alter

Former-commit-id: 0d9b33e7625efe7bee422d1514d8453ff689553d

test.py

@@ -0,0 +1,67 @@
+import cv2
+import numpy as np
+from matplotlib import pyplot as plt
+from scipy.signal import find_peaks
+
+cap = cv2.VideoCapture(1)  # 使用摄像头0，通常更稳定
+cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)  # 降低分辨率提高处理速度
+cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
+
+# 预先创建图形窗口，避免重复创建
+fig, ax = plt.subplots(figsize=(10, 4))
+plt.ion()
+ax.set_title('Saturation Channel Histogram')
+ax.set_xlabel('Saturation Value')
+ax.set_ylabel('Pixel Count')
+ax.set_xlim(0, 255)
+
+while True:
+    ret, frame = cap.read()
+    if not ret:
+        print("Failed to grab frame")
+        break
+    
+    cv2.imshow("Camera Feed", frame)
+    
+    # 直接提取饱和度通道，避免完整HSV转换
+    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
+    s = hsv[:, :, 1]
+    s = s[s > 0]  # 只保留非零饱和度值，减少噪声
+      # 使用更高效的直方图计算
+    hist = cv2.calcHist([s], [0], None, [256], [0, 256])
+    hist = hist.flatten()  # 转换为一维数组
+    
+    # 峰值检测 - 找到直方图中的峰值
+    peaks, properties = find_peaks(hist, 
+                                #  height=np.max(hist) * 0.1,  # 峰值高度至少是最大值的10%
+                                 distance=5,  # 峰值之间的最小距离
+                                 prominence=np.max(hist) * 0.05)  # 峰值的突出度
+    
+    # 清除旧数据并绘制新直方图
+    ax.clear()
+    ax.plot(hist, 'b-', linewidth=1)
+    
+    # 标注峰值
+    if len(peaks) > 0:
+        ax.text(0.5, 1.05, f'Found {len(peaks)} peaks')
+        ax.plot(peaks, hist[peaks], 'ro', markersize=8, label=f'Peaks ({len(peaks)})')
+        # 在峰值处添加文字标注
+        for i, peak in enumerate(peaks):
+            ax.annotate(f'Peak {i+1}\n({peak}, {int(hist[peak])})', 
+                       xy=(peak, hist[peak]), 
+                       xytext=(peak, hist[peak] + np.max(hist) * 0.1),
+                       ha='center', va='bottom',
+                       bbox=dict(boxstyle='round,pad=0.3', facecolor='yellow', alpha=0.7),
+                       arrowprops=dict(arrowstyle='->', color='red'))
+
+    
+    plt.draw()
+    plt.pause(0.1)  # 确保图形更新
+    
+    key = cv2.waitKey(1) & 0xFF
+    if key == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()
+plt.close('all')