143 lines
4.7 KiB
Python
143 lines
4.7 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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深入分析相机设备的行为
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"""
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import cv2
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import numpy as np
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import time
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def analyze_camera_frame(frame, device_index):
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"""
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分析相机帧的特征
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"""
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print(f"\n=== 设备 {device_index} 帧分析 ===")
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print(f"帧形状: {frame.shape}")
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print(f"数据类型: {frame.dtype}")
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print(f"数据范围: {frame.min()} - {frame.max()}")
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# 检查是否是纯色帧（可能是虚拟设备）
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unique_colors = len(np.unique(frame.reshape(-1, frame.shape[-1]), axis=0))
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print(f"唯一颜色数量: {unique_colors}")
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# 检查帧的统计信息
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mean_values = np.mean(frame, axis=(0, 1))
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std_values = np.std(frame, axis=(0, 1))
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print(f"各通道均值: {mean_values}")
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print(f"各通道标准差: {std_values}")
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# 检查是否是静态帧
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if np.all(std_values < 1.0):
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print("⚠️ 这可能是一个静态/虚拟帧（标准差很小）")
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# 检查是否是纯黑帧
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if np.all(mean_values < 10):
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print("⚠️ 这可能是一个黑色帧")
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# 检查帧的变化
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return frame
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def test_camera_devices():
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"""
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测试多个相机设备并比较帧内容
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"""
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print("=== 相机设备详细分析 ===")
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devices_to_test = [0, 1]
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frames = {}
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for device_index in devices_to_test:
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print(f"\n--- 测试设备 {device_index} ---")
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try:
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cap = cv2.VideoCapture(device_index, cv2.CAP_DSHOW)
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if cap.isOpened():
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print(f"设备 {device_index}: 成功打开")
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# 获取设备属性
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width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
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height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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fps = cap.get(cv2.CAP_PROP_FPS)
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fourcc = int(cap.get(cv2.CAP_PROP_FOURCC))
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print(f"分辨率: {width}x{height}")
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print(f"帧率: {fps}")
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print(f"编码: {fourcc}")
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# 读取多帧进行分析
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frames_list = []
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for i in range(5):
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ret, frame = cap.read()
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if ret and frame is not None:
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frames_list.append(frame.copy())
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if i == 0: # 只分析第一帧
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frames[device_index] = analyze_camera_frame(frame, device_index)
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else:
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print(f"第{i+1}帧读取失败")
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break
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# 检查帧间变化
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if len(frames_list) > 1:
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diff = cv2.absdiff(frames_list[0], frames_list[-1])
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total_diff = np.sum(diff)
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print(f"首末帧差异总和: {total_diff}")
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if total_diff < 1000: # 阈值可调整
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print("⚠️ 帧内容几乎没有变化，可能是虚拟设备")
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else:
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print("✓ 帧内容有变化，可能是真实相机")
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else:
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print(f"设备 {device_index}: 无法打开")
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cap.release()
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except Exception as e:
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print(f"设备 {device_index} 测试异常: {e}")
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# 比较不同设备的帧
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if 0 in frames and 1 in frames:
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print("\n=== 设备间帧比较 ===")
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diff = cv2.absdiff(frames[0], frames[1])
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total_diff = np.sum(diff)
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print(f"设备0和设备1帧差异总和: {total_diff}")
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if total_diff < 1000:
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print("⚠️ 两个设备的帧几乎相同，设备1可能是设备0的镜像或虚拟设备")
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else:
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print("✓ 两个设备的帧不同，可能是独立的相机")
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def check_system_cameras():
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"""
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检查系统中可用的相机设备
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"""
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print("\n=== 系统相机设备检查 ===")
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available_cameras = []
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# 测试前10个设备索引
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for i in range(10):
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cap = cv2.VideoCapture(i, cv2.CAP_DSHOW)
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if cap.isOpened():
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ret, _ = cap.read()
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if ret:
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available_cameras.append(i)
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print(f"设备 {i}: 可用")
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else:
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print(f"设备 {i}: 打开但无法读取")
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else:
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print(f"设备 {i}: 不可用")
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cap.release()
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# 避免测试太多设备
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if len(available_cameras) >= 3:
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break
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print(f"\n发现 {len(available_cameras)} 个可用相机设备: {available_cameras}")
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return available_cameras
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if __name__ == "__main__":
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check_system_cameras()
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test_camera_devices() |