Update Dockerfile

Dockerfile

@@ -4,42 +4,83 @@ emoji: 🌍
 colorFrom: blue
 colorTo: purple
 sdk: streamlit
-sdk_version: 1.28.1
+sdk_version: "1.28.1"
 app_file: app.py
 pinned: false
 ---
 
-# 🌍 Multilingual Image Describer
+# 🌍 Multilingual Image Describer with Real Translation
 
-A powerful web application for object detection and multilingual image description deployed on Hugging Face Spaces.
+A powerful web application that analyzes images to detect objects and generate descriptions in **14 different languages** with real translation capabilities.
 
-## 🚀 Features
-- **📸 Multiple Input Methods**: Upload, camera, or sample images
-- **🌍 13 Languages**: English, Spanish, French, German, Chinese, Hindi, Arabic, and more
-- **🔍 Real-time Object Detection**: Powered by YOLOv8
-- **📝 Intelligent Captioning**: Using BLIP model from Salesforce
-- **📊 Interactive Analytics**: Charts, statistics, and visualizations
-- **💾 Export Options**: Download results as JSON or TXT
+## ✨ Features
+- **Real-time Translation**: Uses Hugging Face NLLB model for accurate translations
+- **Object Detection**: Powered by YOLOv8 with confidence scores
+- **Image Captioning**: Generates natural language descriptions using BLIP
+- **14 Languages**: English, Spanish, French, German, Chinese, Hindi, Arabic, Russian, Japanese, Korean, Portuguese, Italian, Amharic, Turkish
+- **Export Results**: Download analysis as JSON or TXT files
 
-## 🛠️ Tech Stack
-- **Frontend**: Streamlit
-- **AI Models**:
-  - BLIP (Salesforce) - Image captioning
-  - YOLOv8 (Ultralytics) - Object detection
-- **Deployment**: Hugging Face Spaces
+## 🚀 How to Use
 
-## 📋 How to Use
-1. **Upload Image**: Drag & drop or click to upload
-2. **Select Language**: Choose from available languages
-3. **Generate**: Click the "Generate Description" button
-4. **Explore**: View results across multiple tabs
-5. **Export**: Download results as JSON or TXT
+### 1. Upload Image
+- Click "Upload" to select an image file
+- Use "Camera" to capture a photo
+- Try "Sample" for a demo image
 
-## 🔧 Configuration Notes
-The settings above (title, emoji, SDK, etc.) are configured in the YAML block at the top of this file.
+### 2. Configure Settings
+- **Select Language**: Choose from 14 available languages
+- **API Token**: Optional Hugging Face token for better translation
+- **Confidence**: Adjust object detection sensitivity
 
-For additional configuration options, refer to the [Spaces configuration reference](https://huggingface.co/docs/hub/spaces-config-reference)[citation:2].
+### 3. Analyze
+- Click "🚀 Analyze Image" to process
+- View results in Description, Objects, and Export tabs
+- Download results for later use
 
----
+## 🔧 Translation Setup
+
+For best translation results:
+
+1. **Get a free Hugging Face token**:
+   - Visit [huggingface.co/settings/tokens](https://huggingface.co/settings/tokens)
+   - Create a new token (select "Read" permission)
+   - Copy the token (starts with `hf_`)
+
+2. **Enter token in the app**:
+   - Paste token in the "Hugging Face Token" field in sidebar
+   - Token is stored locally for your session
+
+## 🌐 Supported Languages
+
+| Language | Code | Support |
+|----------|------|---------|
+| English | en | ✅ Full |
+| Spanish | es | ✅ Full |
+| French | fr | ✅ Full |
+| German | de | ✅ Full |
+| Chinese | zh | ✅ Full |
+| Hindi | hi | ✅ Full |
+| Arabic | ar | ✅ Full |
+| Russian | ru | ✅ Full |
+| Japanese | ja | ✅ Full |
+| Korean | ko | ✅ Full |
+| Portuguese | pt | ✅ Full |
+| Italian | it | ✅ Full |
+| Amharic | am | ✅ Full |
+| Turkish | tr | ✅ Full |
+
+## 📊 Technical Details
+
+- **Image Models**: BLIP (captioning) + YOLOv8 (detection)
+- **Translation**: Facebook NLLB-200-distilled-600M via Hugging Face Inference API
+- **Framework**: Streamlit + Python 3.10
+- **Deployment**: Hugging Face Spaces
+
+## 🛠️ Development
 
-Built with ❤️ by UCAS @2025 | Powered by Hugging Face Spaces
+### Local Setup
+```bash
+git clone https://huggingface.co/spaces/amogneandualem/amogne-vlm-LLM
+cd amogne-vlm-LLM
+pip install -r requirements.txt
+streamlit run app.py