** - Primary language for implementation. | |
| - **Transformers** - Utilized for image classification and text generation. | |
| - **Gradio** - Provides an interactive user interface. | |
| - **Torch** - Facilitates deep learning model computations. | |
| - **Hugging Face Spaces** - Used for deployment with GPU acceleration. | |
| ## 🖼️ User Interface | |
| The app features a clean and responsive UI with: | |
| - Custom styling. | |
| - Intuitive controls for image input and language selection. | |
| - Instant plant identification and information retrieval. | |
| ## 🔥 Model Details | |
| - **Image Classification Model**: `umutbozdag/plant-identity` | |
| - **Text Generation Models**: | |
| - English: `microsoft/Phi-3-mini-4k-instruct` | |
| - Arabic: `ALLaM-AI/ALLaM-7B-Instruct-preview` | |