Implement Nuclio serverless function for CVAT integration with AOC Fruit Detector

.gitignore

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 # Emacs
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+# Python cache
+__pycache__/
+
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nuclio_function/CVAT_INTEGRATION.md

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+# CVAT Integration Example
+
+This document provides an example of how to integrate the AOC Fruit Detector nuclio function with CVAT.
+
+## Prerequisites
+
+1. CVAT is installed and running
+2. Nuclio is installed in your Kubernetes cluster or Docker environment
+3. AOC Fruit Detector nuclio function is deployed
+
+## Step 1: Deploy the Function
+
+```bash
+cd nuclio_function
+./deploy.sh
+```
+
+Note the function endpoint URL from the deployment output.
+
+## Step 2: Configure CVAT Model
+
+1. **Access CVAT Admin Interface**
+   - Go to CVAT admin panel (usually at `http://your-cvat-url/admin`)
+   - Login with admin credentials
+
+2. **Add New Model**
+   - Navigate to `Models` → `Add Model`
+   - Fill in the following details:
+
+   ```
+   Name: AOC Fruit Detector
+   Owner: <your-username>
+   URL: http://<nuclio-function-endpoint>
+   Labels: strawberry,tomato,apple,pear
+   Model type: Detector
+   Storage method: Local
+   Enabled: ✓
+   ```
+
+3. **Configure Labels**
+   Create labels that match your fruit detection types:
+   ```
+   - strawberry
+   - strawberry_ripe
+   - strawberry_unripe
+   - strawberry_overripe
+   - tomato
+   - tomato_ripe
+   - tomato_unripe
+   - tomato_overripe
+   ```
+
+## Step 3: Use in CVAT Tasks
+
+1. **Create or Open Task**
+   - Create a new task or open an existing one
+   - Upload images containing fruits
+
+2. **Run Automatic Annotation**
+   - Go to `Actions` → `Automatic Annotation`
+   - Select "AOC Fruit Detector" from the model dropdown
+   - Configure parameters:
+     ```
+     Threshold: 0.5 (adjust based on your needs)
+     Maximum annotations per frame: 100
+     ```
+   - Click "Submit"
+
+3. **Review Results**
+   - The function will process each frame
+   - Review and adjust annotations as needed
+   - Use CVAT's annotation tools to refine results
+
+## Example API Request
+
+For direct testing, you can send requests to the nuclio function:
+
+```bash
+# Test with a sample image
+curl -X POST \
+  -H "Content-Type: application/json" \
+  -d '{
+    "image": "'$(base64 -w 0 /path/to/fruit_image.jpg)'",
+    "threshold": 0.5
+  }' \
+  http://<nuclio-function-endpoint>
+```
+
+Expected response:
+```json
+[
+  {
+    "confidence": 0.95,
+    "label": "strawberry_ripe",
+    "points": [123.4, 56.7, 234.5, 167.8],
+    "type": "rectangle",
+    "attributes": {
+      "variety": "unknown",
+      "quality": "High",
+      "ripeness_category": "Ripe",
+      "ripeness_level": 0.85
+    }
+  }
+]
+```
+
+## Troubleshooting
+
+### Common Issues
+
+1. **Function Not Responding**
+   - Check if nuclio function is running: `nuctl get functions`
+   - Check function logs: `nuctl logs aoc-fruit-detector`
+
+2. **No Detections Returned**
+   - Lower the confidence threshold
+   - Check if fruit detector ROS2 node is running
+   - Verify ROS2 domain configuration
+
+3. **CVAT Integration Issues**
+   - Ensure function URL is accessible from CVAT
+   - Check CVAT logs for error messages
+   - Verify model configuration in CVAT admin panel
+
+### Performance Tuning
+
+1. **Confidence Threshold**
+   - Start with 0.5 and adjust based on results
+   - Lower values will detect more objects but may include false positives
+
+2. **Function Resources**
+   - Adjust CPU/memory limits in `function.yaml`
+   - Scale replicas based on load requirements
+
+3. **Timeout Settings**
+   - Increase timeout in ROS2 bridge if processing is slow
+   - Configure CVAT model timeout appropriately
+
+## Advanced Configuration
+
+### Custom Labels
+
+To add custom fruit types or ripeness categories:
+
+1. **Update the converter**
+   Edit `cvat_converter.py` to add new fruit type mappings:
+   ```python
+   self.fruit_type_mapping = {
+       'strawberry': 'strawberry',
+       'tomato': 'tomato',
+       'apple': 'apple',      # Add new types
+       'pear': 'pear',
+       # ... more types
+   }
+   ```
+
+2. **Rebuild and redeploy**
+   ```bash
+   docker build -t aoc-fruit-detector:latest .
+   nuctl deploy aoc-fruit-detector --run-image aoc-fruit-detector:latest
+   ```
+
+3. **Update CVAT labels**
+   Add corresponding labels in CVAT model configuration
+
+### Multi-Model Setup
+
+You can deploy multiple versions of the function for different use cases:
+
+```bash
+# Deploy for strawberries only
+nuctl deploy aoc-strawberry-detector --env FRUIT_TYPE=strawberry
+
+# Deploy for tomatoes only  
+nuctl deploy aoc-tomato-detector --env FRUIT_TYPE=tomato
+```

nuclio_function/Dockerfile

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+# Dockerfile for nuclio function deployment
+FROM ros:humble-base
+
+# Set environment variables
+ENV PYTHONUNBUFFERED=1
+ENV ROS_DISTRO=humble
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    python3-pip \
+    python3-dev \
+    python3-opencv \
+    python3-numpy \
+    python3-pil \
+    python3-colcon-common-extensions \
+    ros-humble-cv-bridge \
+    ros-humble-sensor-msgs \
+    ros-humble-geometry-msgs \
+    ros-humble-std-msgs \
+    ros-humble-visualization-msgs \
+    && rm -rf /var/lib/apt/lists/*
+
+# Create workspace for AOC messages
+WORKDIR /opt/ros_ws
+RUN mkdir -p src/aoc_fruit_detector
+
+# Copy package files for building messages
+COPY ../CMakeLists.txt src/aoc_fruit_detector/
+COPY ../package.xml src/aoc_fruit_detector/
+COPY ../msg src/aoc_fruit_detector/msg/
+
+# Build the AOC message package
+RUN bash -c "source /opt/ros/humble/setup.bash && colcon build --packages-select aoc_fruit_detector"
+
+# Set working directory for function
+WORKDIR /opt/nuclio
+
+# Copy function files
+COPY main.py .
+COPY ros2_bridge.py .
+COPY cvat_converter.py .
+COPY requirements.txt .
+
+# Install Python dependencies
+RUN pip3 install --no-cache-dir -r requirements.txt
+
+# Set up environment for ROS2
+ENV ROS_DOMAIN_ID=0
+ENV RMW_IMPLEMENTATION=rmw_cyclonedx_cpp
+ENV PYTHONPATH="/opt/ros_ws/install/aoc_fruit_detector/lib/python3.10/site-packages:${PYTHONPATH}"
+
+# Source both ROS2 and AOC messages setup
+RUN echo "source /opt/ros/humble/setup.bash" >> ~/.bashrc && \
+    echo "source /opt/ros_ws/install/setup.bash" >> ~/.bashrc
+
+# Expose port for nuclio
+EXPOSE 8080
+
+# Set entrypoint
+CMD ["/bin/bash", "-c", "source /opt/ros/humble/setup.bash && source /opt/ros_ws/install/setup.bash && python3 main.py"]