/** * 增加指定摄像机预置位 * * @param cameraCode * 摄像机编码 * @param presetName * 预置位名字 * @return SDKResult<Integer> 领域层封装的返回码对象 * @see [类、类#方法、类#成员] * @since [eSDK IVS V100R003C00] */ @Override public SDKResult<Integer> addPTZPreset(String cameraCode, String presetName) { int sessionId = super.getIVSSessionId(); ByReference presetIndex = new IntByReference(-1); // modify by cWX191990, IVS // Bug:该接口的presetName不支持传String,且转成byte后还要固定长度84 // 长度实际为20个字节,为防止溢出,定义长度为84 int resultCode = super.getBaseCablilityJNA().IVS_SDK_AddPTZPreset(sessionId, cameraCode, BytesUtils.stringToBytesForIVS(presetName, CommonConstant.BusinessModule.IVS_PRESET_NAME_LEN), presetIndex); // 转换成领域层的bean SDKResult<Integer> result = new SDKResult<Integer>(); if (0 == resultCode) { result.setResult(((IntByReference) presetIndex).getValue()); } result.setErrCode(resultCode); return result; }
/** * 增加用户 * * @param userInfo 用户信息 * @return SDKResult<Integer> 封装领域层的SDKResult对象 * @since eSDK IVS V100R003C00 */ @Override public SDKResult<Integer> addUser(UserInfo userInfo) { int sessionId = getIVSSessionId(); SDKResult<Integer> response = new SDKResult<Integer>(); UserInfoSouth userInfoSouth = userMgrSouthConvert.getUserInfoModal2Soap(userInfo); ByReference refuserId = new IntByReference(-1); int errCode = super.getBaseCablilityJNA().IVS_SDK_AddUser(sessionId, userInfoSouth, refuserId); response.setErrCode(errCode); if (0 == errCode) { response.setResult(((IntByReference)refuserId).getValue()); } return response; }
public void convolutionBackwardFilter( ByReference alpha, cudnnTensorDescriptor_t srcDesc, Pointer srcData, cudnnTensorDescriptor_t diffDesc, Pointer diffData, cudnnConvolutionDescriptor_t convDesc, int algo, Pointer workSpace, int workSpaceSizeInBytes, ByReference beta, cudnnFilterDescriptor_t gradDesc, Pointer gradData) throws CudnnException { checkError(library.get().cudnnConvolutionBackwardFilter_v3( handle, alpha, srcDesc, srcData, diffDesc, diffData, convDesc, algo, workSpace, workSpaceSizeInBytes, beta, gradDesc, gradData)); }
public void convolutionBackwardData( ByReference alpha, cudnnFilterDescriptor_t filterDesc, Pointer filterData, cudnnTensorDescriptor_t diffDesc, Pointer diffData, cudnnConvolutionDescriptor_t convDesc, int algo, Pointer workSpace, int workSpaceSizeInBytes, ByReference beta, cudnnTensorDescriptor_t gradDesc, Pointer gradData) throws CudnnException { checkError(library.get().cudnnConvolutionBackwardData_v3( handle, alpha, filterDesc, filterData, diffDesc, diffData, convDesc, algo, workSpace, workSpaceSizeInBytes, beta, gradDesc, gradData)); }
public int cudnnConvolutionBackwardFilter_v3( cudnnHandle_t handle, ByReference alpha, cudnnTensorDescriptor_t srcDesc, Pointer srcData, cudnnTensorDescriptor_t diffDesc, Pointer diffData, cudnnConvolutionDescriptor_t convDesc, int algo, Pointer workSpace, int workSpaceSizeInBytes, ByReference beta, cudnnFilterDescriptor_t gradDesc, Pointer gradData);
public int cudnnConvolutionBackwardData_v3( cudnnHandle_t handle, ByReference alpha, cudnnFilterDescriptor_t filterDesc, Pointer filterData, cudnnTensorDescriptor_t diffDesc, Pointer diffData, cudnnConvolutionDescriptor_t convDesc, int algo, Pointer workSpace, int workSpaceSizeInBytes, ByReference beta, cudnnTensorDescriptor_t gradDesc, Pointer gradData);
protected ByReference newByReference() { ByReference s = new ByReference(); s.useMemory(getPointer()); write(); s.read(); return s; }
boolean GetQueuedCompletionStatus(HANDLE CompletionPort, IntByReference lpNumberOfBytes, ByReference lpCompletionKey, PointerByReference lpOverlapped, int dwMilliseconds);
public static ByReference const1(FloatType floatType) { if(floatType==FloatType.SINGLE) return FLOAT_1; else return DOUBLE_1; }
public static ByReference const0(FloatType floatType) { if(floatType==FloatType.SINGLE) return FLOAT_0; else return DOUBLE_0; }
/** * Function to perform the forward multiconvolution<br> * Original signature : <code>cudnnStatus_t cudnnConvolutionForward(cudnnHandle_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnFilterDescriptor_t, const void*, const cudnnConvolutionDescriptor_t, cudnnConvolutionFwdAlgo_t, void*, size_t, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 407</i> * @throws CudnnException */ public void convolutionForward(ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, CudnnLibrary.cudnnFilterDescriptor_t filterDesc, Pointer filterData, CudnnLibrary.cudnnConvolutionDescriptor_t convDesc, int algo, Pointer workSpace, int workSpaceSizeInBytes, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData) throws CudnnException { checkError(library.get().cudnnConvolutionForward(handle, alpha, srcDesc, srcData, filterDesc, filterData, convDesc, algo, workSpace, workSpaceSizeInBytes, beta, destDesc, destData)); }
/** * Tensor Bias addition : srcDest = alpha * bias + beta * srcDestDesc<br> * Original signature : <code>cudnnStatus_t cudnnAddTensor(cudnnHandle_t, cudnnAddMode_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 229</i> * @throws CudnnException */ public void addTensor(int mode, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t biasDesc, Pointer biasData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t srcDestDesc, Pointer srcDestData) throws CudnnException { checkError(library.get().cudnnAddTensor(handle, mode, alpha, biasDesc, biasData, beta, srcDestDesc, srcDestData)); }
/** * Function to perform forward pooling<br> * Original signature : <code>cudnnStatus_t cudnnPoolingForward(cudnnHandle_t, const cudnnPoolingDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 581</i> * @throws CudnnException */ public void poolingForward(CudnnLibrary.cudnnPoolingDescriptor_t poolingDesc, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData) throws CudnnException { checkError(library.get().cudnnPoolingForward(handle, poolingDesc, alpha, srcDesc, srcData, beta, destDesc, destData)); }
/** * Function to perform forward activation<br> * Original signature : <code>cudnnStatus_t cudnnActivationForward(cudnnHandle_t, cudnnActivationMode_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 619</i> * @throws CudnnException */ public void activationForward(int mode, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData) throws CudnnException { checkError(library.get().cudnnActivationForward(handle, mode, alpha, srcDesc, srcData, beta, destDesc, destData)); }
/** * Function to perform forward softmax<br> * Original signature : <code>cudnnStatus_t cudnnSoftmaxForward(cudnnHandle_t, cudnnSoftmaxAlgorithm_t, cudnnSoftmaxMode_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 487</i> * @throws CudnnException */ public void softmaxForward(int algorithm, int mode, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData) throws CudnnException { checkError(library.get().cudnnSoftmaxForward(handle, algorithm, mode, alpha, srcDesc, srcData, beta, destDesc, destData)); }
/** * Function to perform backward activation<br> * Original signature : <code>cudnnStatus_t cudnnActivationBackward(cudnnHandle_t, cudnnActivationMode_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 630</i> * @throws CudnnException */ public void activationBackward(int mode, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, CudnnLibrary.cudnnTensorDescriptor_t srcDiffDesc, Pointer srcDiffData, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDiffDesc, Pointer destDiffData) throws CudnnException { checkError(library.get().cudnnActivationBackward(handle, mode, alpha, srcDesc, srcData, srcDiffDesc, srcDiffData, destDesc, destData, beta, destDiffDesc, destDiffData)); }
/** * Function to perform backward pooling<br> * Original signature : <code>cudnnStatus_t cudnnPoolingBackward(cudnnHandle_t, const cudnnPoolingDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 592</i> * @throws CudnnException */ public void poolingBackward(CudnnLibrary.cudnnPoolingDescriptor_t poolingDesc, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, CudnnLibrary.cudnnTensorDescriptor_t srcDiffDesc, Pointer srcDiffData, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDiffDesc, Pointer destDiffData) throws CudnnException { checkError(library.get().cudnnPoolingBackward(handle, poolingDesc, alpha, srcDesc, srcData, srcDiffDesc, srcDiffData, destDesc, destData, beta, destDiffDesc, destDiffData)); }
/** * Functions to perform the backward multiconvolution<br> * Original signature : <code>cudnnStatus_t cudnnConvolutionBackwardBias(cudnnHandle_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 423</i> * @throws CudnnException */ public void convolutionBackwardBias(ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData) throws CudnnException { checkError(library.get().cudnnConvolutionBackwardBias(handle, alpha, srcDesc, srcData, beta, destDesc, destData)); }
/** * Original signature : <code>cudnnStatus_t cudnnConvolutionBackwardFilter(cudnnHandle_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnConvolutionDescriptor_t, const void*, const cudnnFilterDescriptor_t, void*)</code><br> * <i>native declaration : line 434</i> * @throws CudnnException */ public void convolutionBackwardFilter(ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, CudnnLibrary.cudnnTensorDescriptor_t diffDesc, Pointer diffData, CudnnLibrary.cudnnConvolutionDescriptor_t convDesc, ByReference beta, CudnnLibrary.cudnnFilterDescriptor_t gradDesc, Pointer gradData) throws CudnnException { checkError(library.get().cudnnConvolutionBackwardFilter(handle, alpha, srcDesc, srcData, diffDesc, diffData, convDesc, beta, gradDesc, gradData)); }
/** * Original signature : <code>cudnnStatus_t cudnnConvolutionBackwardData(cudnnHandle_t, const void*, const cudnnFilterDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnConvolutionDescriptor_t, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 447</i> * @throws CudnnException */ public void convolutionBackwardData(ByReference alpha, CudnnLibrary.cudnnFilterDescriptor_t filterDesc, Pointer filterData, CudnnLibrary.cudnnTensorDescriptor_t diffDesc, Pointer diffData, CudnnLibrary.cudnnConvolutionDescriptor_t convDesc, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t gradDesc, Pointer gradData) throws CudnnException { checkError(library.get().cudnnConvolutionBackwardData(handle, alpha, filterDesc, filterData, diffDesc, diffData, convDesc, beta, gradDesc, gradData)); }
/** * Tensor Bias addition : srcDest = alpha * bias + beta * srcDestDesc<br> * Original signature : <code>cudnnStatus_t cudnnAddTensor(cudnnHandle_t, cudnnAddMode_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 229</i> */ int cudnnAddTensor(CudnnLibrary.cudnnHandle_t handle, int mode, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t biasDesc, Pointer biasData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t srcDestDesc, Pointer srcDestData);
/** * Function to perform the forward multiconvolution<br> * Original signature : <code>cudnnStatus_t cudnnConvolutionForward(cudnnHandle_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnFilterDescriptor_t, const void*, const cudnnConvolutionDescriptor_t, cudnnConvolutionFwdAlgo_t, void*, size_t, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 407</i> */ int cudnnConvolutionForward(CudnnLibrary.cudnnHandle_t handle, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, CudnnLibrary.cudnnFilterDescriptor_t filterDesc, Pointer filterData, CudnnLibrary.cudnnConvolutionDescriptor_t convDesc, int algo, Pointer workSpace, int workSpaceSizeInBytes, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData);
/** * Functions to perform the backward multiconvolution<br> * Original signature : <code>cudnnStatus_t cudnnConvolutionBackwardBias(cudnnHandle_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 423</i> */ int cudnnConvolutionBackwardBias(CudnnLibrary.cudnnHandle_t handle, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData);
/** * Original signature : <code>cudnnStatus_t cudnnConvolutionBackwardFilter(cudnnHandle_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnConvolutionDescriptor_t, const void*, const cudnnFilterDescriptor_t, void*)</code><br> * <i>native declaration : line 434</i> */ int cudnnConvolutionBackwardFilter(CudnnLibrary.cudnnHandle_t handle, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, CudnnLibrary.cudnnTensorDescriptor_t diffDesc, Pointer diffData, CudnnLibrary.cudnnConvolutionDescriptor_t convDesc, ByReference beta, CudnnLibrary.cudnnFilterDescriptor_t gradDesc, Pointer gradData);
/** * Original signature : <code>cudnnStatus_t cudnnConvolutionBackwardData(cudnnHandle_t, const void*, const cudnnFilterDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnConvolutionDescriptor_t, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 447</i> */ int cudnnConvolutionBackwardData(CudnnLibrary.cudnnHandle_t handle, ByReference alpha, CudnnLibrary.cudnnFilterDescriptor_t filterDesc, Pointer filterData, CudnnLibrary.cudnnTensorDescriptor_t diffDesc, Pointer diffData, CudnnLibrary.cudnnConvolutionDescriptor_t convDesc, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t gradDesc, Pointer gradData);
/** * Function to perform forward softmax<br> * Original signature : <code>cudnnStatus_t cudnnSoftmaxForward(cudnnHandle_t, cudnnSoftmaxAlgorithm_t, cudnnSoftmaxMode_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 487</i> */ int cudnnSoftmaxForward(CudnnLibrary.cudnnHandle_t handle, int algorithm, int mode, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData);
/** * Function to perform forward pooling<br> * Original signature : <code>cudnnStatus_t cudnnPoolingForward(cudnnHandle_t, const cudnnPoolingDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 581</i> */ int cudnnPoolingForward(CudnnLibrary.cudnnHandle_t handle, CudnnLibrary.cudnnPoolingDescriptor_t poolingDesc, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData);
/** * Function to perform backward pooling<br> * Original signature : <code>cudnnStatus_t cudnnPoolingBackward(cudnnHandle_t, const cudnnPoolingDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 592</i> */ int cudnnPoolingBackward(CudnnLibrary.cudnnHandle_t handle, CudnnLibrary.cudnnPoolingDescriptor_t poolingDesc, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, CudnnLibrary.cudnnTensorDescriptor_t srcDiffDesc, Pointer srcDiffData, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDiffDesc, Pointer destDiffData);
/** * Function to perform forward activation<br> * Original signature : <code>cudnnStatus_t cudnnActivationForward(cudnnHandle_t, cudnnActivationMode_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 619</i> */ int cudnnActivationForward(CudnnLibrary.cudnnHandle_t handle, int mode, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData);
/** * Function to perform backward activation<br> * Original signature : <code>cudnnStatus_t cudnnActivationBackward(cudnnHandle_t, cudnnActivationMode_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const cudnnTensorDescriptor_t, const void*, const void*, const cudnnTensorDescriptor_t, void*)</code><br> * <i>native declaration : line 630</i> */ int cudnnActivationBackward(CudnnLibrary.cudnnHandle_t handle, int mode, ByReference alpha, CudnnLibrary.cudnnTensorDescriptor_t srcDesc, Pointer srcData, CudnnLibrary.cudnnTensorDescriptor_t srcDiffDesc, Pointer srcDiffData, CudnnLibrary.cudnnTensorDescriptor_t destDesc, Pointer destData, ByReference beta, CudnnLibrary.cudnnTensorDescriptor_t destDiffDesc, Pointer destDiffData);
/** * Copies the {@code CFNumber}'s value into the space pointed to by * {@code value}, as the specified type. If conversion needs to take place, * the conversion rules follow human expectation and not C's promotion and * truncation rules. If the conversion is lossy, or the value is out of * range, false is returned. Best attempt at conversion will still be in * {@code value}. * * @param cfNumber the {@link CFNumberRef} whose value to get. * @param theType {@code cfNumber}'s {@link CFNumberType}. * @param value (Output) A pointer to where the retrieved value should be * written. * @return {@code false} if the conversion is lossy or the value is out of * range, {@code true} otherwise. */ boolean CFNumberGetValue(CFNumberRef cfNumber, CFNumberType theType, ByReference value);
/** * 开始实况浏览 * * @param sessionId 登录成功后的会话ID * @param realplayParam 实况浏览媒体参数 * @param cameraCode 摄像机编码 * @param hWnd 窗口句柄 * @param handle 播放句柄 * @return 成功 0/失败,参见错误码 * @attention <无> * @par 示例 * @code * * @endcode * @see \ref function1Example | fuction2Example * @since [eSDK IVS V100R005C30] */ int IVS_SDK_StartRealPlay(int sessionId, RealplayParam realplayParam, byte[] cameraCode, HWND hWnd, ByReference handle);
/****************************************************************** function : IVS_SDK_PtzControl description : 云镜控制 input : iSessionID 登录成功后的会话ID cameraCode 摄像机编码 controlCode 云台控制码,值参考IVS_PTZ_CODE controlPara1 参数1 controlPara2 参数2 output : lockStatus 云台锁定状态:0-解锁,1-锁定 return : 成功返回0(IVS_SUCCEED);失败返回错误码 *******************************************************************/ int IVS_SDK_PtzControl(int iSessionID, byte[] cameraCode, int controlCode, String pControlPara1, String pControlPara2, ByReference lockStatus);
/** * 增加用户 * * @param sessionId 登录成功后的会话ID * @param userInfo 用户信息 * @param userId 增加成功返回的userId * @return 成功返回0,失败返回错误码 * @code * <示例代码(示例代码如果添加注释,请使用//)> * @endcode * @see \ref function1Example | fuction2Example * @since [eSDK IVS V100R003C00] */ public int IVS_SDK_AddUser(int sessionId, UserInfoSouth userInfo, ByReference userId);
/** * 获取用户Id * * @param sessionId 登录成功后的会话ID * @param domainCode 领域码 * @param userId 查询的userId * @return 成功返回0,失败返回错误码 * @code * <示例代码(示例代码如果添加注释,请使用//)> * @endcode * @see \ref function1Example | fuction2Example * @since [eSDK IVS V100R003C00] */ public int IVS_SDK_GetUserID(int sessionId, ByReference userId);
/** * 增加指定摄像机预置位 * * @param sessionId 登录成功后的会话ID * @param cameraCode 摄像机编码 * @param presetName 预置位名称 * @param uiPresetIndex 预置位编号 * @return 成功 0/失败,参见错误码 * @attention <无> * @par 示例 * @code * * @endcode * @see \ref function1Example | fuction2Example * @since [eSDK IVS V100R003C00] */ public int IVS_SDK_AddPTZPreset(int sessionId, String cameraCode, byte[] presetName, ByReference presetIndex);
/** * 开始实况浏览 * * @param sessionId 登录成功后的会话ID * @param realplayParamSouth 实况浏览媒体参数 * @param cameraCode 摄像机编码 * @param mediaAddrDst 媒体流目标地址 * @param mediaAddrSrc 媒体流源地址 * @param handle 播放句柄 * @return 成功 0/失败,参见错误码 * @attention <无> * @par 示例 * @code * * @endcode * @see \ref function1Example | fuction2Example * @since [eSDK IVS V100R003C00] */ public int IVS_SDK_StartRealPlayByIPEx(int sessionId, RealplayParamSouth realplayParamSouth, byte[] cameraCode, MediaAddressSouth mediaAddrDst, Pointer mediaAddrSrc, ByReference handle);
/** * 修改指定摄像机预置位 * * @param sessionId 登录成功后的会话ID * @param cameraCode 摄像机编码 * @param pPTZPresetList 预置位信息列表 * @param bufferSize 缓存大小 * @param ptzPresetNum 预置位信息列表个数 * @return 成功 0/失败,参见错误码 * @attention <无> * @par 示例 * @code * * @endcode * @see \ref function1Example | fuction2Example * @since [eSDK IVS V100R003C00] */ public int IVS_SDK_GetPTZPresetList(int sessionId, byte[] cameraCode, Pointer pPTZPresetList, int bufferSize, ByReference ptzPresetNum);