cluster4npu/example_postprocess_options.py

#!/usr/bin/env python3
"""
Example demonstrating the new default postprocess options in the app.

This script shows how to use the different postprocessing types:
- Fire detection (classification)
- YOLO v3/v5 (object detection with bounding boxes)
- General classification
- Raw output

The postprocessing options are built-in to the app and provide text output
and bounding box visualization in live view windows.
"""

import sys
import os

# Add the project root to Python path
sys.path.insert(0, os.path.dirname(__file__))

from core.functions.Multidongle import (
    MultiDongle, 
    PostProcessorOptions, 
    PostProcessType,
    WebcamInferenceRunner
)


def demo_fire_detection():
    """Demo fire detection postprocessing (default)"""
    print("=== Fire Detection Demo ===")
    
    # Configure for fire detection
    options = PostProcessorOptions(
        postprocess_type=PostProcessType.FIRE_DETECTION,
        threshold=0.5,
        class_names=["No Fire", "Fire"]
    )
    
    print(f"Postprocess type: {options.postprocess_type.value}")
    print(f"Threshold: {options.threshold}")
    print(f"Class names: {options.class_names}")
    return options


def demo_yolo_object_detection():
    """Demo YOLO object detection with bounding boxes"""
    print("=== YOLO Object Detection Demo ===")
    
    # Configure for YOLO v5 object detection
    options = PostProcessorOptions(
        postprocess_type=PostProcessType.YOLO_V5,
        threshold=0.3,
        class_names=["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck"],
        nms_threshold=0.5,
        max_detections_per_class=50
    )
    
    print(f"Postprocess type: {options.postprocess_type.value}")
    print(f"Detection threshold: {options.threshold}")
    print(f"NMS threshold: {options.nms_threshold}")
    print(f"Class names: {options.class_names[:5]}...")  # Show first 5
    return options


def demo_general_classification():
    """Demo general classification"""
    print("=== General Classification Demo ===")
    
    # Configure for general classification
    options = PostProcessorOptions(
        postprocess_type=PostProcessType.CLASSIFICATION,
        threshold=0.6,
        class_names=["cat", "dog", "bird", "fish", "horse"]
    )
    
    print(f"Postprocess type: {options.postprocess_type.value}")
    print(f"Threshold: {options.threshold}")
    print(f"Class names: {options.class_names}")
    return options


def main():
    """Main demo function"""
    print("Default Postprocess Options Demo")
    print("=" * 40)
    
    # Demo different postprocessing options
    fire_options = demo_fire_detection()
    print()
    
    yolo_options = demo_yolo_object_detection()
    print()
    
    classification_options = demo_general_classification()
    print()
    
    # Example of how to initialize MultiDongle with options
    print("=== MultiDongle Integration Example ===")
    
    # NOTE: Update these paths according to your setup
    PORT_IDS = [28, 32]  # Update with your device port IDs
    SCPU_FW = 'fw_scpu.bin'  # Update with your firmware path
    NCPU_FW = 'fw_ncpu.bin'  # Update with your firmware path
    MODEL_PATH = 'your_model.nef'  # Update with your model path
    
    try:
        # Example 1: Fire detection (default)
        print("Initializing with fire detection...")
        multidongle_fire = MultiDongle(
            port_id=PORT_IDS,
            scpu_fw_path=SCPU_FW,
            ncpu_fw_path=NCPU_FW,
            model_path=MODEL_PATH,
            upload_fw=False,  # Set to True if you need firmware upload
            postprocess_options=fire_options
        )
        print(f"✓ Fire detection configured: {multidongle_fire.postprocess_options.postprocess_type.value}")
        
        # Example 2: Change postprocessing options dynamically
        print("Changing to YOLO detection...")
        multidongle_fire.set_postprocess_options(yolo_options)
        print(f"✓ YOLO detection configured: {multidongle_fire.postprocess_options.postprocess_type.value}")
        
        # Example 3: Get available types
        available_types = multidongle_fire.get_available_postprocess_types()
        print(f"Available postprocess types: {[t.value for t in available_types]}")
        
    except Exception as e:
        print(f"Note: MultiDongle initialization skipped (no hardware): {e}")
    
    print("\n=== Usage Notes ===")
    print("1. Fire detection option is set as default")
    print("2. Text output shows classification results with probabilities")
    print("3. Bounding box output visualizes detected objects in live view")
    print("4. All postprocessing is built-in to the app (no external dependencies)")
    print("5. Exact nodes can configure postprocessing through UI properties")


if __name__ == "__main__":
    main()