Merge remote-tracking branch 'origin/ui' into ui
This commit is contained in:
Administrator
@@ -82,6 +82,21 @@ def main():
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group = groups[idx]
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logger.info(f" • {group['name']} (串口:{group['serial_port']}, 采集卡:{group['camera_index']})")
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# 串口冲突预检：同一串口被多个组占用通常会导致仅一路成功
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port_to_groups = {}
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for idx in selected_indices:
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g = groups[idx]
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port_to_groups.setdefault(g['serial_port'], []).append(g['name'])
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conflicts = {p: names for p, names in port_to_groups.items() if p and len(names) > 1}
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if conflicts:
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logger.warning("⚠️ 检测到串口冲突（同一COM被多个组使用）：")
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for p, names in conflicts.items():
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logger.warning(f" {p}: {', '.join(names)}")
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go_on = input("上述冲突很可能导致仅一组成功，其它失败。仍要继续? (y/n): ").strip().lower()
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if go_on != 'y':
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logger.info("已取消启动以避免串口冲突")
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return
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confirm = input("\n确认启动? (y/n): ").strip().lower()
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if confirm != 'y':
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logger.info("❌ 取消启动")
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796
test_capture_card.py
Normal file
796
test_capture_card.py
Normal file
@@ -0,0 +1,796 @@
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"""
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采集卡截图测试类
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用于测试采集卡的分辨率和色差
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保持与实际代码相同的实现逻辑
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"""
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import time
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import threading
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import warnings
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import os
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import sys
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import io
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import cv2
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import numpy as np
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from PIL import Image
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from utils.logger import logger, throttle
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import logging
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# 抑制OpenCV的警告信息（兼容不同版本）
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os.environ['OPENCV_LOG_LEVEL'] = 'SILENT'
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os.environ['OPENCV_IO_ENABLE_OPENEXR'] = '0'
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try:
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if hasattr(cv2, 'setLogLevel'):
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if hasattr(cv2, 'LOG_LEVEL_SILENT'):
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cv2.setLogLevel(cv2.LOG_LEVEL_SILENT)
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elif hasattr(cv2, 'LOG_LEVEL_ERROR'):
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cv2.setLogLevel(cv2.LOG_LEVEL_ERROR)
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elif hasattr(cv2, 'utils'):
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cv2.utils.setLogLevel(0)
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except Exception:
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pass
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class CaptureCardTester:
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"""
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采集卡测试类
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使用与实际代码相同的实现逻辑
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"""
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def __init__(self, cam_index=0, width=1920, height=1080):
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"""
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初始化采集卡测试器
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:param cam_index: 采集卡索引
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:param width: 期望宽度
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:param height: 期望高度
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"""
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logger.info(f"🔧 正在初始化采集卡测试器 {cam_index}...")
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self.cap = None
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self.frame = None
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self.running = True
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self.cam_index = cam_index
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self.expected_width = width
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self.expected_height = height
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self.actual_width = None
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self.actual_height = None
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# 尝试多种方式打开采集卡（与实际代码相同）
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backends_to_try = [
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(cam_index, cv2.CAP_DSHOW),
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(cam_index, cv2.CAP_ANY),
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(cam_index, None), # 默认后端
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]
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# 重定向stderr来抑制OpenCV的错误输出
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old_stderr = sys.stderr
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suppressed_output = io.StringIO()
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try:
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sys.stderr = suppressed_output
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for idx, backend in backends_to_try:
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try:
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with warnings.catch_warnings():
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warnings.filterwarnings('ignore', category=UserWarning)
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if backend is not None:
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self.cap = cv2.VideoCapture(idx, backend)
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else:
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self.cap = cv2.VideoCapture(idx)
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if self.cap.isOpened():
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# 测试读取一帧
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ret, test_frame = self.cap.read()
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if ret and test_frame is not None:
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logger.info(f"✅ 采集卡 {cam_index} 打开成功")
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break
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else:
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self.cap.release()
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self.cap = None
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except Exception as e:
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if self.cap:
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try:
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self.cap.release()
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except:
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pass
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self.cap = None
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continue
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finally:
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# 恢复stderr
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sys.stderr = old_stderr
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if self.cap is None or not self.cap.isOpened():
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logger.error(f"❌ 无法打开采集卡 {cam_index}")
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logger.error("请检查：\n 1. 采集卡是否正确连接\n 2. 采集卡索引是否正确（尝试扫描采集卡）\n 3. 采集卡驱动是否安装\n 4. 采集卡是否被其他程序占用")
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self.cap = None
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return
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# 设置分辨率（与实际代码相同）
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try:
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self.cap.set(cv2.CAP_PROP_FRAME_WIDTH, width)
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self.cap.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
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# 实际获取设置后的分辨率
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self.actual_width = int(self.cap.get(cv2.CAP_PROP_FRAME_WIDTH))
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self.actual_height = int(self.cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
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logger.info(f" 分辨率设置: {width}x{height} -> 实际: {self.actual_width}x{self.actual_height}")
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except Exception as e:
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logger.warning(f"⚠️ 设置分辨率失败: {e}")
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# 启动更新线程（与实际代码相同）
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threading.Thread(target=self.update, daemon=True).start()
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# 等待几帧确保采集卡正常工作
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time.sleep(1.0)
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logger.info(f"✅ 采集卡 {cam_index} 初始化完成")
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def update(self):
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"""持续更新帧（与实际代码相同）"""
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while self.running and self.cap is not None:
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try:
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ret, frame = self.cap.read()
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if ret and frame is not None:
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self.frame = frame
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# 限制读取频率，避免占满CPU
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time.sleep(0.008)
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else:
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# 读取失败时不打印，避免刷屏
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time.sleep(0.02)
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except Exception as e:
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# 只在异常时打印错误
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throttle(f"cap_read_err_{self.cam_index}", 2.0, logging.WARNING, f"⚠️ 采集卡 {self.cam_index} 读取异常: {e}")
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time.sleep(0.1) # 出错时短暂延迟
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def get_frame(self):
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"""
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获取处理后的帧（与实际代码相同）
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返回: [im_opencv, im_PIL] 或 None
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"""
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if self.cap is None or self.frame is None:
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return None
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try:
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im_opencv = cv2.cvtColor(self.frame, cv2.COLOR_BGR2RGB)
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im_opencv = im_opencv[30:30+720, 0:1280] # 裁剪尺寸（与实际代码相同）
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im_PIL = Image.fromarray(im_opencv)
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return [im_opencv, im_PIL]
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except Exception as e:
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throttle(f"img_proc_err_{self.cam_index}", 2.0, logging.WARNING, f"⚠️ 图像处理错误: {e}")
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return None
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def get_raw_frame(self):
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"""
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获取原始帧（未裁剪）
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返回: numpy array 或 None
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"""
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if self.cap is None or self.frame is None:
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return None
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return self.frame.copy()
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def test_resolution(self):
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"""
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测试分辨率
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返回分辨率信息字典
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"""
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if self.cap is None:
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logger.error("采集卡未初始化")
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return None
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result = {
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'expected': (self.expected_width, self.expected_height),
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'actual_cap': (self.actual_width, self.actual_height),
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'actual_frame': None,
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'cropped_frame': None,
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'match': False
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}
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# 获取原始帧尺寸
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raw_frame = self.get_raw_frame()
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if raw_frame is not None:
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h, w = raw_frame.shape[:2]
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result['actual_frame'] = (w, h)
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# 获取裁剪后帧尺寸
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processed = self.get_frame()
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if processed is not None:
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im_opencv = processed[0]
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h, w = im_opencv.shape[:2]
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result['cropped_frame'] = (w, h)
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# 检查分辨率是否匹配
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if result['actual_cap'] is not None:
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result['match'] = (result['actual_cap'][0] == self.expected_width and
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result['actual_cap'][1] == self.expected_height)
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return result
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def test_color_difference(self, frame1=None, frame2=None):
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"""
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测试色差
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:param frame1: 第一帧（可选，不提供则使用当前帧）
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:param frame2: 第二帧（可选，不提供则等待一帧后获取）
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:return: 色差信息字典
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"""
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if frame1 is None:
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frame1 = self.get_frame()
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if frame1 is None:
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logger.error("无法获取第一帧")
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return None
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frame1 = frame1[0] # 使用opencv格式
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if frame2 is None:
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# 等待一小段时间获取新帧
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time.sleep(0.1)
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frame2 = self.get_frame()
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if frame2 is None:
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logger.error("无法获取第二帧")
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return None
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frame2 = frame2[0] # 使用opencv格式
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# 确保两帧尺寸相同
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if frame1.shape != frame2.shape:
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logger.warning(f"两帧尺寸不同: {frame1.shape} vs {frame2.shape}")
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# 调整尺寸
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h, w = min(frame1.shape[0], frame2.shape[0]), min(frame1.shape[1], frame2.shape[1])
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frame1 = frame1[:h, :w]
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frame2 = frame2[:h, :w]
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# 计算色差
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diff = cv2.absdiff(frame1, frame2)
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diff_gray = cv2.cvtColor(diff, cv2.COLOR_RGB2GRAY)
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# 计算统计信息
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mean_diff = np.mean(diff)
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std_diff = np.std(diff)
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max_diff = np.max(diff)
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mean_diff_gray = np.mean(diff_gray)
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# 计算RGB各通道的平均色差
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mean_diff_r = np.mean(diff[:, :, 0])
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mean_diff_g = np.mean(diff[:, :, 1])
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mean_diff_b = np.mean(diff[:, :, 2])
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# 计算PSNR（峰值信噪比）
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mse = np.mean((frame1.astype(float) - frame2.astype(float)) ** 2)
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if mse == 0:
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psnr = float('inf')
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else:
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psnr = 20 * np.log10(255.0 / np.sqrt(mse))
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result = {
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'mean_diff': float(mean_diff),
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'std_diff': float(std_diff),
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'max_diff': int(max_diff),
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'mean_diff_gray': float(mean_diff_gray),
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'mean_diff_r': float(mean_diff_r),
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'mean_diff_g': float(mean_diff_g),
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'mean_diff_b': float(mean_diff_b),
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'psnr': float(psnr),
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'mse': float(mse),
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'diff_image': diff,
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'diff_gray': diff_gray
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}
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return result
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def test_color_stability(self, num_frames=10, interval=0.1):
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"""
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测试颜色稳定性（连续多帧的色差）
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:param num_frames: 测试帧数
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:param interval: 帧间隔（秒）
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:return: 稳定性统计信息
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"""
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frames = []
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logger.info(f"开始采集 {num_frames} 帧用于稳定性测试...")
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for i in range(num_frames):
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frame = self.get_frame()
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if frame is None:
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logger.warning(f"无法获取第 {i+1} 帧")
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continue
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frames.append(frame[0]) # 使用opencv格式
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if i < num_frames - 1:
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time.sleep(interval)
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if len(frames) < 2:
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logger.error("采集的帧数不足")
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return None
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||||
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||||
# 计算所有帧之间的平均色差
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all_diffs = []
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for i in range(len(frames) - 1):
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diff_result = self.test_color_difference(frames[i], frames[i+1])
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if diff_result:
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||||
all_diffs.append(diff_result['mean_diff'])
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||||
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||||
if not all_diffs:
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||||
return None
|
||||
|
||||
result = {
|
||||
'num_frames': len(frames),
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||||
'avg_mean_diff': float(np.mean(all_diffs)),
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'std_mean_diff': float(np.std(all_diffs)),
|
||||
'min_mean_diff': float(np.min(all_diffs)),
|
||||
'max_mean_diff': float(np.max(all_diffs)),
|
||||
'all_diffs': [float(d) for d in all_diffs]
|
||||
}
|
||||
|
||||
return result
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||||
|
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def print_resolution_test(self):
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"""打印分辨率测试结果"""
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||||
print("\n" + "="*60)
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||||
print("分辨率测试结果")
|
||||
print("="*60)
|
||||
result = self.test_resolution()
|
||||
if result is None:
|
||||
print("❌ 测试失败：采集卡未初始化")
|
||||
return
|
||||
|
||||
print(f"期望分辨率: {result['expected'][0]} x {result['expected'][1]}")
|
||||
if result['actual_cap']:
|
||||
print(f"实际分辨率(采集卡): {result['actual_cap'][0]} x {result['actual_cap'][1]}")
|
||||
match_str = "✅ 匹配" if result['match'] else "❌ 不匹配"
|
||||
print(f"分辨率匹配: {match_str}")
|
||||
|
||||
if result['actual_frame']:
|
||||
print(f"实际分辨率(原始帧): {result['actual_frame'][0]} x {result['actual_frame'][1]}")
|
||||
|
||||
if result['cropped_frame']:
|
||||
print(f"裁剪后分辨率: {result['cropped_frame'][0]} x {result['cropped_frame'][1]}")
|
||||
print("="*60 + "\n")
|
||||
|
||||
def print_color_test(self):
|
||||
"""打印色差测试结果"""
|
||||
print("\n" + "="*60)
|
||||
print("色差测试结果（两帧对比）")
|
||||
print("="*60)
|
||||
result = self.test_color_difference()
|
||||
if result is None:
|
||||
print("❌ 测试失败：无法获取帧")
|
||||
return
|
||||
|
||||
print(f"平均色差: {result['mean_diff']:.2f}")
|
||||
print(f"色差标准差: {result['std_diff']:.2f}")
|
||||
print(f"最大色差: {result['max_diff']}")
|
||||
print(f"灰度平均色差: {result['mean_diff_gray']:.2f}")
|
||||
print(f"\nRGB通道平均色差:")
|
||||
print(f" R通道: {result['mean_diff_r']:.2f}")
|
||||
print(f" G通道: {result['mean_diff_g']:.2f}")
|
||||
print(f" B通道: {result['mean_diff_b']:.2f}")
|
||||
print(f"\nPSNR (峰值信噪比): {result['psnr']:.2f} dB")
|
||||
print(f"MSE (均方误差): {result['mse']:.2f}")
|
||||
print("="*60 + "\n")
|
||||
|
||||
def print_stability_test(self, num_frames=10):
|
||||
"""打印稳定性测试结果"""
|
||||
print("\n" + "="*60)
|
||||
print(f"颜色稳定性测试结果（{num_frames}帧）")
|
||||
print("="*60)
|
||||
result = self.test_color_stability(num_frames)
|
||||
if result is None:
|
||||
print("❌ 测试失败：无法获取足够的帧")
|
||||
return
|
||||
|
||||
print(f"测试帧数: {result['num_frames']}")
|
||||
print(f"平均色差均值: {result['avg_mean_diff']:.2f}")
|
||||
print(f"色差标准差: {result['std_mean_diff']:.2f}")
|
||||
print(f"最小色差: {result['min_mean_diff']:.2f}")
|
||||
print(f"最大色差: {result['max_mean_diff']:.2f}")
|
||||
print(f"\n各帧间色差: {[f'{d:.2f}' for d in result['all_diffs']]}")
|
||||
print("="*60 + "\n")
|
||||
|
||||
def save_test_images(self, save_dir="test_output"):
|
||||
"""保存测试图像"""
|
||||
os.makedirs(save_dir, exist_ok=True)
|
||||
|
||||
# 保存原始帧
|
||||
raw_frame = self.get_raw_frame()
|
||||
if raw_frame is not None:
|
||||
cv2.imwrite(os.path.join(save_dir, "raw_frame.jpg"), raw_frame)
|
||||
logger.info(f"已保存原始帧: {save_dir}/raw_frame.jpg")
|
||||
|
||||
# 保存处理后的帧
|
||||
processed = self.get_frame()
|
||||
if processed is not None:
|
||||
cv2.imwrite(os.path.join(save_dir, "processed_frame.jpg"), cv2.cvtColor(processed[0], cv2.COLOR_RGB2BGR))
|
||||
logger.info(f"已保存处理后帧: {save_dir}/processed_frame.jpg")
|
||||
|
||||
# 保存色差图
|
||||
color_diff = self.test_color_difference()
|
||||
if color_diff is not None:
|
||||
cv2.imwrite(os.path.join(save_dir, "color_diff.jpg"), cv2.cvtColor(color_diff['diff_image'], cv2.COLOR_RGB2BGR))
|
||||
cv2.imwrite(os.path.join(save_dir, "color_diff_gray.jpg"), color_diff['diff_gray'])
|
||||
logger.info(f"已保存色差图: {save_dir}/color_diff.jpg")
|
||||
logger.info(f"已保存灰度色差图: {save_dir}/color_diff_gray.jpg")
|
||||
|
||||
def release(self):
|
||||
"""释放资源（与实际代码相同）"""
|
||||
self.running = False
|
||||
time.sleep(0.2)
|
||||
if self.cap is not None:
|
||||
self.cap.release()
|
||||
cv2.destroyAllWindows()
|
||||
logger.info("🔚 采集卡已释放")
|
||||
|
||||
def __del__(self):
|
||||
"""析构函数（与实际代码相同）"""
|
||||
if hasattr(self, "cap") and self.cap is not None:
|
||||
try:
|
||||
self.release()
|
||||
except:
|
||||
pass
|
||||
|
||||
|
||||
class MultiCaptureCardTester:
|
||||
"""
|
||||
多采集卡测试管理器
|
||||
支持同时测试多张采集卡
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
"""初始化多采集卡测试管理器"""
|
||||
self.testers = {} # {cam_index: CaptureCardTester}
|
||||
self.config = None
|
||||
|
||||
def load_from_config(self):
|
||||
"""从配置文件加载采集卡"""
|
||||
try:
|
||||
from config import config_manager
|
||||
config_manager.load_config()
|
||||
self.config = config_manager.config
|
||||
|
||||
groups = self.config.get('groups', [])
|
||||
if not groups:
|
||||
logger.warning("配置文件中没有找到配置组")
|
||||
return []
|
||||
|
||||
# 获取所有配置组中的采集卡
|
||||
camera_configs = []
|
||||
for group in groups:
|
||||
cam_idx = group.get('camera_index')
|
||||
cam_width = group.get('camera_width', 1920)
|
||||
cam_height = group.get('camera_height', 1080)
|
||||
name = group.get('name', f"配置组{groups.index(group)}")
|
||||
|
||||
# 检查是否已存在相同索引的采集卡
|
||||
if cam_idx not in [c['index'] for c in camera_configs]:
|
||||
camera_configs.append({
|
||||
'index': cam_idx,
|
||||
'width': cam_width,
|
||||
'height': cam_height,
|
||||
'name': name,
|
||||
'group': group
|
||||
})
|
||||
|
||||
return camera_configs
|
||||
except Exception as e:
|
||||
logger.error(f"从配置加载失败: {e}")
|
||||
return []
|
||||
|
||||
def add_camera(self, cam_index, width=1920, height=1080, name=None):
|
||||
"""
|
||||
添加一张采集卡到测试列表
|
||||
:param cam_index: 采集卡索引
|
||||
:param width: 宽度
|
||||
:param height: 高度
|
||||
:param name: 采集卡名称（可选）
|
||||
"""
|
||||
if name is None:
|
||||
name = f"采集卡{cam_index}"
|
||||
|
||||
if cam_index in self.testers:
|
||||
logger.warning(f"采集卡 {cam_index} 已存在，将重新初始化")
|
||||
self.testers[cam_index].release()
|
||||
|
||||
tester = CaptureCardTester(cam_index=cam_index, width=width, height=height)
|
||||
if tester.cap is not None:
|
||||
tester.name = name
|
||||
self.testers[cam_index] = tester
|
||||
return True
|
||||
else:
|
||||
logger.error(f"无法初始化采集卡 {cam_index}")
|
||||
return False
|
||||
|
||||
def initialize_from_config(self, use_all_groups=True):
|
||||
"""
|
||||
从配置初始化所有采集卡
|
||||
:param use_all_groups: 是否使用所有配置组，False则只使用活动配置组
|
||||
"""
|
||||
camera_configs = self.load_from_config()
|
||||
|
||||
if not camera_configs:
|
||||
logger.warning("没有找到可用的采集卡配置")
|
||||
return False
|
||||
|
||||
# 筛选配置组
|
||||
if not use_all_groups:
|
||||
camera_configs = [c for c in camera_configs if c.get('group', {}).get('active', False)]
|
||||
if not camera_configs:
|
||||
logger.warning("没有活动的配置组")
|
||||
return False
|
||||
|
||||
logger.info(f"📷 找到 {len(camera_configs)} 张采集卡配置")
|
||||
|
||||
success_count = 0
|
||||
for config in camera_configs:
|
||||
if self.add_camera(
|
||||
cam_index=config['index'],
|
||||
width=config['width'],
|
||||
height=config['height'],
|
||||
name=config['name']
|
||||
):
|
||||
success_count += 1
|
||||
|
||||
logger.info(f"✅ 成功初始化 {success_count}/{len(camera_configs)} 张采集卡")
|
||||
return success_count > 0
|
||||
|
||||
def test_all_resolution(self):
|
||||
"""测试所有采集卡的分辨率"""
|
||||
print("\n" + "="*60)
|
||||
print("所有采集卡分辨率测试")
|
||||
print("="*60)
|
||||
|
||||
results = {}
|
||||
for cam_index, tester in self.testers.items():
|
||||
name = getattr(tester, 'name', f"采集卡{cam_index}")
|
||||
print(f"\n【{name} (索引: {cam_index})】")
|
||||
result = tester.test_resolution()
|
||||
results[cam_index] = result
|
||||
|
||||
# 汇总结果
|
||||
print("\n" + "-"*60)
|
||||
print("分辨率测试汇总")
|
||||
print("-"*60)
|
||||
for cam_index, result in results.items():
|
||||
if result is None:
|
||||
continue
|
||||
name = getattr(self.testers[cam_index], 'name', f"采集卡{cam_index}")
|
||||
match_str = "✅" if result.get('match', False) else "❌"
|
||||
print(f"{match_str} {name}: 期望{result['expected']} -> 实际{result.get('actual_cap', 'N/A')}")
|
||||
|
||||
return results
|
||||
|
||||
def test_all_color(self):
|
||||
"""测试所有采集卡的色差"""
|
||||
print("\n" + "="*60)
|
||||
print("所有采集卡色差测试")
|
||||
print("="*60)
|
||||
|
||||
results = {}
|
||||
for cam_index, tester in self.testers.items():
|
||||
name = getattr(tester, 'name', f"采集卡{cam_index}")
|
||||
print(f"\n【{name} (索引: {cam_index})】")
|
||||
result = tester.test_color_difference()
|
||||
results[cam_index] = result
|
||||
|
||||
# 汇总结果
|
||||
print("\n" + "-"*60)
|
||||
print("色差测试汇总")
|
||||
print("-"*60)
|
||||
for cam_index, result in results.items():
|
||||
if result is None:
|
||||
continue
|
||||
name = getattr(self.testers[cam_index], 'name', f"采集卡{cam_index}")
|
||||
print(f"{name}: 平均色差={result['mean_diff']:.2f}, PSNR={result['psnr']:.2f}dB")
|
||||
|
||||
return results
|
||||
|
||||
def test_all_stability(self, num_frames=10):
|
||||
"""测试所有采集卡的稳定性"""
|
||||
print("\n" + "="*60)
|
||||
print("所有采集卡稳定性测试")
|
||||
print("="*60)
|
||||
|
||||
results = {}
|
||||
for cam_index, tester in self.testers.items():
|
||||
name = getattr(tester, 'name', f"采集卡{cam_index}")
|
||||
print(f"\n【{name} (索引: {cam_index})】")
|
||||
result = tester.test_color_stability(num_frames=num_frames)
|
||||
results[cam_index] = result
|
||||
|
||||
# 汇总结果
|
||||
print("\n" + "-"*60)
|
||||
print("稳定性测试汇总")
|
||||
print("-"*60)
|
||||
for cam_index, result in results.items():
|
||||
if result is None:
|
||||
continue
|
||||
name = getattr(self.testers[cam_index], 'name', f"采集卡{cam_index}")
|
||||
print(f"{name}: 平均色差={result['avg_mean_diff']:.2f}±{result['std_mean_diff']:.2f}")
|
||||
|
||||
return results
|
||||
|
||||
def save_all_test_images(self, base_dir="test_output"):
|
||||
"""保存所有采集卡的测试图像"""
|
||||
for cam_index, tester in self.testers.items():
|
||||
name = getattr(tester, 'name', f"采集卡{cam_index}")
|
||||
# 清理名称中的特殊字符，用于目录名
|
||||
safe_name = "".join(c for c in name if c.isalnum() or c in (' ', '-', '_')).rstrip()
|
||||
save_dir = os.path.join(base_dir, safe_name)
|
||||
tester.save_test_images(save_dir=save_dir)
|
||||
|
||||
def release_all(self):
|
||||
"""释放所有采集卡"""
|
||||
for tester in self.testers.values():
|
||||
try:
|
||||
tester.release()
|
||||
except:
|
||||
pass
|
||||
self.testers.clear()
|
||||
|
||||
def __del__(self):
|
||||
"""析构函数"""
|
||||
self.release_all()
|
||||
|
||||
|
||||
def scan_cameras(max_index=10):
|
||||
"""
|
||||
扫描可用的采集卡
|
||||
:param max_index: 最大扫描索引
|
||||
:return: 可用采集卡索引列表
|
||||
"""
|
||||
print("🔍 正在扫描采集卡...")
|
||||
available = []
|
||||
|
||||
old_stderr = sys.stderr
|
||||
suppressed_output = io.StringIO()
|
||||
|
||||
try:
|
||||
sys.stderr = suppressed_output
|
||||
|
||||
for i in range(max_index):
|
||||
cap = None
|
||||
try:
|
||||
with warnings.catch_warnings():
|
||||
warnings.filterwarnings('ignore')
|
||||
cap = cv2.VideoCapture(i, cv2.CAP_DSHOW)
|
||||
if cap.isOpened():
|
||||
ret, frame = cap.read()
|
||||
if ret and frame is not None:
|
||||
available.append(i)
|
||||
print(f" ✅ 找到采集卡: 索引 {i}")
|
||||
if cap:
|
||||
cap.release()
|
||||
except:
|
||||
if cap:
|
||||
try:
|
||||
cap.release()
|
||||
except:
|
||||
pass
|
||||
finally:
|
||||
sys.stderr = old_stderr
|
||||
|
||||
if not available:
|
||||
print(" ❌ 未找到可用的采集卡")
|
||||
else:
|
||||
print(f"✅ 共找到 {len(available)} 张采集卡")
|
||||
|
||||
return available
|
||||
|
||||
|
||||
def main():
|
||||
"""主测试函数"""
|
||||
print("="*60)
|
||||
print("采集卡截图测试工具（支持多采集卡）")
|
||||
print("="*60)
|
||||
|
||||
multi_tester = MultiCaptureCardTester()
|
||||
|
||||
# 选择测试模式
|
||||
print("\n选择测试模式:")
|
||||
print(" 1. 从配置文件加载（所有配置组）")
|
||||
print(" 2. 从配置文件加载（仅活动配置组）")
|
||||
print(" 3. 手动指定采集卡索引")
|
||||
print(" 4. 扫描采集卡")
|
||||
print(" 0. 退出")
|
||||
|
||||
choice = input("\n请选择 (0-4): ").strip()
|
||||
|
||||
if choice == "0":
|
||||
print("👋 退出")
|
||||
return
|
||||
elif choice == "1":
|
||||
# 从配置加载所有配置组
|
||||
if not multi_tester.initialize_from_config(use_all_groups=True):
|
||||
print("❌ 无法从配置初始化采集卡")
|
||||
return
|
||||
elif choice == "2":
|
||||
# 从配置加载活动配置组
|
||||
if not multi_tester.initialize_from_config(use_all_groups=False):
|
||||
print("❌ 无法从配置初始化采集卡")
|
||||
return
|
||||
elif choice == "3":
|
||||
# 手动指定
|
||||
indices_input = input("请输入采集卡索引(用逗号分隔,如: 0,1,2): ").strip()
|
||||
try:
|
||||
indices = [int(x.strip()) for x in indices_input.split(',')]
|
||||
width_input = input("请输入宽度 (默认1920): ").strip()
|
||||
height_input = input("请输入高度 (默认1080): ").strip()
|
||||
width = int(width_input) if width_input else 1920
|
||||
height = int(height_input) if height_input else 1080
|
||||
|
||||
success_count = 0
|
||||
for idx in indices:
|
||||
if multi_tester.add_camera(idx, width=width, height=height):
|
||||
success_count += 1
|
||||
|
||||
if success_count == 0:
|
||||
print("❌ 无法初始化任何采集卡")
|
||||
return
|
||||
except ValueError:
|
||||
print("❌ 输入格式错误")
|
||||
return
|
||||
elif choice == "4":
|
||||
# 扫描采集卡
|
||||
available = scan_cameras()
|
||||
if not available:
|
||||
return
|
||||
|
||||
indices_input = input(f"请输入要测试的采集卡索引(用逗号分隔,可用: {available}): ").strip()
|
||||
try:
|
||||
indices = [int(x.strip()) for x in indices_input.split(',')]
|
||||
# 验证索引有效性
|
||||
indices = [i for i in indices if i in available]
|
||||
if not indices:
|
||||
print("❌ 没有有效的采集卡索引")
|
||||
return
|
||||
|
||||
width_input = input("请输入宽度 (默认1920): ").strip()
|
||||
height_input = input("请输入高度 (默认1080): ").strip()
|
||||
width = int(width_input) if width_input else 1920
|
||||
height = int(height_input) if height_input else 1080
|
||||
|
||||
success_count = 0
|
||||
for idx in indices:
|
||||
if multi_tester.add_camera(idx, width=width, height=height):
|
||||
success_count += 1
|
||||
|
||||
if success_count == 0:
|
||||
print("❌ 无法初始化任何采集卡")
|
||||
return
|
||||
except ValueError:
|
||||
print("❌ 输入格式错误")
|
||||
return
|
||||
else:
|
||||
print("❌ 无效选择")
|
||||
return
|
||||
|
||||
if not multi_tester.testers:
|
||||
print("❌ 没有可用的采集卡")
|
||||
return
|
||||
|
||||
try:
|
||||
# 等待采集卡稳定
|
||||
print("\n等待采集卡稳定...")
|
||||
time.sleep(1.0)
|
||||
|
||||
# 测试分辨率
|
||||
multi_tester.test_all_resolution()
|
||||
|
||||
# 等待一下确保采集卡稳定
|
||||
time.sleep(0.5)
|
||||
|
||||
# 测试色差
|
||||
multi_tester.test_all_color()
|
||||
|
||||
# 测试稳定性
|
||||
multi_tester.test_all_stability(num_frames=10)
|
||||
|
||||
# 保存测试图像
|
||||
multi_tester.save_all_test_images()
|
||||
|
||||
print("\n✅ 所有测试完成！")
|
||||
print("按 Enter 键退出...")
|
||||
input()
|
||||
|
||||
except KeyboardInterrupt:
|
||||
print("\n\n用户中断测试")
|
||||
except Exception as e:
|
||||
logger.error(f"测试过程中发生错误: {e}")
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
finally:
|
||||
multi_tester.release_all()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
||||
356
yolo_test.py
356
yolo_test.py
@@ -1,26 +1,195 @@
|
||||
import cv2
|
||||
from utils.get_image import get_image
|
||||
from utils.get_image import GetImage
|
||||
from ultralytics import YOLO
|
||||
from config import config_manager
|
||||
from utils.logger import logger
|
||||
import os
|
||||
import numpy as np
|
||||
|
||||
model = YOLO(r"best0.pt").to('cuda')
|
||||
# 检查模型文件是否存在
|
||||
model_path = r"best0.pt"
|
||||
if not os.path.exists(model_path):
|
||||
print(f"❌ 模型文件不存在: {model_path}")
|
||||
exit(1)
|
||||
|
||||
def yolo_shibie(im_PIL, detections):
|
||||
# 加载YOLO模型
|
||||
try:
|
||||
model = YOLO(model_path).to('cuda')
|
||||
print(f"✅ 模型加载成功: {model_path}")
|
||||
except Exception as e:
|
||||
print(f"❌ 模型加载失败: {e}")
|
||||
exit(1)
|
||||
|
||||
def enhance_sharpness(image, strength=1.5):
|
||||
"""
|
||||
增强图像锐度
|
||||
:param image: 输入图像（BGR格式）
|
||||
:param strength: 锐化强度（1.0-3.0，默认1.5）
|
||||
:return: 锐化后的图像
|
||||
"""
|
||||
# 创建锐化核
|
||||
kernel = np.array([[-1, -1, -1],
|
||||
[-1, 9*strength, -1],
|
||||
[-1, -1, -1]]) / (9*strength - 8)
|
||||
sharpened = cv2.filter2D(image, -1, kernel)
|
||||
return sharpened
|
||||
|
||||
|
||||
def enhance_contrast(image, alpha=1.2, beta=10):
|
||||
"""
|
||||
增强对比度和亮度
|
||||
:param image: 输入图像
|
||||
:param alpha: 对比度控制（1.0-3.0，默认1.2）
|
||||
:param beta: 亮度控制（-100到100，默认10）
|
||||
:return: 增强后的图像
|
||||
"""
|
||||
return cv2.convertScaleAbs(image, alpha=alpha, beta=beta)
|
||||
|
||||
|
||||
def denoise_image(image, method='bilateral'):
|
||||
"""
|
||||
去噪处理
|
||||
:param image: 输入图像
|
||||
:param method: 去噪方法 ('bilateral', 'gaussian', 'fastNlMeans')
|
||||
:return: 去噪后的图像
|
||||
"""
|
||||
if method == 'bilateral':
|
||||
# 双边滤波，保留边缘的同时去噪
|
||||
return cv2.bilateralFilter(image, 9, 75, 75)
|
||||
elif method == 'gaussian':
|
||||
# 高斯模糊去噪
|
||||
return cv2.GaussianBlur(image, (5, 5), 0)
|
||||
elif method == 'fastNlMeans':
|
||||
# 非局部均值去噪（效果最好但较慢）
|
||||
return cv2.fastNlMeansDenoisingColored(image, None, 10, 10, 7, 21)
|
||||
return image
|
||||
|
||||
|
||||
def apply_enhancements(image, sharpness=True, contrast=True, denoise=True,
|
||||
sharp_strength=1.5, contrast_alpha=1.2, contrast_beta=10,
|
||||
denoise_method='bilateral'):
|
||||
"""
|
||||
应用所有图像增强
|
||||
:param image: 输入图像（BGR格式）
|
||||
:param sharpness: 是否锐化
|
||||
:param contrast: 是否增强对比度
|
||||
:param denoise: 是否去噪
|
||||
:param sharp_strength: 锐化强度
|
||||
:param contrast_alpha: 对比度系数
|
||||
:param contrast_beta: 亮度调整
|
||||
:param denoise_method: 去噪方法
|
||||
:return: 增强后的图像
|
||||
"""
|
||||
enhanced = image.copy()
|
||||
|
||||
if denoise:
|
||||
enhanced = denoise_image(enhanced, denoise_method)
|
||||
|
||||
if contrast:
|
||||
enhanced = enhance_contrast(enhanced, contrast_alpha, contrast_beta)
|
||||
|
||||
if sharpness:
|
||||
enhanced = enhance_sharpness(enhanced, sharp_strength)
|
||||
|
||||
return enhanced
|
||||
|
||||
|
||||
def set_camera_properties(cap, brightness=None, contrast=None, saturation=None,
|
||||
sharpness=None, gain=None, exposure=None):
|
||||
"""
|
||||
设置采集卡硬件参数
|
||||
:param cap: VideoCapture对象
|
||||
:param brightness: 亮度 (0-100)
|
||||
:param contrast: 对比度 (0-100)
|
||||
:param saturation: 饱和度 (0-100)
|
||||
:param sharpness: 锐度 (0-100)
|
||||
:param gain: 增益 (0-100)
|
||||
:param exposure: 曝光 (通常为负值，如-6)
|
||||
"""
|
||||
props = {
|
||||
cv2.CAP_PROP_BRIGHTNESS: brightness,
|
||||
cv2.CAP_PROP_CONTRAST: contrast,
|
||||
cv2.CAP_PROP_SATURATION: saturation,
|
||||
cv2.CAP_PROP_SHARPNESS: sharpness,
|
||||
cv2.CAP_PROP_GAIN: gain,
|
||||
cv2.CAP_PROP_EXPOSURE: exposure,
|
||||
}
|
||||
|
||||
for prop, value in props.items():
|
||||
if value is not None:
|
||||
try:
|
||||
cap.set(prop, value)
|
||||
actual = cap.get(prop)
|
||||
logger.info(f" 设置 {prop.name if hasattr(prop, 'name') else prop}: {value} -> 实际: {actual:.2f}")
|
||||
except Exception as e:
|
||||
logger.warning(f" ⚠️ 设置参数 {prop} 失败: {e}")
|
||||
|
||||
|
||||
def yolo_shibie(im_PIL, im_opencv_rgb, raw_frame_bgr, detections, model, show_original=True,
|
||||
enhance_enabled=False, enhance_params=None):
|
||||
"""
|
||||
YOLO识别函数
|
||||
:param im_PIL: PIL图像对象
|
||||
:param im_opencv_rgb: RGB格式的OpenCV图像（裁剪后）
|
||||
:param raw_frame_bgr: 原始BGR格式的OpenCV图像（未裁剪，与raw_frame.jpg一致）
|
||||
:param detections: 检测结果字典
|
||||
:param model: YOLO模型
|
||||
:param show_original: 是否同时显示原始帧
|
||||
:return: 更新后的detections字典，如果用户退出则返回None
|
||||
"""
|
||||
if im_PIL is None:
|
||||
return detections
|
||||
|
||||
try:
|
||||
results = model(im_PIL)
|
||||
result = results[0]
|
||||
|
||||
# ✅ 获取绘制好框的图像
|
||||
frame_with_boxes = result.plot()
|
||||
# ✅ 获取绘制好框的图像（RGB格式）
|
||||
frame_with_boxes_rgb = result.plot()
|
||||
|
||||
# ✅ 用 OpenCV 动态显示
|
||||
cv2.imshow("YOLO实时检测", frame_with_boxes)
|
||||
# ✅ 转换为BGR格式用于OpenCV显示
|
||||
frame_with_boxes_bgr = cv2.cvtColor(frame_with_boxes_rgb, cv2.COLOR_RGB2BGR)
|
||||
|
||||
# ESC 或 Q 键退出
|
||||
if cv2.waitKey(1) & 0xFF in [27, ord('q')]:
|
||||
return None
|
||||
# 应用图像增强（如果启用）
|
||||
display_frame = frame_with_boxes_bgr.copy()
|
||||
if enhance_enabled and enhance_params:
|
||||
try:
|
||||
display_frame = apply_enhancements(display_frame, **enhance_params)
|
||||
except Exception as e:
|
||||
print(f"⚠️ 图像增强失败: {e}")
|
||||
|
||||
# 显示画面
|
||||
if show_original and raw_frame_bgr is not None:
|
||||
# 同时显示原始帧和检测结果（并排显示）
|
||||
# 调整原始帧大小以匹配裁剪后的检测结果
|
||||
h, w = display_frame.shape[:2]
|
||||
# 裁剪原始帧（与get_frame的处理一致：30:30+720, 0:1280）
|
||||
raw_height, raw_width = raw_frame_bgr.shape[:2]
|
||||
crop_top = 30
|
||||
crop_bottom = min(crop_top + h, raw_height)
|
||||
crop_right = min(w, raw_width)
|
||||
raw_cropped = raw_frame_bgr[crop_top:crop_bottom, 0:crop_right]
|
||||
|
||||
# 如果尺寸不匹配，调整原始帧大小
|
||||
if raw_cropped.shape[:2] != (h, w):
|
||||
raw_cropped = cv2.resize(raw_cropped, (w, h))
|
||||
|
||||
# 并排显示：原始帧(左) | 检测结果(右)
|
||||
# 原始帧已经是BGR格式，检测结果也是BGR格式，可以直接拼接
|
||||
combined = cv2.hconcat([raw_cropped, display_frame])
|
||||
cv2.imshow("Original BGR (Left) | YOLO Detection (Right)", combined)
|
||||
else:
|
||||
# 只显示检测结果
|
||||
cv2.imshow("YOLO Real-time Detection", display_frame)
|
||||
|
||||
# ✅ 提取检测信息
|
||||
if result.boxes is not None and len(result.boxes.xyxy) > 0:
|
||||
for i in range(len(result.boxes.xyxy)):
|
||||
left, top, right, bottom = result.boxes.xyxy[i]
|
||||
try:
|
||||
left = float(result.boxes.xyxy[i][0])
|
||||
top = float(result.boxes.xyxy[i][1])
|
||||
right = float(result.boxes.xyxy[i][2])
|
||||
bottom = float(result.boxes.xyxy[i][3])
|
||||
cls_id = int(result.boxes.cls[i])
|
||||
label = result.names[cls_id]
|
||||
|
||||
@@ -31,12 +200,121 @@ def yolo_shibie(im_PIL, detections):
|
||||
elif label in ['daojv', 'gw']:
|
||||
player_x = int(left + (right - left) / 2) + 3
|
||||
player_y = int(top + (bottom - top) / 2) + 40
|
||||
# 确保列表存在
|
||||
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
|
||||
|
||||
except Exception as e:
|
||||
print(f"⚠️ YOLO检测出错: {e}")
|
||||
|
||||
return detections
|
||||
|
||||
|
||||
while True:
|
||||
def main():
|
||||
"""主函数"""
|
||||
print("="*60)
|
||||
print("YOLO实时检测测试")
|
||||
print("="*60)
|
||||
|
||||
# 从配置加载采集卡设置
|
||||
active_group = config_manager.get_active_group()
|
||||
|
||||
if active_group is None:
|
||||
print("⚠️ 没有活动的配置组，使用默认设置")
|
||||
print("提示: 可以运行 python gui_config.py 设置配置")
|
||||
cam_index = 0
|
||||
width = 1920
|
||||
height = 1080
|
||||
else:
|
||||
print(f"📋 使用配置组: {active_group['name']}")
|
||||
cam_index = active_group['camera_index']
|
||||
width = active_group['camera_width']
|
||||
height = active_group['camera_height']
|
||||
|
||||
print(f" 采集卡索引: {cam_index}")
|
||||
print(f" 分辨率: {width}x{height}")
|
||||
print()
|
||||
|
||||
# 初始化采集卡
|
||||
print("🔧 正在初始化采集卡...")
|
||||
get_image = GetImage(
|
||||
cam_index=cam_index,
|
||||
width=width,
|
||||
height=height
|
||||
)
|
||||
|
||||
if get_image.cap is None:
|
||||
print("❌ 采集卡初始化失败")
|
||||
print("请检查：")
|
||||
print("1. 采集卡是否正确连接")
|
||||
print("2. 采集卡索引是否正确")
|
||||
print("3. 采集卡驱动是否安装")
|
||||
return
|
||||
|
||||
# 设置采集卡硬件参数以提高清晰度（可选）
|
||||
print("\n🔧 设置采集卡参数以提高清晰度...")
|
||||
print("提示: 可以根据实际情况调整这些参数")
|
||||
set_camera_properties(
|
||||
get_image.cap,
|
||||
brightness=50, # 亮度 (0-100)
|
||||
contrast=50, # 对比度 (0-100)
|
||||
saturation=55, # 饱和度 (0-100)
|
||||
sharpness=60, # 锐度 (0-100，提高清晰度)
|
||||
gain=None, # 增益 (根据实际情况调整)
|
||||
exposure=None # 曝光 (根据实际情况调整，通常为负值)
|
||||
)
|
||||
|
||||
print("✅ 采集卡初始化成功")
|
||||
print("\n快捷键:")
|
||||
print(" 'q' 或 ESC - 退出")
|
||||
print(" 'o' - 切换原始帧对比模式")
|
||||
print(" 'e' - 切换图像增强")
|
||||
print(" '1'/'2' - 调整锐化强度 (+/-0.1)")
|
||||
print(" '3'/'4' - 调整对比度 (+/-0.1)")
|
||||
print()
|
||||
|
||||
try:
|
||||
frame_count = 0
|
||||
show_original = True # 默认同时显示原始帧和检测结果
|
||||
enhance_enabled = False # 默认关闭图像增强
|
||||
|
||||
# 图像增强参数
|
||||
enhance_params = {
|
||||
'sharpness': True,
|
||||
'contrast': True,
|
||||
'denoise': True,
|
||||
'sharp_strength': 1.5,
|
||||
'contrast_alpha': 1.2,
|
||||
'contrast_beta': 10,
|
||||
'denoise_method': 'bilateral'
|
||||
}
|
||||
|
||||
while True:
|
||||
# 获取帧
|
||||
frame_data = get_image.get_frame()
|
||||
|
||||
if frame_data is None:
|
||||
print("⚠️ 无法获取帧，跳过...")
|
||||
continue
|
||||
|
||||
# frame_data 是 [im_opencv_rgb, im_PIL] 格式
|
||||
# im_opencv_rgb 已经是RGB格式（经过BGR2RGB转换）
|
||||
im_opencv_rgb, im_PIL = frame_data
|
||||
|
||||
if im_PIL is None:
|
||||
print("⚠️ PIL图像为空，跳过...")
|
||||
continue
|
||||
|
||||
# 获取原始BGR帧（与test_capture_card.py保存的raw_frame.jpg一致）
|
||||
raw_frame_bgr = None
|
||||
if get_image.cap is not None and get_image.frame is not None:
|
||||
raw_frame_bgr = get_image.frame.copy() # 原始BGR格式，未裁剪
|
||||
|
||||
# 初始化检测结果字典
|
||||
detections = {
|
||||
'center': None, 'next': None,
|
||||
'npc1': None, 'npc2': None, 'npc3': None, 'npc4': None,
|
||||
@@ -44,12 +322,56 @@ while True:
|
||||
'daojv': [], 'gw': []
|
||||
}
|
||||
|
||||
im_opencv = get_image.get_frame() # [RGB, PIL]
|
||||
detections = yolo_shibie(im_opencv[1], detections)
|
||||
# 执行YOLO检测
|
||||
detections = yolo_shibie(im_PIL, im_opencv_rgb, raw_frame_bgr, detections, model,
|
||||
show_original, enhance_enabled, enhance_params)
|
||||
|
||||
if detections is None: # 用户退出
|
||||
# 检查按键
|
||||
key = cv2.waitKey(1) & 0xFF
|
||||
if key in [27, ord('q'), ord('Q')]:
|
||||
print("\n用户退出")
|
||||
break
|
||||
elif key == ord('o') or key == ord('O'):
|
||||
show_original = not show_original
|
||||
print(f"切换显示模式: {'原始帧对比' if show_original else '仅检测结果'}")
|
||||
elif key == ord('e') or key == ord('E'):
|
||||
enhance_enabled = not enhance_enabled
|
||||
status = "开启" if enhance_enabled else "关闭"
|
||||
print(f"图像增强: {status} (锐化={enhance_params['sharp_strength']:.1f}, "
|
||||
f"对比度={enhance_params['contrast_alpha']:.1f})")
|
||||
elif key == ord('1'):
|
||||
enhance_params['sharp_strength'] = min(3.0, enhance_params['sharp_strength'] + 0.1)
|
||||
print(f"锐化强度: {enhance_params['sharp_strength']:.1f}")
|
||||
elif key == ord('2'):
|
||||
enhance_params['sharp_strength'] = max(0.5, enhance_params['sharp_strength'] - 0.1)
|
||||
print(f"锐化强度: {enhance_params['sharp_strength']:.1f}")
|
||||
elif key == ord('3'):
|
||||
enhance_params['contrast_alpha'] = min(3.0, enhance_params['contrast_alpha'] + 0.1)
|
||||
print(f"对比度: {enhance_params['contrast_alpha']:.1f}")
|
||||
elif key == ord('4'):
|
||||
enhance_params['contrast_alpha'] = max(0.5, enhance_params['contrast_alpha'] - 0.1)
|
||||
print(f"对比度: {enhance_params['contrast_alpha']:.1f}")
|
||||
|
||||
print(detections)
|
||||
frame_count += 1
|
||||
if frame_count % 30 == 0: # 每30帧打印一次
|
||||
print(f"📊 已处理 {frame_count} 帧")
|
||||
# 打印有检测到的目标
|
||||
detected_items = {k: v for k, v in detections.items() if v is not None and v != []}
|
||||
if detected_items:
|
||||
print(f" 检测到: {detected_items}")
|
||||
|
||||
cv2.destroyAllWindows()
|
||||
except KeyboardInterrupt:
|
||||
print("\n\n用户中断测试")
|
||||
except Exception as e:
|
||||
print(f"\n❌ 测试过程中发生错误: {e}")
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
finally:
|
||||
# 清理资源
|
||||
get_image.release()
|
||||
cv2.destroyAllWindows()
|
||||
print("🔚 测试结束")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
||||
Reference in New Issue
Block a user