debug: print YOLO output values and max confidence

internal/captcha/handler.go

@@ -885,6 +885,13 @@ func (h *Handler) detectYOLO(modelName, imageBase64 string) (*DetectionResult, e
 		return nil, err
 	}
 
+	// DEBUG: 打印 ONNX 输出的前 20 个值
+	fmt.Printf("DEBUG YOLO output first 20 values: ")
+	for i := 0; i < 20 && i < len(output); i++ {
+		fmt.Printf("%.4f ", output[i])
+	}
+	fmt.Println()
+
 	// YOLO11 输出: [1, 5, 8400] 或 [1, 84, 8400]
 	// 需要转置 + NMS 后处理，坐标从 640x640 缩放到原图尺寸
 	// 对于小图片（order 提示图）使用更低的置信度阈值
@@ -972,6 +979,9 @@ func postprocessYOLO(output []float32, origW, origH int, confThresh, nmsThresh f
 
 	detections := []YOLODetection{}
 
+	// 记录最大置信度用于调试
+	maxConf := 0.0
+
 	// 遍历所有检测框
 	for i := 0; i < numBoxes; i++ {
 		// YOLO11 输出是 [features, boxes]，需要转置访问
@@ -984,6 +994,10 @@ func postprocessYOLO(output []float32, origW, origH int, confThresh, nmsThresh f
 		}
 		confidence := float64(output[confIdx])
 
+		if confidence > maxConf {
+			maxConf = confidence
+		}
+
 		if confidence < confThresh {
 			continue
 		}
@@ -1032,6 +1046,8 @@ func postprocessYOLO(output []float32, origW, origH int, confThresh, nmsThresh f
 		})
 	}
 
+	fmt.Printf("DEBUG YOLO postprocess: outputLen=%d, numFeatures=%d, maxConf=%.4f, found=%d\n", outputLen, numFeatures, maxConf, len(detections))
+
 	// NMS
 	return nms(detections, nmsThresh)
 }