小编Ama*_*h R的帖子

图像处理 - 使用opencv进行着装分割

图片

我正在使用opencv进行服装特征识别.作为第一步,我需要通过从图像中移除面部和手部来分割T恤.任何建议表示赞赏.

matlab image-processing computer-vision image-segmentation opencv3.0

14
推荐指数
1
解决办法
2206
查看次数

在 ubuntu 18.04 上使用 libnvinfer7 库(Cuda 10.2)安装 TensorRT 面临的问题

我试图在 ubuntu 18.4 (nv-tensorrt-repo-ubuntu1804-cuda10.2-trt7.0.0.11-ga-20191216_1-1_amd64.deb) debian 中安装 tensorRT 7.0。

遵循文档https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html#installing-debian

我在使用 libnvinfer7 时遇到以下错误。在这个星球上寻找这个,无法找到,浪费了我的时间和睡眠。请帮我解决这个问题:

 amarnath@amarnath-Precision-T3610:/opt/pixuate$ sudo apt install tensorrt
    Reading package lists... Done
    Building dependency tree       
    Reading state information... Done
    Some packages could not be installed. This may mean that you have
    requested an impossible situation or if you are using the unstable
    distribution that some required packages have not yet been created
    or been moved out of Incoming.
    The following information may help to resolve the situation:

    The following …
Run Code Online (Sandbox Code Playgroud)

nvidia tensorrt nvidia-deepstream

8
推荐指数
1
解决办法
8135
查看次数

C ++ OpenCV:将mat转换为base64,反之亦然

无论如何,都可以将opencv mat对象转换为base64。

我使用下面的URL进行base64编码和解码:

http://www.adp-gmbh.ch/cpp/common/base64.html

下面是代码片段:

const unsigned char * inBuffer = reinterpret_cast(image.data);

c++ opencv image-processing

4
推荐指数
2
解决办法
9209
查看次数

在Windows上使用mingw32-make时opencv安装错误

在Windows 10平台上使用mingw32-make命令进行opencv安装,然后可能最终得到以下错误.

Windows版本:10 OpenCv:3.2.0

请建议我安装.

D:\installers\opencv\sources\modules\ts\src\ts_gtest.cpp: In constructor 'testing::internal::Mutex::Mutex()':
D:\installers\opencv\sources\modules\ts\src\ts_gtest.cpp:8829:45: error: cannot convert 'CRITICAL_SECTION* {aka _CRITICAL_SECTION*}' to '_RTL_CRITICAL_SECTION*' in initialization
       critical_section_(new CRITICAL_SECTION) {
                                             ^
D:\installers\opencv\sources\modules\ts\src\ts_gtest.cpp:8830:48: error: cannot convert '_RTL_CRITICAL_SECTION*' to 'LPCRITICAL_SECTION {aka _CRITICAL_SECTION*}' for argument '1' to 'void InitializeCriticalSection(LPCRITICAL_SECTION)'
   ::InitializeCriticalSection(critical_section_);
                                                ^
D:\installers\opencv\sources\modules\ts\src\ts_gtest.cpp: In destructor 'testing::internal::Mutex::~Mutex()':
D:\installers\opencv\sources\modules\ts\src\ts_gtest.cpp:8840:46: error: cannot convert '_RTL_CRITICAL_SECTION*' to 'PCRITICAL_SECTION {aka _CRITICAL_SECTION*}' for argument '1' to 'void DeleteCriticalSection(PCRITICAL_SECTION)'
     ::DeleteCriticalSection(critical_section_);
                                              ^
D:\installers\opencv\sources\modules\ts\src\ts_gtest.cpp: In member function 'void testing::internal::Mutex::Lock()':
D:\installers\opencv\sources\modules\ts\src\ts_gtest.cpp:8848:43: error: cannot convert '_RTL_CRITICAL_SECTION*' to 'LPCRITICAL_SECTION {aka _CRITICAL_SECTION*}' for argument '1' …
Run Code Online (Sandbox Code Playgroud)

opencv mingw mingw-w64

4
推荐指数
1
解决办法
2563
查看次数

如何使用amazon aws ec2保留实例?

最近我购买了一个预留的实例EC2 t2.medium.

没有选项可以启动和停止,而我的免费装备具有所有功能,包括停止,启动,公共IP等.

请建议我,如何使用和解决保留实例||

amazon-ec2 amazon-web-services

3
推荐指数
1
解决办法
817
查看次数

Tensorflow - Keras:考虑关闭自动分片或将 auto_shard_policy 切换为 DATA 以对该数据集进行分片

在 keras / tensorflow 中训练模型时:

代码片段:

strategy = tf.distribute.experimental.MultiWorkerMirroredStrategy()
Run Code Online (Sandbox Code Playgroud)

我收到以下错误/警告:

Consider either turning off auto-sharding or switching the auto_shard_policy to DATA to shard this dataset. You can do this by creating a new `tf.data.Options()` object then setting `options.experimental_distribute.auto_shard_policy = AutoShardPolicy.DATA` before applying the options object to the dataset via `dataset.with_options(options)`.
    2020-12-16 17:12:20.885741: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:127] None of the MLIR optimization passes are enabled (registered 2)
    2020-12-16 17:12:20.905570: I tensorflow/core/platform/profile_utils/cpu_utils.cc:112] CPU Frequency: 3593105000 Hz
    Epoch 1/40
Run Code Online (Sandbox Code Playgroud)

任何帮助表示赞赏。

keras tensorflow

3
推荐指数
1
解决办法
3330
查看次数