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