# -- coding: utf-8 -- import sys import platform import copy import os from ctypes import * import numpy import cv2 # 配置项 image_area = 1080 * 1440 / 4 threshold_area = image_area*0.01 currentsystem = platform.system() print(f"current system: {currentsystem}") if currentsystem == 'Windows': sys.path.append(os.getenv('MVCAM_COMMON_RUNENV') + "/Samples/Python/MvImport") else: # Demo 目录: "/opt/xxx/Samples/平台/OpenCV/ZZ/ ") python接口目录： "/opt/xxx/Samples/平台/Python/MvImport" sys.path.append("/opt/MVS/Samples/aarch64/Python/MvImport") print(f"sys.path: {sys.path}") from MvCameraControl_class import * # 兼容Python 2.x和3.x的输入处理 if sys.version_info[0] < 3: # Python 2.x input_func = raw_input else: # Python 3.x input_func = input stFrame = POINTER(MV_FRAME_OUT) fun_ctype = get_platform_functype() FrameInfoCallBack2 = fun_ctype(None, stFrame, c_void_p, c_bool) def IsHBPixelFormat(enPixelType = 0): if enPixelType in (PixelType_Gvsp_HB_Mono8, \ PixelType_Gvsp_HB_Mono10,\ PixelType_Gvsp_HB_Mono10_Packed,\ PixelType_Gvsp_HB_Mono12,\ PixelType_Gvsp_HB_Mono12_Packed,\ PixelType_Gvsp_HB_Mono16,\ PixelType_Gvsp_HB_RGB8_Packed,\ PixelType_Gvsp_HB_BGR8_Packed,\ PixelType_Gvsp_HB_RGBA8_Packed,\ PixelType_Gvsp_HB_BGRA8_Packed,\ PixelType_Gvsp_HB_RGB16_Packed,\ PixelType_Gvsp_HB_BGR16_Packed,\ PixelType_Gvsp_HB_RGBA16_Packed,\ PixelType_Gvsp_HB_BGRA16_Packed,\ PixelType_Gvsp_HB_YUV422_Packed,\ PixelType_Gvsp_HB_YUV422_YUYV_Packed,\ PixelType_Gvsp_HB_BayerGR8,\ PixelType_Gvsp_HB_BayerRG8,\ PixelType_Gvsp_HB_BayerGB8,\ PixelType_Gvsp_HB_BayerBG8,\ PixelType_Gvsp_HB_BayerRBGG8,\ PixelType_Gvsp_HB_BayerGB10,\ PixelType_Gvsp_HB_BayerGB10_Packed,\ PixelType_Gvsp_HB_BayerBG10,\ PixelType_Gvsp_HB_BayerBG10_Packed,\ PixelType_Gvsp_HB_BayerRG10,\ PixelType_Gvsp_HB_BayerRG10_Packed,\ PixelType_Gvsp_HB_BayerGR10,\ PixelType_Gvsp_HB_BayerGR10_Packed,\ PixelType_Gvsp_HB_BayerGB12,\ PixelType_Gvsp_HB_BayerGB12_Packed,\ PixelType_Gvsp_HB_BayerBG12,\ PixelType_Gvsp_HB_BayerBG12_Packed,\ PixelType_Gvsp_HB_BayerRG12,\ PixelType_Gvsp_HB_BayerRG12_Packed,\ PixelType_Gvsp_HB_BayerGR12,\ PixelType_Gvsp_HB_BayerGR12_Packed): return True else: return False def IsMonoPixelFormat(enPixelType = 0): if enPixelType in (PixelType_Gvsp_Mono8, \ PixelType_Gvsp_Mono10, \ PixelType_Gvsp_Mono10_Packed, \ PixelType_Gvsp_Mono12, \ PixelType_Gvsp_Mono12_Packed, \ PixelType_Gvsp_Mono14, \ PixelType_Gvsp_Mono16): return True else: return False #执行1次 g_SaveImageOnce = False def image_callback2(pstFrame, pUser, bAutoFree): start_time = cv2.getTickCount() stFrame = cast(pstFrame, POINTER(MV_FRAME_OUT)).contents User = ctypes.cast(pUser, ctypes.py_object).value if stFrame: # print ("get one frame: Width[%d], Height[%d], nFrameNum[%d] len[%d] nLostPacket[%d]" % (stFrame.stFrameInfo.nWidth, stFrame.stFrameInfo.nHeight, stFrame.stFrameInfo.nFrameNum ,stFrame.stFrameInfo.nFrameLen, stFrame.stFrameInfo.nLostPacket)) global g_SaveImageOnce while True: stDecodeParam = MV_CC_HB_DECODE_PARAM() stConvertParam = MV_CC_PIXEL_CONVERT_PARAM_EX() memset(byref(stConvertParam), 0, sizeof(stConvertParam)) # 如果是HB图像，需要进行HB解码 result = IsHBPixelFormat(stFrame.stFrameInfo.enPixelType) if True == result : DecodeBufferlen = stFrame.stFrameInfo.nWidth * stFrame.stFrameInfo.nHeight * 3 DecodeBuffer = (c_ubyte * DecodeBufferlen)() stDecodeParam.pSrcBuf = stFrame.pBufAddr stDecodeParam.nSrcLen = stFrame.stFrameInfo.nFrameLen stDecodeParam.pDstBuf = DecodeBuffer stDecodeParam.nDstBufSize = DecodeBufferlen ret = User.MV_CC_HBDecode(stDecodeParam) if ret != 0: print("HB Decode fail! ret[0x%x]" % ret) break stConvertParam.pSrcData = stDecodeParam.pDstBuf stConvertParam.nSrcDataLen = stDecodeParam.nDstBufLen stConvertParam.enSrcPixelType = stDecodeParam.enDstPixelType else: stConvertParam.pSrcData = stFrame.pBufAddr stConvertParam.nSrcDataLen = stFrame.stFrameInfo.nFrameLen stConvertParam.enSrcPixelType = stFrame.stFrameInfo.enPixelType # 图像进行格式转换 enDstPixelType = PixelType_Gvsp_Undefined nChannelNum = 1 bMono = IsMonoPixelFormat(stConvertParam.enSrcPixelType) if True == bMono : enDstPixelType = PixelType_Gvsp_Mono8 nChannelNum = 1 else: enDstPixelType = PixelType_Gvsp_BGR8_Packed nChannelNum = 3 convertdestBufflen = nChannelNum *stFrame.stFrameInfo.nWidth * stFrame.stFrameInfo.nHeight DstBuffer = (c_ubyte * convertdestBufflen)() DstBufferlen = convertdestBufflen stConvertParam.nWidth = stFrame.stFrameInfo.nWidth stConvertParam.nHeight = stFrame.stFrameInfo.nHeight stConvertParam.enDstPixelType = enDstPixelType stConvertParam.pDstBuffer = DstBuffer stConvertParam.nDstBufferSize = DstBufferlen ret = User.MV_CC_ConvertPixelTypeEx(stConvertParam) if ret != 0: print ("convert pixel fail! ret[0x%x]" % ret) break if nChannelNum == 1: numpy_image = numpy.frombuffer(DstBuffer, dtype=numpy.ubyte, count=DstBufferlen). \ reshape(stFrame.stFrameInfo.nHeight, stFrame.stFrameInfo.nWidth) # 执行1次, 只保存1张图 if g_SaveImageOnce == False: output_path = "output_mono_image.bmp" cv2.imwrite(output_path, numpy_image) print("save output_mono_image.bmp success") g_SaveImageOnce = True else: numpy_image = numpy.frombuffer(DstBuffer, dtype=numpy.ubyte, count=DstBufferlen). \ reshape(stFrame.stFrameInfo.nHeight, stFrame.stFrameInfo.nWidth, 3) #分辨率缩小一半，提高处理速度 numpy_image = cv2.resize(numpy_image, None, fx=0.5, fy=0.5, interpolation=cv2.INTER_AREA) # 1. 预处理：灰度图 + 高斯模糊 (去噪) Gray_image = cv2.cvtColor(numpy_image, cv2.COLOR_BGR2GRAY) # 稍微增大模糊核，例如 (5,5)，以平滑更多纹理细节 Gauss_image = cv2.GaussianBlur(Gray_image, (5, 5), 1) # 2. 二值化替代 Canny (更稳健) # 方法A: Otsu自动阈值 (适合对比度明显的场景) ret, binary = cv2.threshold(Gauss_image, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU) # 方法B: 如果光照不均，建议取消下面注释改用自适应阈值 # binary = cv2.adaptiveThreshold(Gauss_image, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, # cv2.THRESH_BINARY, 11, 2) # 3. 形态学操作 (关键步骤：连接断裂，去除噪点) kernel = numpy.ones((3,3),numpy.uint8) # 核越大，连接能力越强，但也可能使物体变形 dilated_binary = cv2.dilate(binary, kernel, iterations=1) # 膨胀 eroded_binary = cv2.erode(dilated_binary, kernel, iterations=1) # 腐蚀 (先膨胀后腐蚀=闭运算，用于填补空洞) # 4. 查找轮廓 # 注意：二值化图像中，物体应为白色(255)，背景为黑色(0) contours, _ = cv2.findContours(eroded_binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) for cnt in contours: cv2.drawContours(numpy_image, [cnt], -1, (0, 255, 0), 1) # 绘制原始轮廓，调试用 # --- 筛选条件 1: 面积过滤 --- # 忽略太小的噪点，根据实际情况调整数值 (例如忽略小于画面 1% 的区域) area = cv2.contourArea(cnt) if area < threshold_area: continue # --- 筛选条件 2: 形状近似,必须是四边形且为凸多边形 --- epsilon = 0.02 * cv2.arcLength(cnt, True) approx = cv2.approxPolyDP(cnt, epsilon, True) if len(approx) == 4 and cv2.isContourConvex(approx): # 绘制结果 cv2.drawContours(numpy_image, [approx], -1, (0, 0, 255), 2) # 绘制顶点 for point in approx: cv2.circle(numpy_image, tuple(point[0]), 5, (255, 0, 0), -1) # fps计算 current_time = cv2.getTickCount() fps = cv2.getTickFrequency() / (current_time - start_time) text = f"FPS: {fps:.2f}" # 在左上角绘制文字 cv2.putText(numpy_image, text, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2) # 显示结果 cv2.imshow('Result', numpy_image) cv2.imshow('Binary', eroded_binary) # 调试时可查看二值化效果 # cv2.imshow("ROI", img_ROI) cv2.waitKey(1) # 执行1次, 只保存1张图 # if g_SaveImageOnce == False: # output_path = "output_color_image.bmp" # cv2.imwrite(output_path, numpy_image) # print("save output_color_image.bmp success") # g_SaveImageOnce = True #正常退出 break #非自动释放模式，需要额外进行 手动释放资源 if bAutoFree == False : if pUser != None: User.MV_CC_FreeImageBuffer(stFrame) else : print ("user is null, invalid") CALL_BACK_FUN2 = FrameInfoCallBack2(image_callback2) if __name__ == "__main__": # ch:初始化SDK | en: initialize SDK MvCamera.MV_CC_Initialize() deviceList = MV_CC_DEVICE_INFO_LIST() # ch:选择枚举的传输层协议 (根据需求和系统支持情况选择) | en: Select the Transport Layer Protocol (based on your requirements and system support). tlayerType = (MV_GIGE_DEVICE | MV_USB_DEVICE | MV_GENTL_CAMERALINK_DEVICE | MV_GENTL_CXP_DEVICE | MV_GENTL_XOF_DEVICE) # ch:枚举设备 | en:Enum device ret = MvCamera.MV_CC_EnumDevices(tlayerType, deviceList) if ret != 0: print ("enum devices fail! ret[0x%x]" % ret) sys.exit() if deviceList.nDeviceNum == 0: print ("find no device!") sys.exit() print ("find %d devices!" % deviceList.nDeviceNum) for i in range(0, deviceList.nDeviceNum): mvcc_dev_info = cast(deviceList.pDeviceInfo[i], POINTER(MV_CC_DEVICE_INFO)).contents if mvcc_dev_info.nTLayerType == MV_GIGE_DEVICE or mvcc_dev_info.nTLayerType == MV_GENTL_GIGE_DEVICE: print ("\ngige device: [%d]" % i) strModeName = ''.join([chr(c) for c in mvcc_dev_info.SpecialInfo.stGigEInfo.chModelName if c != 0]) print ("device model name: %s" % strModeName) nip1 = ((mvcc_dev_info.SpecialInfo.stGigEInfo.nCurrentIp & 0xff000000) >> 24) nip2 = ((mvcc_dev_info.SpecialInfo.stGigEInfo.nCurrentIp & 0x00ff0000) >> 16) nip3 = ((mvcc_dev_info.SpecialInfo.stGigEInfo.nCurrentIp & 0x0000ff00) >> 8) nip4 = (mvcc_dev_info.SpecialInfo.stGigEInfo.nCurrentIp & 0x000000ff) print ("current ip: %d.%d.%d.%d\n" % (nip1, nip2, nip3, nip4)) elif mvcc_dev_info.nTLayerType == MV_USB_DEVICE: print ("\nu3v device: [%d]" % i) strModeName = ''.join([chr(c) for c in mvcc_dev_info.SpecialInfo.stUsb3VInfo.chModelName if c != 0]) print ("device model name: %s" % strModeName) strSerialNumber = ''.join([chr(c) for c in mvcc_dev_info.SpecialInfo.stUsb3VInfo.chSerialNumber if c != 0]) print ("user serial number: %s" % strSerialNumber) elif mvcc_dev_info.nTLayerType == MV_GENTL_CAMERALINK_DEVICE: print ("\nCML device: [%d]" % i) strModeName = ''.join([chr(c) for c in mvcc_dev_info.SpecialInfo.stCMLInfo.chModelName if c != 0]) print ("device model name: %s" % strModeName) strSerialNumber = ''.join([chr(c) for c in mvcc_dev_info.SpecialInfo.stCMLInfo.chSerialNumber if c != 0]) print ("user serial number: %s" % strSerialNumber) elif mvcc_dev_info.nTLayerType == MV_GENTL_CXP_DEVICE: print ("\nCXP device: [%d]" % i) strModeName = ''.join([chr(c) for c in mvcc_dev_info.SpecialInfo.stCXPInfo.chModelName if c != 0]) print ("device model name: %s" % strModeName) strSerialNumber = ''.join([chr(c) for c in mvcc_dev_info.SpecialInfo.stCXPInfo.chSerialNumber if c != 0]) print ("user serial number: %s" % strSerialNumber) elif mvcc_dev_info.nTLayerType == MV_GENTL_XOF_DEVICE: print ("\nXoF device: [%d]" % i) strModeName = ''.join([chr(c) for c in mvcc_dev_info.SpecialInfo.stXoFInfo.chModelName if c != 0]) print ("device model name: %s" % strModeName) strSerialNumber = ''.join([chr(c) for c in mvcc_dev_info.SpecialInfo.stXoFInfo.chSerialNumber if c != 0]) print ("user serial number: %s" % strSerialNumber) # nConnectionNum = input_func("please input_func the number of the device to connect:") nConnectionNum = 0 if int(nConnectionNum) >= deviceList.nDeviceNum: print ("intput error!") sys.exit() # ch:创建相机实例 | en:Creat Camera Object cam = MvCamera() # ch:选择设备并创建句柄 | en:Select device and create handle stDeviceList = cast(deviceList.pDeviceInfo[int(nConnectionNum)], POINTER(MV_CC_DEVICE_INFO)).contents ret = cam.MV_CC_CreateHandle(stDeviceList) if ret != 0: print ("create handle fail! ret[0x%x]" % ret) sys.exit() # ch:打开设备 | en:Open device ret = cam.MV_CC_OpenDevice(MV_ACCESS_Exclusive, 0) if ret != 0: print ("open device fail! ret[0x%x]" % ret) sys.exit() # ch:探测网络最佳包大小(只对GigE相机有效) | en:Detection network optimal package size(It only works for the GigE camera) if stDeviceList.nTLayerType == MV_GIGE_DEVICE or stDeviceList.nTLayerType == MV_GENTL_GIGE_DEVICE: nPacketSize = cam.MV_CC_GetOptimalPacketSize() if int(nPacketSize) > 0: ret = cam.MV_CC_SetIntValue("GevSCPSPacketSize",nPacketSize) if ret != 0: print ("Warning: Set Packet Size fail! ret[0x%x]" % ret) else: print ("Warning: Get Packet Size fail! ret[0x%x]" % nPacketSize) # ch:设置触发模式为off | en:Set trigger mode as off ret = cam.MV_CC_SetEnumValue("TriggerMode", MV_TRIGGER_MODE_OFF) if ret != 0: print ("set trigger mode fail! ret[0x%x]" % ret) sys.exit() # ch:注册抓图回调 | en:Register image callback ret = cam.MV_CC_RegisterImageCallBackEx2(CALL_BACK_FUN2, ctypes.py_object(cam), True) if ret != 0: print ("register image callback fail! ret[0x%x]" % ret) sys.exit() # ch:开始取流 | en:Start grab image ret = cam.MV_CC_StartGrabbing() if ret != 0: print ("start grabbing fail! ret[0x%x]" % ret) sys.exit() print ("press Enter key to stop grabbing.") input_func() cv2.destroyAllWindows() # ch:停止取流 | en:Stop grab image ret = cam.MV_CC_StopGrabbing() if ret != 0: print ("stop grabbing fail! ret[0x%x]" % ret) sys.exit() # ch:关闭设备 | Close device ret = cam.MV_CC_CloseDevice() if ret != 0: print ("close deivce fail! ret[0x%x]" % ret) sys.exit() # ch:销毁句柄 | Destroy handle ret = cam.MV_CC_DestroyHandle() if ret != 0: print ("destroy handle fail! ret[0x%x]" % ret) sys.exit() # ch:反初始化SDK | en: finalize SDK MvCamera.MV_CC_Finalize()