Opencv 4 2 0

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The name of the virtual environment. To exit the virtual environment, use the deactivate command.Once inside the virtual environment, you can now install OpenCV. Execute the command below.pip3 install opencv-pythonInstall OpenCV with pipFrom the image above, you can see we have successfully installed OpenCV version 4.5.1.48. That’s it! You are done with OpenCV installation. To test OpenCV in your project, skip to the Test section at the bottom of the article.Method 2: Install OpenCV from the sourceIf you need a full installation of OpenCV, which includes patented algorithms, then you should use this method. Unlike the pip install method, which only takes a couple of minutes, compiling OpenCV from the source can take around two (2) hours. Follow the steps below:Step 1. Activate your virtual environment with the workon command below.workon sbb_cvStep 2. Download the source code for both OpenCV and Opencv_contrib from Github. Use the wget commands below.wget -O opencv_contrib.zip -O opencv.zip you get an error like ‘wget command not found,’ then you will need to install it with the command – sudo apt install wgetStep 3. We need to unzip the contents of the two files we downloaded. Use the unzip command as shown below:unzip opencv.zipunzip opencv_contrib.zipStep 4. After extracting the zip files, we will have two folders – opencv-4.5.2 and opencv_contrib-4.5.1. Let’s rename these two to something memorable like opencv and opencv_contrib.mv opencv-4.5.2 opencvmv opencv_contrib-4.5.1 opencv_contribRename foldersStep 5. Compiling OpenCV can be quite heavy on the Raspberry Pi memory. To avoid freezing or hanging, we can increase the SWAP space and utilize all four cores of the Pi in the compiling process. To do so, we will edit the dphys-swapfile present in the /etc. directory. Execute the command below to open dphys-swapfile with the nano editor.sudo nano /etc/dphys-swapfileFind the line – CONF_SWAPSIZE and set its value to

Nonzerox[left_lane_inds]lefty = nonzeroy[left_lane_inds] rightx = nonzerox[right_lane_inds]righty = nonzeroy[right_lane_inds]return leftx, lefty, rightx, righty, out_imgdef fit_polynomial_first_lane(binary_warped):leftx, lefty, rightx, righty, out_img = find_lane_pixels(binary_warped)left_fit = np.polyfit(lefty, leftx, 2)right_fit = np.polyfit(righty, rightx, 2)ploty = np.linspace(0, binary_warped.shape[0]-1, binary_warped.shape[0])try:left_fitx = left_fit[0] * ploty2 + left_fit[1] * ploty + left_fit[2]right_fitx = right_fit[0] * ploty2 + right_fit[1] * ploty + right_fit[2]except TypeError:print('The function failed to fit a line!')left_fitx = 1 * ploty2 + 1 * plotyright_fitx = 1 * ploty2 + 1 * plotyout_img[lefty, leftx] = [255, 0, 0]out_img[righty, rightx] = [0, 0, 255]left_pts = np.transpose(np.vstack((left_fitx, ploty))).astype(np.int32)right_pts = np.transpose(np.vstack((right_fitx, ploty))).astype(np.int32)cv2.polylines(out_img, np.int32([left_pts]), False, (255, 255, 0), thickness=5)cv2.polylines(out_img, np.int32([right_pts]), False, (255, 255, 0), thickness=5)return left_fit, right_fit, out_imgbinary_warped pixel range: 0 to 255binary_warped shape: (720, 1280, 3), type: uint8out_img shape: (720, 1280, 9), type: uint8error Traceback (most recent call last) in ()146147 # Find lane pixels and fit polynomial--> 148 left_fit, right_fit, out_img = fit_polynomial_first_lane(binary_warped)149150 # Plot the results1 frames in find_lane_pixels(binary_warped)66 win_xright_high = min(binary_warped.shape[1], win_xright_high)67---> 68 cv2.rectangle(out_img, (win_xleft_low, win_y_low), (win_xleft_high, win_y_high), (0, 255, 0), 2)69 cv2.rectangle(out_img, (win_xright_low, win_y_low), (win_xright_high, win_y_high), (0, 255, 0), 2)70error: OpenCV(4.8.0) /io/opencv/modules/core/src/copy.cpp:71: error: (-215:Assertion failed) cn

🐛 BugI think it's a small problem but I still can't future it out ..I want to accomplish inference feature using libtorch and OpenCV . So I downloaded the last libtorch(GPU) from Pytorch.org. And also build OpenCV(4.0.0) from source.When I build libtorch app and OpenCV app with cmake independently, it succeeds.And when I build libtorch and OpenCV together and don't use 'imread()' function,it succeeds. And the code works in GPU(speed faster than CPU):#include "torch/script.h"#include "torch/torch.h"#include #include #include using namespace std;using namespace cv;int main(int argc, const char* argv[]){ if (argc != 2) { std::cerr \n"; return -1; } std::shared_ptr module = torch::jit::load(argv[1]); std::vector inputs; inputs.push_back(torch::ones({1,3,224,224}).to(at::kCUDA)); module->to(at::kCUDA); // inputs.at[0].to(at::kCUDA); double timeStart = (double)getTickCount(); for(int i = 0 ; i forward(inputs).toTensor(); double nTime = ((double)getTickCount() - timeStart) / getTickFrequency(); cout #include opencv2/opencv.hpp>#include "torch/script.h"#include "torch/torch.h"#include iostream>#include memory>#include ctime>using namespace std;using namespace cv;int main(int argc, const char* argv[]){ if (argc != 2) { std::cerr "usage: example-app \n"; return -1; } std::shared_ptr module = torch::jit::load(argv[1]); std::vector inputs; inputs.push_back(torch::ones({1,3,224,224}).to(at::kCUDA)); module->to(at::kCUDA); // inputs.at[0].to(at::kCUDA); double timeStart = (double)getTickCount(); for(int i = 0 ; i 1000 ; i++) at::Tensor output = module->forward(inputs).toTensor(); double nTime = ((double)getTickCount() - timeStart) / getTickFrequency(); cout "Time used:" 1000 " ms" the CMakeLists:cmake_minimum_required(VERSION 3.12 FATAL_ERROR)project(simnet)find_package(Torch REQUIRED)find_package(OpenCV REQUIRED)if(NOT Torch_FOUND) message(FATAL_ERROR "Pytorch Not Found!")endif(NOT Torch_FOUND)message(STATUS "Pytorch status:")message(STATUS " libraries: ${TORCH_LIBRARIES}")message(STATUS "OpenCV library status:")message(STATUS " version: ${OpenCV_VERSION}")message(STATUS " libraries: ${OpenCV_LIBS}")message(STATUS " include path: ${OpenCV_INCLUDE_DIRS}")add_executable(simnet main.cpp)# link_directories(/usr/local/lib) 'find_package' has already done thistarget_link_libraries(simnet ${TORCH_LIBRARIES} ${OpenCV_LIBS})set_property(TARGET simnet PROPERTY CXX_STANDARD 11)and cmake config:/home/prototype/Downloads/clion-2018.3/bin/cmake/linux/bin/cmake -DCMAKE_BUILD_TYPE=Debug -DCMAKE_PREFIX_PATH=/home/prototype/Desktop/Cuda-project/libtorch -G "CodeBlocks - Unix Makefiles" /home/prototype/CLionProjects/simnet-- The C compiler identification is GNU 7.3.0-- The CXX compiler identification is GNU 7.3.0-- Check for working C compiler: /usr/bin/cc-- Check for working C compiler: /usr/bin/cc -- works-- Detecting C compiler ABI info-- Detecting C compiler ABI info - done-- Detecting C compile features-- Detecting C compile features - done-- Check for working CXX compiler: /usr/bin/c++-- Check for working CXX compiler: /usr/bin/c++ -- works-- Detecting CXX compiler ABI info-- Detecting CXX compiler ABI info - done-- Detecting CXX compile features-- Detecting CXX compile features - done-- Looking for pthread.h-- Looking for pthread.h - found-- Looking for pthread_create-- Looking for pthread_create -