cluster4npu/tests/debug_detection_issues.py

#!/usr/bin/env python3
"""
Debug script to investigate abnormal detection results.
檢查異常偵測結果的調試腳本。
"""

import sys
import os
sys.path.append(os.path.dirname(os.path.abspath(__file__)))

from core.functions.Multidongle import BoundingBox, ObjectDetectionResult

def analyze_detection_result(result: ObjectDetectionResult):
    """分析偵測結果，找出異常情況"""
    print("=== DETECTION RESULT ANALYSIS ===")
    print(f"Class count: {result.class_count}")
    print(f"Box count: {result.box_count}")
    
    if not result.box_list:
        print("No bounding boxes found.")
        return
    
    # 統計分析
    class_counts = {}
    coordinate_issues = []
    score_issues = []
    
    for i, box in enumerate(result.box_list):
        # 統計每個類別的數量
        class_counts[box.class_name] = class_counts.get(box.class_name, 0) + 1
        
        # 檢查座標問題
        if box.x1 < 0 or box.y1 < 0 or box.x2 < 0 or box.y2 < 0:
            coordinate_issues.append(f"Box {i}: Negative coordinates ({box.x1},{box.y1},{box.x2},{box.y2})")
        
        if box.x1 >= box.x2 or box.y1 >= box.y2:
            coordinate_issues.append(f"Box {i}: Invalid box dimensions ({box.x1},{box.y1},{box.x2},{box.y2})")
        
        if box.x1 == box.x2 and box.y1 == box.y2:
            coordinate_issues.append(f"Box {i}: Zero-area box ({box.x1},{box.y1},{box.x2},{box.y2})")
        
        # 檢查分數問題
        if box.score < 0 or box.score > 1:
            score_issues.append(f"Box {i}: Unusual score {box.score} for {box.class_name}")
    
    # 報告結果
    print("\n--- CLASS DISTRIBUTION ---")
    for class_name, count in sorted(class_counts.items()):
        if count > 50:  # 標記異常高的數量
            print(f"⚠ {class_name}: {count} (ABNORMALLY HIGH)")
        else:
            print(f"✓ {class_name}: {count}")
    
    print(f"\n--- COORDINATE ISSUES ({len(coordinate_issues)}) ---")
    for issue in coordinate_issues[:10]:  # 只顯示前10個
        print(f"⚠ {issue}")
    if len(coordinate_issues) > 10:
        print(f"... and {len(coordinate_issues) - 10} more coordinate issues")
    
    print(f"\n--- SCORE ISSUES ({len(score_issues)}) ---")
    for issue in score_issues[:10]:  # 只顯示前10個
        print(f"⚠ {issue}")
    if len(score_issues) > 10:
        print(f"... and {len(score_issues) - 10} more score issues")
    
    # 建議
    print("\n--- RECOMMENDATIONS ---")
    if any(count > 50 for count in class_counts.values()):
        print("⚠ Abnormally high detection counts suggest:")
        print("  1. Model output format mismatch")
        print("  2. Confidence threshold too low")
        print("  3. Test/debug mode accidentally enabled")
    
    if coordinate_issues:
        print("⚠ Coordinate issues suggest:")
        print("  1. Coordinate transformation problems")
        print("  2. Model output scaling issues")
        print("  3. Hardware preprocessing info missing")
    
    if score_issues:
        print("⚠ Score issues suggest:")
        print("  1. Score values might be in log space")
        print("  2. Wrong score interpretation")
        print("  3. Need score normalization")

def create_mock_problematic_result():
    """創建一個模擬的有問題的偵測結果用於測試"""
    boxes = []
    
    # 模擬您遇到的問題
    class_names = ['person', 'bicycle', 'car', 'motorbike', 'aeroplane', 'bus', 'toothbrush', 'hair drier']
    
    # 添加大量異常的邊界框
    for i in range(100):
        box = BoundingBox(
            x1=i % 5,  # 很小的座標
            y1=(i + 1) % 4,
            x2=(i + 2) % 6,
            y2=(i + 3) % 5,
            score=2.0 + (i * 0.1),  # 異常的分數值
            class_num=i % len(class_names),
            class_name=class_names[i % len(class_names)]
        )
        boxes.append(box)
    
    return ObjectDetectionResult(
        class_count=len(class_names),
        box_count=len(boxes),
        box_list=boxes
    )

def suggest_fixes():
    """提供修復建議"""
    print("\n=== SUGGESTED FIXES ===")
    
    print("\n1. 檢查模型配置:")
    print("   - 確認使用正確的後處理類型（YOLO_V3, YOLO_V5, etc.）")
    print("   - 檢查類別名稱列表是否正確")
    print("   - 驗證信心閾值設定（建議 0.3-0.7）")
    
    print("\n2. 檢查座標轉換:")
    print("   - 確認模型輸出格式（中心座標 vs 角點座標）")
    print("   - 檢查圖片尺寸縮放")
    print("   - 驗證硬體預處理信息")
    
    print("\n3. 添加結果過濾:")
    print("   - 過濾無效座標的邊界框")
    print("   - 限制每個類別的最大檢測數量")
    print("   - 添加 NMS（非極大值抑制）")
    
    print("\n4. 調試步驟:")
    print("   - 添加詳細的調試日誌")
    print("   - 檢查原始模型輸出")
    print("   - 測試不同的後處理參數")

if __name__ == "__main__":
    print("Detection Issues Debug Tool")
    print("=" * 50)
    
    # 測試與您遇到類似問題的模擬結果
    print("Testing with mock problematic result...")
    mock_result = create_mock_problematic_result()
    analyze_detection_result(mock_result)
    
    suggest_fixes()
    
    print("\nTo use this tool with real results:")
    print("from debug_detection_issues import analyze_detection_result")
    print("analyze_detection_result(your_detection_result)")