测试文件提交

yolo_test.py

@@ -161,6 +161,9 @@ def yolo_shibie(im_PIL, detections, model, enhance_enabled=False, enhance_params
 
         # ✅ 提取检测信息
         if result.boxes is not None and len(result.boxes.xyxy) > 0:
+            # 用于存储多个候选npc4（如果检测到多个）
+            npc4_candidates = []
+            
             for i in range(len(result.boxes.xyxy)):
                 try:
                     left = float(result.boxes.xyxy[i][0])
@@ -169,11 +172,37 @@ def yolo_shibie(im_PIL, detections, model, enhance_enabled=False, enhance_params
                     bottom = float(result.boxes.xyxy[i][3])
                     cls_id = int(result.boxes.cls[i])
                     label = result.names[cls_id]
+                    
+                    # 获取置信度（如果可用）
+                    confidence = float(result.boxes.conf[i]) if hasattr(result.boxes, 'conf') and len(result.boxes.conf) > i else 1.0
 
-                    if label in ['center', 'next', 'npc1', 'npc2', 'npc3', 'npc4', 'boss', 'zhaozi']:
+                    # npc1-npc4 使用底部位置（与main.py保持一致）
+                    if label in ['npc1', 'npc2', 'npc3', 'npc4']:
+                        player_x = int(left + (right - left) / 2)
+                        player_y = int(bottom) + 30  # 使用底部位置，与main.py保持一致
+                        position = [player_x, player_y]
+                        
+                        # 特殊处理npc4：如果检测到多个，收集所有候选
+                        if label == 'npc4':
+                            npc4_candidates.append({
+                                'position': position,
+                                'confidence': confidence,
+                                'box': [left, top, right, bottom],
+                                'area': (right - left) * (bottom - top)  # 检测框面积
+                            })
+                        else:
+                            # npc1-npc3直接赋值（如果已经有值，保留置信度更高的）
+                            if detections[label] is None or (hasattr(result.boxes, 'conf') and 
+                                                              confidence > 0.5):
+                                detections[label] = position
+                    
+                    # 其他目标使用中心点
+                    elif label in ['center', 'next', 'boss', 'zhaozi']:
                         player_x = int(left + (right - left) / 2) + 3
                         player_y = int(top + (bottom - top) / 2) + 40
                         detections[label] = [player_x, player_y]
+                    
+                    # 道具和怪物可以多个
                     elif label in ['daojv', 'gw']:
                         player_x = int(left + (right - left) / 2) + 3
                         player_y = int(top + (bottom - top) / 2) + 40
@@ -181,9 +210,34 @@ def yolo_shibie(im_PIL, detections, model, enhance_enabled=False, enhance_params
                         if label not in detections:
                             detections[label] = []
                         detections[label].append([player_x, player_y])
+                        
                 except Exception as e:
                     print(f"⚠️ 处理检测框时出错: {e}")
                     continue
+            
+            # 处理npc4：如果检测到多个，选择最合适的
+            if npc4_candidates:
+                # 按置信度排序，选择置信度最高的
+                npc4_candidates.sort(key=lambda x: x['confidence'], reverse=True)
+                
+                # 选择最佳候选（置信度最高且面积合理）
+                best_npc4 = None
+                for candidate in npc4_candidates:
+                    # 置信度阈值：至少0.3（可根据实际情况调整）
+                    if candidate['confidence'] >= 0.3:
+                        # 检查检测框面积是否合理（避免过小的误检）
+                        area = candidate['area']
+                        if area > 100:  # 最小面积阈值
+                            best_npc4 = candidate
+                            break
+                
+                if best_npc4:
+                    detections['npc4'] = best_npc4['position']
+                    # 可选：输出调试信息
+                    # print(f"✅ 检测到npc4: 位置={best_npc4['position']}, 置信度={best_npc4['confidence']:.2f}")
+                elif len(npc4_candidates) == 1:
+                    # 如果只有一个候选，即使置信度较低也使用
+                    detections['npc4'] = npc4_candidates[0]['position']
 
     except Exception as e:
         print(f"⚠️ YOLO检测出错: {e}")