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hauteculturefashion · 5 years ago

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San Juan La Laguna is a charming town on Lake Atitlan and just a short ride away by water taxi from the buzzing little port town of Panajachel. It was the first town we visited whilst scouting workshops for our Guatemala: Weaving, Embroidery and Community Tour. San Juan has a wonderful communal spirit thanks to the multitude of cooperatives focusing on coffee production, traditional textiles and organic produce. Natural dyeing is incredibly popular in Guatemalan textiles today and San Juan has more than it’s fair share of interesting and insightful places to learn local techniques, in August 2019 we visited the natural dye garden of the Flor Juanera Cooperative in San Juan with our partners from Maya Traditions to find out more about sustainable natural dyeing processors in the community and for the heritage textiles market in general.

A mural of a local Tz’utujil weaver preparing the warp for the back-strap loom. She is wearing a traditional huipil of her community which has a special meaning behind the embroidery and colours.

The artistic spirit of San Juan La Laguna is reflected in the gorgeous murals that welcome you to the village with a creative embrace. These depict scenes from Tz’utujil heritage, including women weaving and men playing musical instruments. The textile community in San Juan is solid, with women in control of most of the dyeing and weaving cottage industry. There are plenty of boutiques selling handmade ikat woven cushions, throws, bags, scarves and shawls and there is a distinct whiff of bohemianism in the air as many travellers decide to stay on in San Juan, immersing themselves in the creative vibes and chill cafe culture.

The native women of the region are creative, entrepreneurial and strong. The mostly Tz’utujil community in this beautiful town still wear traditional cultural garments in their day-to-day lives, the most notable feature being the decorative necklines of their huipils which are embroidered with 24 squares that represent the town’s patron saint, Saint John the Baptist. Their textiles are mostly dyed in red to represent the purity of their ancestral blood, blue for the sky and the lake that envelops the town from above and below, and green for the lush volcanic flora surrounding Lake Atitlan valley. Often, all these colours are combined into a deep purple.

San Juan, Lake Atitlan

Boutiques selling beautiful ikat weaving.

Street art adds to the bohemian vibe.

Our first stop on arrival was the house of one of the artisans, Celeste, who collaborates with Maya Traditions. She was working on the most incredible piece of multi-coloured ikat fabric that included intricate designs of insects, centipedes, love hearts, flowers and butterflies.

So far, she had been working on the fabric for two days, carefully creating the vivid motifs by binding bundles of yarn used for the warp threads of the loom into the desired patterns before dyeing and then over-dyeing the exposed threads. She told us she still had two days’ worth of weaving ahead of her before it was finished.

The piece was part of a big commission that requested she uses synthetic dyes in order to achieve the level of vibrancy desired for the design. Although we were in San Juan to work with natural dyes, the natural ancestral knowledge required was a well-guarded secret for many years which meant that most artisans in the region were actually more familiar with synthetic dyes. It’s only as foreign demand for naturally dyed fabrics has risen over the past twenty-five years that more artisans have reverted back to the traditional techniques for exported goods and souvenirs.

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Celeste explains to us about the time-consuming steps involved to create an ikat resist dye woven masterpiece. The piece she is weaving uses multiple over-dying to highlight and differentiate the motifs in each vertical stripe such as butterflies, centipedes, flowers, trees and hearts.

Six days to finish this masterpiece!

The vivid colours used for the intricate ikat motifs came from synthetic dyes.

After saying goodbye to Celeste we walked up the steep hill to meet the artisans of Flor Juanera Cooperative, or Xe’ Kuku’ Aab’aj in Tz’utujil, and visited their organic, natural dyeing and medicine garden. The garden looks different depending on the season and we got to know the women from the cooperative – Cecilia, María Clara, Elena, Eufemia – whilst we looked through a sample of natural dyes that would be available for our textile tour in March and August. The dyes are mostly made from tree bark, plant leaves, vegetables and coconut shells. The plants give different colours depending on whether they are fresh or dried.

Environmental concerns about synthetic dyes have also caused an increase in demand for naturally dyed textiles. Many chemical-based dyes can enter irrigation systems and have hugely detrimental effects on local communities. However: this doesn’t mean that all products made using natural dyes are always holistic. The demand for natural dyes has left many eco-systems ravished and some plants used for natural dyeing were/are even becoming extinct as most of the raw materials required are taken directly from the local environment rather than purpose-driven farms, therefore resources are rarely re-planted. It’s very important to have sustainability in mind when buying naturally dyed goods. One of the best ways you can ensure you are shopping (or dyeing) sustainably is to visit a co-operative that has its own natural dye garden.

Chilling in the gorgeous natural dye and medicine garden.

Perusing the menu of organic dyes on offer!

Celia prepares to blow our minds with the hot vs cold dye technique.

Eco dyeing with tree bark: learning from the best.

For our workshop that day, we decided to work with Campeche tree. It is really quite a remarkable resource: the dye it produces when cold turns fabric a vivid blue, but when hot the dye turns into a regal purple. This was very exciting to experiment with and something we’d never seen before. Whilst natural dyeing in Mexico we learnt how altering the PH level will affect the colour a dye turns, but the temperature alone was a whole new method to explore with!

We left the fabric we’d bought with us in the dye vat for about 30 minutes and that was long enough to turn it a deep, rich purple. Then all the women helped us to pull a skein in order to wrap the bundles around the threads which create the ikat resist dyeing technique. You need to have a very firm grip and it took four of us to wrap everything together correctly. Spaces are created in the yarn to ensure that the dye doesn’t enter the hidden areas of the yarn when you submerge it in the dye. This means you can create different patterns and re-dye the same fabric with new colours later. We created basic striped patterns but as you can see from the images of Celeste above you can create very sophisticated motifs. The technique we used worked really well (thanks to the expertise of Cecilia, María Clara, Elena and Eufemia) and we were very pleased with the final outcome and colours.

How many artisans does it take to create a resist dye pattern?

The women were so lovely, welcoming us into their homes to share their expertise with us.

We used the fabric and yarn from this workshop again in our bird embroidery workshop taster in Santiago and in the Randa and Ixcaco workshop with the Waqxaqi’ Kan Cooperative. The idea with all the workshops from around Lake Atitlan is that each cooperative teaches us new techniques that are unique to the heritage of that community. This means that throughout the tour, participants can add new layers and skills to a particular garment as they learn new methods from the artisans. We shared this concept with Cecilia, María Clara, Elena, Eufemia and they loved the idea of creating a multi-collaborative piece with the communities working around the Lake. After the workshop, we headed to one of the cafes for some local coffee and cake before taxi the water taxi back to our hotel.

Left to right: Cecilia, María Clara, Elena, Eufemia

Dina, Celia and I after a fascinating day of textiles

Dina from Maye Traditions leading the way home

Taking a water taxi across Lake Atitlan

Ikat natural dyeing is one of the many highlights on our Guatemala: Weaving, Embroidery and Community Tour.

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fix bug in paint tool (mirrored brush texture)

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worked around a bug in Mojave (greyed out pull down button in material browser)

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the-fitsquad · 7 years ago

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toradex · 8 years ago

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Starting with OpenCV on i.MX 6 Processors

Introduction

As the saying goes, a picture is worth a thousand words. It is indeed true to some extent: a picture can hold information about objects, environment, text, people, age and situations, among other information. It can also be extended to video, that can be interpreted as a series of pictures and thus holds motion information.

This might be a good hint as to why computer vision (CV) has been a field of study that is expanding its boundaries every day. But then we come to the question: what is computer vision? It is the ability to extract meaning from an image, or a series of images. It is not to be confused with digital imaging neither image processing, which are the production of an input image and the application of mathematical operations to images, respectively. Indeed, they are both required to make CV possible.

But what might be somehow trivial to human beings, such as reading or recognizing people, is not always true when talking about computers interpreting images. Although nowadays there are many well known applications such as face detection in digital cameras and even face recognition in some systems, or optical character recognition (OCR) for book scanners and license plate reading in traffic monitoring systems, these are fields that nearly didn't exist 15 years ago in people's daily lives. Self-driving cars going from controlled environments to the streets are a good measure of how cutting-edge this technology is, and one of the enablers of CV is the advancement of computing power in smaller packages.

Being so, this blog post is an introduction to the use of computer vision in embedded systems, by employing the OpenCV 2.4 and 3.1 versions in Computer on Modules (CoMs) equipped with NXP i.MX 6 processors. The CoMs chosen were the Colibri and Apalis families from Toradex.

OpenCV stands for Open Source Computer Vision Library, which is a set of libraries that contain several hundreds of computer vision related algorithms. It has a modular structure, divided in a core library and several others such as image processing module, video analysis module and user interface capabilities module, among others.

Considerations about OpenCV, i.MX 6 processors and the Toradex modules

OpenCV is a set of libraries that computes mathematical operations on the CPU by default. It has support for multicore processing by using a few external libraries such as OpenMP (Open Multi-processing) and TBB (Threading Building Blocks). This blog post will not go deeper into comparing the implementation aspects of the choices available, but the performance of a specific application might change with different libraries.

Regarding support for the NEON floating-point unit coprocessor, the release of OpenCV 3.0 states that approximately 40 functions have been accelerated and a new HAL (hardware abstraction layer) provides an easy way to create NEON-optimized code, which is a good way to enhance performance in many ARM embedded systems. I didn't dive deep into it, but if you like to see under the hood, having a look at the OpenCV source-code (1, 2) might be interesting.

This blog post will present how to use OpenCV 2.4 and also OpenCV 3.1 - this was decided because there might be readers with legacy applications that want to use the older version. It is a good opportunity for you to compare performance between versions and have a hint about the NEON optimizations gains.

The i.MX 6 single/dual lite SoC has graphics GPU (GC880) which supports OpenGL ES, while the i.MX 6 dual/quad SoC, has 3D graphics GPU (GC2000) which supports OpenGL ES and also OpenCL Embedded Profile, but not the Full Profile. The i.MX 6 also has 2D GPU (GC320), IPU and, for the dual/quad version, vector GPU (GC335), but this blog post will not discuss the possibility of using these hardware capabilities with OpenCV - it suffices to say that OpenCV source-code does not support them by default, therefore a considerable amount of effort would be required to take advantage of the i.MX 6 hardware specifics.

While OpenCL is a general purpose GPU programming language, its use is not the target of this blog post. OpenGL is an API for rendering 2D and 3D graphics on the GPU, and therefore is not meant for general purpose computing, although some experiments (1) have demonstrated that it is possible to use OpenGL ES for general purpose image processing, and there is even an application-note by NXP for those interested. If you would like to use GPU accelerated OpenCV out-of-the-box, Toradex has a module that supports CUDA – the Apalis TK1. See this blog post for more details.

Despite all the hardware capabilities available and possibly usable to gain performance, according to this presentation, the optimization of OpenCV source-code focusing only software and the NEON co-processor could yield a performance enhancement of 2-3x for algorithm and another 3-4x NEON optimizations.

The Images 1 and 2 present, respectively, the Colibri iMX6DL + Colibri Evaluation Board and the Apalis iMX6Q + Apalis Evaluation Board, both with supply, debug UART, ethernet, USB camera and VGA display cables plugged in.

Colibri iMX6DL Colibri Evaluation Board setup

Apalis iMX6Q Apalis Evaluation Board setup

It is important to notice that different USB camera models had a performance offset, and that the camera employed in this blog post is a generic consumer camera – the driver was listed as “Aveo Technology Corp”. There are also professional cameras in the market, USB or not, such as the solutions provided by Basler AG, that are meant for embedded solutions when going to develop a real-world solution.

Professional camera from Basler AG

In addition, Toradex has the CSI Camera Module 5MP OV5640. It is an add-on board for the Apalis computer-on-module which uses MIPI-CSI Interface. It uses the OmniVision OV5640 camera sensor with built-in auto-focus. The OV5640 image sensor is a low voltage, high-performance, 1/4-inch 5 megapixel CMOS image sensor that provides the full functionality of a single chip 5 megapixel (2592x1944) camera. The CSI Camera Module 5MP OV5640 can be connected to the MIPI-CSI connector on the Ixora carrier board V1.1 using a 24 way 0.5mm pitch FFC cable.

Toradex CSI Camera Module 5MP OV5640

At the end of this blog post, a summary of the instructions to install OpenCV and deploy applications to the target is provided.

Building Linux image with OpenCV

Images for the OpenCV 2.4 and 3.1 are built with OpenEmbedded. You may follow this article to set up your host machine. The first step required is to install the system prerequisites for OpenEmbedded. Below an example is given for Ubuntu 16.04 - for other versions of Ubuntu and Fedora, please refer to the article link above:

sudo dpkg --add-architecture i386 sudo apt-get update sudo apt-get install g++-5-multilib sudo apt-get install curl dosfstools gawk g++-multilib gcc-multilib lib32z1-dev libcrypto++9v5:i386 libcrypto++-dev:i386 liblzo2-dev:i386 libstdc++-5-dev:i386 libusb-1.0-0:i386 libusb-1.0-0-dev:i386 uuid-dev:i386 cd /usr/lib; sudo ln -s libcrypto++.so.9.0.0 libcryptopp.so.6

The repo utility must also be installed, to fetch the various git repositories required to build the images:

mkdir ~/bin export PATH=~/bin:$PATH curl http://commondatastorage.googleapis.com/git-repo-downloads/repo > ~/bin/repo chmod a+x ~/bin/repo

Let's build the images with OpenCV 2.4 and 3.1 in different directories. If you are interested in only one version, some steps might be omitted. A directory to share the content downloaded by OpenEmbedded will also be created:

cd mkdir oe-core-opencv2.4 oe-core-opencv3.1 oe-core-downloads cd oe-core-opencv2.4 repo init -u http://git.toradex.com/toradex-bsp-platform.git -b LinuxImageV2.6.1 repo sync cd ../oe-core-opencv3.1 repo init -u http://git.toradex.com/toradex-bsp-platform.git -b LinuxImageV2.7 repo sync

OpenCV 2.4

OpenCV 2.4 will be included in the Toradex base image V2.6.1. Skip this section and go to the OpenCV3.1 if you are not interested in this version. The recipe included by

default uses the version 2.4.11 and has no support for multicore processing included.

Remove the append present in the meta-fsl-arm and the append present in the meta-toradex-demos:

rm layers/meta-fsl-arm/openembedded-layer/recipes-support/opencv/opencv_2.4.bbappend rm layers/meta-toradex-demos/recipes-support/opencv/opencv_2.4.bbappend

Let's create an append to use the version 2.4.13.2 (latest version so far) and add TBB as the framework to take advantage of multiple cores. Enter the oe-core-opencv2.4 directory:

cd oe-core-opencv2.4

Let's create an append in the meta-toradex-demos layer (layers/meta-toradex-demos/recipes-support/opencv/opencv_2.4.bbappend) with the following content:

gedit layers/meta-toradex-demos/recipes-support/opencv/opencv_2.4.bbappend ------------------------------------------------------------------------------------- SRCREV = "d7504ecaed716172806d932f91b65e2ef9bc9990" SRC_URI = "git://github.com/opencv/opencv.git;branch=2.4" PV = "2.4.13.2+git${SRCPV}" PACKAGECONFIG += " tbb" PACKAGECONFIG[tbb] = "-DWITH_TBB=ON,-DWITH_TBB=OFF,tbb,"

Alternatively, OpenMP could be used instead of TBB:

Set up the environment before configuring the machine and adding support for OpenCV. Source the export script that is inside the oe-core-opencv2.4 directory:

. export

You will automatically enter the build directory. Edit the conf/local.conf file to modify and/or add the variables below:

gedit conf/local.conf ------------------------------------------------------------------------------- MACHINE ?= "apalis-imx6" # or colibri-imx6 depending on the CoM you have # Use the previously created folder for shared downloads, e.g. DL_DIR ?= "/home/user/oe-core-downloads" ACCEPT_FSL_EULA = "1" # libgomp is optional if you use TBB IMAGE_INSTALL_append = " opencv opencv-samples libgomp"

After that you can build the image, which takes a while:

bitbake –k angstrom-lxde-image

OpenCV 3.1

OpenCV 3.1 will be included in the Toradex base image V2.7. This recipe, different from the 2.4, already has TBB support included. Still, a compiler flag must be added or the compiling process will fail. Enter the oe-core-opencv3.1 directory:

cd oe-core-opencv3.1

Create a recipe append (layers/meta-openembedded/meta-oe/recipes-support/opencv/opencv_3.1.bb) with the following contents:

gedit layers/meta-toradex-demos/recipes-support/opencv/opencv_3.1.bbappend ------------------------------------------------------------------------------------- CXXFLAGS += " -Wa,-mimplicit-it=thumb"

Alternatively, OpenMP could be used instead of TBB. If you want to do it, create the bbappend with the following contents:

gedit layers/meta-toradex-demos/recipes-support/opencv/opencv_3.1.bbappend ------------------------------------------------------------------------------------- CXXFLAGS_armv7a += " -Wa,-mimplicit-it=thumb" PACKAGECONFIG_remove = "tbb" EXTRA_OECMAKE += " -DWITH_OPENMP=ON"

Set up the environment before configuring the machine and adding support for OpenCV. Source the export script that is inside the oe-core-opencv3.1 directory:

. export

You will automatically enter the build directory. Edit the conf/local.conf file to modify and/or add the variables below:

After that you can build the image, which will take a while:

bitbake –k angstrom-lxde-image

Update the module

The images for both OpenCV versions will be found in the oe-core-opencv<version>/deploy/images/<board_name> directory, under the name <board_name>_LinuxImage<image_version>_<date>.tar.bz2. Copy the compressed image to some project directory in your computer, if you want. An example is given below for Apalis iMX6 with OpenCV 2.4, built in 2017/01/26:

cd /home/user/oe-core-opencv2.4/deploy/images/apalis-imx6/ cp Apalis_iMX6_LinuxImageV2.6.1_20170126.tar.bz2 /home/root/myProjectDir cd /home/root/myProjectDir

Please follow this article's instructions to update your module.

Generating SDK

To generate an SDK, that will be used to cross-compile applications, run the following command:

bitbake –c populate_sdk angstrom-lxde-image

After the process is complete, you will find the SDK under /deploy/sdk. Run the script to install – you will be prompted to chose an installation path:

./angstrom-glibc-x86_64-armv7at2hf-vfp-neon-v2015.12-toolchain.sh Angstrom SDK installer version nodistro.0 ========================================= Enter target directory for SDK (default: /usr/local/oecore-x86_64):

In the next steps it will be assumed that you are using the following SDK directories: For OpenCV 2.4: /usr/local/oecore-opencv2_4 For OpenCV 3.1: /usr/local/oecore-opencv3_1

Preparing for cross-compilation

After the installation is complete, you can use the SDK to compile your applications. In order to generate the Makefiles, CMake was employed. If you don't have CMake, install it:

sudo apt-get install cmake

Create a file named CMakeLists.txt inside your project folder, with the content below. Please make sure that the sysroot name inside your SDK folder is the same as the one in the script (e.g. armv7at2hf-vfp-neon-angstrom-linux-gnueabi):

cd ~ mkdir my_project gedit CMakeLists.txt -------------------------------------------------------------------------------- cmake_minimum_required(VERSION 2.8) project( MyProject ) set(CMAKE_RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin") add_executable( myApp src/myApp.cpp ) if(OCVV EQUAL 2_4) message(STATUS "OpenCV version required: ${OCVV}") SET(CMAKE_PREFIX_PATH /usr/local/oecore-opencv${OCVV}/sysroots/armv7at2hf-vfp-neon-angstrom-linux-gnueabi) elseif(OCVV EQUAL 3_1) message(STATUS "OpenCV version required: ${OCVV}") SET(CMAKE_PREFIX_PATH /usr/local/oecore-opencv${OCVV}/sysroots/armv7at2hf-neon-angstrom-linux-gnueabi) else() message(FATAL_ERROR "OpenCV version needs to be passed. Make sure it matches your SDK version. Use -DOCVV=<version>, currently supported 2_4 and 3_1. E.g. -DOCVV=3_1") endif() SET(OpenCV_DIR ${CMAKE_PREFIX_PATH}/usr/lib/cmake/OpenCV) find_package( OpenCV REQUIRED ) include_directories( ${OPENCV_INCLUDE_DIRS} ) target_link_libraries( myApp ${OPENCV_LIBRARIES} )

It is also needed to have a CMake file to point where are the includes and libraries. For that we will create one CMake script inside each SDK sysroot. Let's first do it for the 2.4 version:

cd /usr/local/oecore-opencv2_4/sysroots/armv7at2hf-vfp-neon-angstrom-linux-gnueabi/usr/lib/cmake mkdir OpenCV gedit OpenCV/OpenCVConfig.cmake ----------------------------------------------------------------------------------- set(OPENCV_FOUND TRUE) get_filename_component(_opencv_rootdir ${CMAKE_CURRENT_LIST_DIR}/../../../ ABSOLUTE) set(OPENCV_VERSION_MAJOR 2) set(OPENCV_VERSION_MINOR 4) set(OPENCV_VERSION 2.4) set(OPENCV_VERSION_STRING "2.4") set(OPENCV_INCLUDE_DIR ${_opencv_rootdir}/include) set(OPENCV_LIBRARY_DIR ${_opencv_rootdir}/lib) set(OPENCV_LIBRARY -L${OPENCV_LIBRARY_DIR} -lopencv_calib3d -lopencv_contrib -lopencv_core -lopencv_features2d -lopencv_flann -lopencv_gpu -lopencv_highgui -lopencv_imgproc -lopencv_legacy -lopencv_ml -lopencv_nonfree -lopencv_objdetect -lopencv_ocl -lopencv_photo -lopencv_stitching -lopencv_superres -lopencv_video -lopencv_videostab) if(OPENCV_FOUND) set( OPENCV_LIBRARIES ${OPENCV_LIBRARY} ) set( OPENCV_INCLUDE_DIRS ${OPENCV_INCLUDE_DIR} ) endif() mark_as_advanced(OPENCV_INCLUDE_DIRS OPENCV_LIBRARIES)

The same must be done for the 3.1 version - notice that the libraries change from OpenCV 2 to OpenCV 3:

cd /usr/local/oecore-opencv3_1/sysroots/armv7at2hf-vfp-neon-angstrom-linux-gnueabi/usr/lib/cmake mkdir OpenCV gedit OpenCV/OpenCVConfig.cmake ----------------------------------------------------------------------------------- set(OPENCV_FOUND TRUE) get_filename_component(_opencv_rootdir ${CMAKE_CURRENT_LIST_DIR}/../../../ ABSOLUTE) set(OPENCV_VERSION_MAJOR 3) set(OPENCV_VERSION_MINOR 1) set(OPENCV_VERSION 3.1) set(OPENCV_VERSION_STRING "3.1") set(OPENCV_INCLUDE_DIR ${_opencv_rootdir}/include) set(OPENCV_LIBRARY_DIR ${_opencv_rootdir}/lib) set(OPENCV_LIBRARY -L${OPENCV_LIBRARY_DIR} -lopencv_aruco -lopencv_bgsegm -lopencv_bioinspired -lopencv_calib3d -lopencv_ccalib -lopencv_core -lopencv_datasets -lopencv_dnn -lopencv_dpm -lopencv_face -lopencv_features2d -lopencv_flann -lopencv_fuzzy -lopencv_highgui -lopencv_imgcodecs -lopencv_imgproc -lopencv_line_descriptor -lopencv_ml -lopencv_objdetect -lopencv_optflow -lopencv_photo -lopencv_plot -lopencv_reg -lopencv_rgbd -lopencv_saliency -lopencv_shape -lopencv_stereo -lopencv_stitching -lopencv_structured_light -lopencv_superres -lopencv_surface_matching -lopencv_text -lopencv_tracking -lopencv_videoio -lopencv_video -lopencv_videostab -lopencv_xfeatures2d -lopencv_ximgproc -lopencv_xobjdetect -lopencv_xphoto) if(OPENCV_FOUND) set( OPENCV_LIBRARIES ${OPENCV_LIBRARY} ) set( OPENCV_INCLUDE_DIRS ${OPENCV_INCLUDE_DIR} ) endif() mark_as_advanced(OPENCV_INCLUDE_DIRS OPENCV_LIBRARIES)

After that, return to the project folder. You must export the SDK variables and run the CMake script:

# For OpenCV 2.4 source /usr/local/oecore-opencv2_4/environment-setup-armv7at2hf-vfp-neon-angstrom-linux-gnueabi cmake -DOCVV=2_4 . # For OpenCV 3.1 source /usr/local/oecore-opencv3_1/environment-setup-armv7at2hf-neon-angstrom-linux-gnueabi cmake –DOCVV=3_1 .

Cross-compiling and deploying

To test the cross-compilation environment, let's build a hello-world application that reads an image from a file and displays the image on a screen. This code is essentially the same as the one from this OpenCV tutorial:

mkdir src gedit src/myApp.cpp --------------------------------------------------------------------------------- #include #include <opencv2/opencv.hpp> using namespace std; using namespace cv; int main(int argc, char** argv ){ cout << "OpenCV version: " << CV_MAJOR_VERSION << '.' << CV_MINOR_VERSION << "\n"; if ( argc != 2 ){ cout << "usage: ./myApp \n"; return -1; } Mat image; image = imread( argv[1], 1 ); if ( !image.data ){ cout << "No image data \n"; return -1; } bitwise_not(image, image); namedWindow("Display Image", WINDOW_AUTOSIZE ); imshow("Display Image", image); waitKey(0); return 0; }

To compile and deploy, follow the instructions below. The board must have access to the LAN – you may plug an ethernet cable or use a WiFi-USB adapter, for instance. To find out the ip, use the ifconfig command.

make scp bin/myApp root@<board-IP>/home/root # Also copy some image to test! scp <path-to-image>/myimage.jpg root@<board-IP>:/home/root

In the embedded system, run the application:

root@colibri-imx6:~# ./myApp

You must see the image on the screen, as in Image 3:

Hello World application

Reading from camera

In this section, a code that reads from the camera and processes the input using the Canny edge detection algorithm will be tested. It is just one out of many algorithms already implemented in OpenCV. By the way, OpenCV has a comprehensive documentation, with tutorials, examples and library references.

In the Linux OS, when a camera device is attached, it can be accessed from the filesystem. The device is mounted in the /dev directory. Let's check the directory contents of Apalis iMX6 before plugging the USB camera:

root@apalis-imx6:~# ls /dev/video* /dev/video0 /dev/video1 /dev/video16 /dev/video17 /dev/video18 /dev/video19 /dev/video2 /dev/video20

And after plugging in:

root@apalis-imx6:~# ls /dev/video* /dev/video0 /dev/video1 /dev/video16 /dev/video17 /dev/video18 /dev/video19 /dev/video2 /dev/video20 /dev/video3

Notice that it is listed as /dev/video3. It can be confirmed using the video4linux2 command-line utility (run v4l2-ctl –help for details):

root@apalis-imx6:~# v4l2-ctl --list-devices [ 3846.876041] ERROR: v4l2 capture: slave not found! V4L2_CID_HUE [ 3846.881940] ERROR: v4l2 capture: slave not found! V4L2_CID_HUE [ 3846.887923] ERROR: v4l2 capture: slave not found! V4L2_CID_HUE DISP4 BG ():[ 3846.897425] ERROR: v4l2 capture: slave not found! V4L2_CID_HUE /dev/video16 /dev/video17 /dev/video18 /dev/video19 /dev/video20 UVC Camera (046d:081b) (usb-ci_hdrc.1-1.1.3): /dev/video3 Failed to open /dev/video0: Resource temporarily unavailable

It is also possible to get the input device parameters. Notice that the webcam used in all the tests has a resolution of 640x480 pixels.

root@apalis-imx6:~# v4l2-ctl -V --device=/dev/video3 Format Video Capture: Width/Height : 640/480 Pixel Format : 'YUYV' Field : None Bytes per Line: 1280 Size Image : 614400 Colorspace : SRGB

In addition, since all of the video interfaces are abstracted by the Linux kernel, if you were using the CSI Camera Module 5MP OV5640 from Toradex, it would be listed as another video interface. On Apalis iMX6 the kernel drivers are loaded by default. For more information, please check this knowledge-base article.

Going to the code, the OpeCV object that does the camera handling, VideoCapture, accepts the camera index (which is 3 for our /dev/video3 example) or -1 to autodetect the camera device.

An infinite loop processes the video frame by frame. Our example applies the filters conversion to gray scale -> Gaussian blur -> Canny and then sends the processed image to the video output. The code is presented below:

#include #include #include <opencv2/core/core.hpp> #include <opencv2/imgproc/imgproc.hpp> #include <opencv2/highgui/highgui.hpp> using namespace std; using namespace cv; int main(int argc, char** argv ){ cout << "OpenCV version: " << CV_MAJOR_VERSION << '.' << CV_MINOR_VERSION << '\n'; VideoCapture cap(-1); // searches for video device if(!cap.isOpened()){ cout << "Video device could not be opened\n"; return -1; } Mat edges; namedWindow("edges",1); double t_ini, fps; for(; ; ){ t_ini = (double)getTickCount(); // Image processing Mat frame; cap >> frame; // get a new frame from camera cvtColor(frame, edges, COLOR_BGR2GRAY); GaussianBlur(edges, edges, Size(7,7), 1.5, 1.5); Canny(edges, edges, 0, 30, 3); // Display image and calculate current FPS imshow("edges", edges); if(waitKey(30) >= 0) break; fps = getTickFrequency()/((double)getTickCount() - t_ini); cout << "Current fps: " << fps << '\r' << flush; } return 0; }

Image 4 presents the result. Notice that neighter the blur nor the Canny algorithms parameters were tuned.

Capture from USB camera being processed with Canny edge detection

In order to compare between the Colibri iMX6S and iMX6DL and be assured that multicore processing is being done, the average FPS for 1000 samples was measured, and is presented in table 1. It was also done for the Apalis iMX6Q with the Apalis Heatsink. All of the tests had frequency scaling disabled.

Table 1 – Canny implementation comparison between modules and OpenCV configurations (640x480)

As a comparison, the Canny algorithm was replaced in the code with the Sobel derivatives, based on this example. The results are presented in table 2:

Table 2 – Sobel implementation comparison between modules and OpenCV configurations (640x480)

It is interesting to notice that using the TBB framework may be slightly faster than OpenMP in most of the situations, but not always. It is interesting to notice that there is a small performance difference even for the single-core results.

Also, the enhancements made from OpenCV 2.4 to OpenCV 3.1 have a significant impact in the applications performance – which might be explained by the NEON optimizations made so far, and also an incentive to try to optimize the algorithms that your application requires. Based on this preliminary results, it is interesting to test a specific application with several optimization combinations and using only the latest OpenCV version before deploying.

Testing an OpenCV face-tracking sample

There is also a face-tracking sample in the OpenCV source-code that was tested, since it is heavier than the previously made tests and might provide a better performance awareness regarding Colibri x Apalis when choosing the more appropriate hardware for your project.

The first step was to copy the application source-code from GitHub and replace the contents of myApp.cpp, or create another file and modify the CMake script if you prefer. You will also need the Haar cascades provided for face and eye recognition. You might as well clone the whole OpenCV git directory and later test other samples.

A few changes must be made in the source-code so it also works for OpenCV2.4: include the stdio.h library, modify the OpenCV included libraries (take a look in the new headers layout section here) and make some changes to the CommandLineParser, since the versions from OpenCV 2 and 3 are not compatible. Image 5 presents the application running:

Face and eye tracking application

The code already prints the time it takes to run a face detection. Table 3, presented below, holds the results for 100 samples:

Table 3 – Face detection comparison between modules and OpenCV configurations (640x480)

Again the difference between OpenCV versions is not negligible - for the Apalis iMX6Q (quad-core) the performance gain is 3x, and using OpenCV 3.1 with the dual-core Colibri iMX6DL delivers a better performance than OpenCV 2.4 with the quad-core Apalis iMX6Q.

The single-core IT version, thus with reduced clock compared to the others, has results far behind as expected. The reduced clock may explain why the performance improvement from single to dual core is higher than dual to quad core.

Conclusion

Since OpenCV is nowadays (probably) the most popular set of libraries for computer vision, and with the enhancement of performance in embedded systems, knowing how to start with OpenCV for embedded applications provides a powerful tool to solve problems of nowadays and the near future.

This blog post has chosen a widely known family of microprocessors as an example and a starting point, be for those only studying computer vision or those already focusing on developing real-world applications. It also has demonstrated that things are only starting – see for instance the performance improvements from OpenCV 2 to 3 for ARM processors – which also points towards the need to understand the system architecture and focus on optimizing the application as much as possible – even under the hood. I hope this blog post was useful and see you next time!

Summary

1) Building image with OpenCV To build an image with OpenCV 3.1, first follow this article steps to setup OpenEmbedded for the Toradex image V2.7. Edit the OpenCV recipe from meta-openembedded, adding the following line:

CXXFLAGS += " -Wa,-mimplicit-it=thumb"

In the local.conf file uncomment your machine, accept the Freescale license and add OpenCV:

MACHINE ?= "apalis-imx6" # or colibri-imx6 depending on the CoM you have ACCEPT_FSL_EULA = "1" IMAGE_INSTALL_append = " opencv"

2) Generating SDK Then you are able to run the build, and also generate the SDK:

bitbake –k angstrom-lxde-image bitbake –c populate_sdk angstrom-lxde-image

To deploy the image to the embedded system, you may follow this article's steps.

3) Preparing for cross-compilation After you install the SDK, there will be a sysroot for the target (ARM) inside the SDK directory. Create an OpenCV directory inside <path_to_ARM_sysroot>/usr/lib/cmake and, inside this new directory create a file named OpenCVConfig.cmake with the contents presented below:

cd /usr/lib/cmake mkdir OpenCV vim OpenCVConfig.cmake --------------------------------------------------------------------------- set(OPENCV_FOUND TRUE) get_filename_component(_opencv_rootdir ${CMAKE_CURRENT_LIST_DIR}/../../../ ABSOLUTE) set(OPENCV_VERSION_MAJOR 3) set(OPENCV_VERSION_MINOR 1) set(OPENCV_VERSION 3.1) set(OPENCV_VERSION_STRING "3.1") set(OPENCV_INCLUDE_DIR ${_opencv_rootdir}/include) set(OPENCV_LIBRARY_DIR ${_opencv_rootdir}/lib) set(OPENCV_LIBRARY -L${OPENCV_LIBRARY_DIR} -lopencv_aruco -lopencv_bgsegm -lopencv_bioinspired -lopencv_calib3d -lopencv_ccalib -lopencv_core -lopencv_datasets -lopencv_dnn -lopencv_dpm -lopencv_face -lopencv_features2d -lopencv_flann -lopencv_fuzzy -lopencv_highgui -lopencv_imgcodecs -lopencv_imgproc -lopencv_line_descriptor -lopencv_ml -lopencv_objdetect -lopencv_optflow -lopencv_photo -lopencv_plot -lopencv_reg -lopencv_rgbd -lopencv_saliency -lopencv_shape -lopencv_stereo -lopencv_stitching -lopencv_structured_light -lopencv_superres -lopencv_surface_matching -lopencv_text -lopencv_tracking -lopencv_videoio -lopencv_video -lopencv_videostab -lopencv_xfeatures2d -lopencv_ximgproc -lopencv_xobjdetect -lopencv_xphoto) if(OPENCV_FOUND) set( OPENCV_LIBRARIES ${OPENCV_LIBRARY} ) set( OPENCV_INCLUDE_DIRS ${OPENCV_INCLUDE_DIR} ) endif() mark_as_advanced(OPENCV_INCLUDE_DIRS OPENCV_LIBRARIES)

Inside your project folder, create a CMake script to generate the Makefiles for cross-compilation, with the following contents:

cd vim CMakeLists.txt -------------------------------------------------------------------------------- cmake_minimum_required(VERSION 2.8) project( MyProject ) set(CMAKE_RUNTIME_OUTPUT_DIRECTORY "${CMAKE_BINARY_DIR}/bin") add_executable( myApp src/myApp.cpp ) SET(CMAKE_PREFIX_PATH /usr/local/oecore-x86_64/sysroots/armv7at2hf-neon-angstrom-linux-gnueabi) SET(OpenCV_DIR ${CMAKE_PREFIX_PATH}/usr/lib/cmake/OpenCV) find_package( OpenCV REQUIRED ) include_directories( ${OPENCV_INCLUDE_DIRS} ) target_link_libraries( myApp ${OPENCV_LIBRARIES} )

Export the SDK environment variables and after that run the CMake script. In order to do so, you may run:

source /usr/local/oecore-x86_64/environment-setup-armv7at2hf-neon-angstrom-linux-gnueabi cmake .

4) Cross-compiling and deploying Now you may create a src directory and a file named myApp.cpp inside it, where you can write a hello world application, such as this one:

mkdir src vim src/myApp.cpp -------------------------------------------------------------------------------- #include #include <opencv2/opencv.hpp> using namespace std; using namespace cv; int main(int argc, char** argv ){ Mat image; image = imread( "/home/root/myimage.jpg", 1 ); if ( !image.data ){ cout << "No image data \n"; return -1; } namedWindow("Display Image", WINDOW_AUTOSIZE ); imshow("Display Image", image); waitKey(0); return 0; }

Cross-compile and deploy to the target:

make scp bin/myApp root@<board-ip>:/home/root # Also copy some image to test! scp <path-to-image>/myimage.jpg root@<board-ip>:/home/root

In the embedded system:

root@colibri-imx6:~# ./myApp

#OpenCV #Computer on Modules #Computer Vision #NXP iMX6 #Embedded Systems #Toradex

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outsourcebigdata · 1 year ago

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How to Find the Best Web Crawlers at Zero Cost ?

Starting a digital business can be daunting, especially if you're unfamiliar with SEO. Since Google dominates 86.86% of the search engine market, improving your Google ranking is crucial. Manual SEO analysis is time-consuming and error-prone, so using a best web crawler is essential. Web crawlers automatically detect broken links, missing titles, duplicate content, and other issues to improve your site's structure and search engine ranking.

What is a Web Crawler?

A web crawler, also known as a spider or bot, automates data extraction and SEO auditing by exploring web pages, videos, PDFs, and images through links. This process saves time, money, and ensures access to up-to-date data.

Key Features to Look for in a Web Crawler

User-Friendly Interface: Easy to navigate and intuitive design.

Robust Features: Includes auto-execution, multi-threaded scraping, adjustable speeds, and scalability.

Auto-Detection of Robots.txt and Sitemaps: Enhances efficiency and simplifies crawling.

Detection of Broken Pages and Links: Quickly identifies and improves navigation.

Handling Redirect Issues: Manages outdated or expired URLs seamlessly.

Integration with Google Analytics: Allows comprehensive data analysis.

Multiple File Format Delivery: Exports reports in formats like CSV and Excel.

Support for Multiple Devices: Compatible with tablets, mobile devices, and desktops.

Recommended Free Web Crawlers

ApiScrapy: Advanced pre-built crawlers for automated data collection.

Cyotek WebCopy: Customizable tool for offline reading, lacking JavaScript parsing.

Getleft: User-friendly, supports multiple languages, ideal for full website downloads.

HTTrack: Open-source, supports unlimited crawling and proxy use.

Scraper Wiki: Offers PDF scraping and a Python/R environment for data analysis.

Octoparse: Cloud-based, designed for Windows and Mac, advanced data extraction.

Anysite Scraper: Customizable for various sites, supports multiple formats.

Outwit Hub Light: Advanced scraping with support for various export formats.

Content Grabber: Enterprise-level, extracts data from almost any site.

ScrapeStorm: AI-driven, supports various export formats, user-friendly.

Conclusion

If managing a web crawler isn't feasible, consider OutsourceBigdata for professional web crawling services. OutsourceBigdata offers advanced solutions tailored to your business needs, ensuring efficient data extraction and indexing, allowing you to focus on core activities while benefiting from accurate data.

#best web scraping tool #data extraction services #best web scraping company

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kelsusit · 8 years ago

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Improving Visual Comfort At A Computer Workstation

Up A Pc Workstation

The above write-up is all about shared workplace space for rental and its positive aspects for new enterprise workplace, new startups to start off a new office in their desired place. Try a corner desk with a fold-down worktop, or if that’s also small and you need to have a lot more storage verify out the workplace corner laptop desks with built-in shelves. The WorkFit A (US$649.00) “contains arm, work surface, base, keyboard tray support, keyboard tray, desk clamp, grommet mount, assembly fasteners, cable management hardware and adjustment tools.” Its maximum capacity is 25 lbs (11.four kg), which effortlessly accommodates the 20 to 22 lb weight of the iMac from late 2009 to present, plus keyboard and mouse. With the risk of damage to supply chain computer systems drastically lowered, Industrial Pc Workstations deliver an practically immediate return on investment by cutting the cost of IT gear repair or replacement, even though lowering the threat of provide chain disruption.

The Software Licensing Service reported that necessary license could not be discovered. It is worth noting that this laptop is one particular of the slimmest and lightest of the workstations in this list. By the late 1970s, Baudrillard interprets the media as important simulation machines which reproduce images, indicators, and codes which constitute an autonomous realm of (hyper)reality and which come to play a essential part in every day life and the obliteration of the social. Despite the fact that greatest known for our workstations, Staverton has a a lot wider range of furniture options spanning workplace mobility, meetings, storage, workwall and integrated technologies also. If you want your workplace to impress, the surest way is to hire a specialist carpenter or match-out specialist to design distinctive workstations that serve your business requirements precisely.

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Personal computer systems that assistance the design and style and improvement procedure for industrial merchandise. These “uncubicles” have been conceived to enable, support and inspire creativity within the Open Strategy Office, the quintessential collaborative workspace of this young new century. We use Genuine Intel CPU, ASUS Motherboard, Samsung SSDs and Seagate or Western Digital difficult drives. Meanwhile, computer monitors, printers, keyboards and other accessories are protected from rigorous industrial environments. It does not give as significantly shelf storage but it nevertheless has a lot of double hang as effectively as lengthy hanging space and shelves for footwear and sweaters. Freelancers, amateur designers and CAD hobbyist will possibly love the freedom employing a laptop provides when designing Employing a laptop means you can design and style models on-the-go with out the limitations of being glued to a desktop pc.

This operation could not be completed since the DNS server listed as the current important master for this zone is down or misconfigured. – The outbound network restrictions have to permit connectivity only to authorized cloud services utilizing the guidance in Phase 2. No open web access ought to be permitted from PAWs. Just acquiring the Z8 box without having considerably inside will price you $2,439, but if you want, say, a pair of the newest Xeon Platinum 8180M chips with 28 cores every single and two of NVIDIA’s 24GB P6000 Quadro graphics adapters, these products alone would run you a cool $35,000. Microsoft’s new Workstation mode promises greater functionality in particular workloads, which could be of interest to customers who frequently use advanced workstation capabilities.

Mainframes are massive and strong systems to manage the processing of thousands of customers at any one time. Universal Apps are developed to provide a seamless encounter across devices, which is aided by the truth their information is stored in the cloud, so it really is far more than just a case of a familiar look and feel for the user on their telephone as on their laptop. If your home or apartment is short on space, appear for modest desks like a roll best or secretary that conserves space but still functions effectively. Z620 systems configured with E5-1600 series processors may possibly not add a 2nd processor. Keep in mind that we are building our workstation around NVIDIA’S Quadro M5000 graphics card, so our hardware selections will be made with this card in mind.

The problem was soon after installing Sophos on a personal computer I was unable to Handle computers on the network, this turned out to be an situation with the reality the server IP address was changed soon after the install of sophos which meant the workstations have been listening to the old address rather than the new one. Several new attributes offer to minimize data bottlenecks and speed up the efficiency of modern day challenging drives. Figure 3. The tool that shows supported graphics cards. I’m truly attempting to string the life of one particular of our editing bays out a tiny longer, so I was looking for RAM when I came across an ad for a 2 unit rackmount server with dual quad core Xenon processors and 24GB of RAM. Usually instances while operating men and women might uncover themselves concentrating far more on the aches and pains they are experiencing from sitting in a poorly made workplace chair than their actual operate they need to have to be focusing on. This not only leads to unproductive personnel but also leads to unhappy staff which eventually leads to a greater turn more than price and a low employee retention price.

In addition, the auditor prepares a day-to-day summary of cash, verify and credit card activities that occurred at the front desk. In conclusion workstation mobile laptops are the laptops that come with the best and really high-efficiency processor, graphics, memory and much a lot more and they use for a variety of works like animation, 3d modeling, game improvement, architecture works with AutoCAD, Revit and significantly more he said. (Not necessarily an concern if you plan on possessing it tucked away, though you will definitely notice it if you engage in some of that aforementioned schlepping.) It also looks much less black than it does on Apple’s internet site – more like the “Space Gray” that it actually is. As it occurs, that case is effortless to unlock and slip off, on the uncommon occasion that you want to replace the RAM, storage or one of the GPUs.

Note: If your application does not support GPU rendering, use the alternate components under these parts to get far better CPU rendering functionality. When trains get to Aquia Landing, they will spot the cars according the “When Empty return to” directions on the bill. A File Server Resource Manager XML configuration file or import-export file is corrupted. Desktop Computer users can surf the Net, play media files, email, play games, chat and video conference. You can place the installation files on a USB or Regional Disk and start off the and set up windows 7. (I suggest use USB) at least 8GB or 4GB. I want to use Registered-ECC memory because ECC(Error-correcting code) memory is primarily employed for servers and other mission-essential applications that require extra safety and stability and this ASUS Z10PE-D8 WS motherboard do help it. So, I decide on the RAM from the ASUS Z10PE-D8 WS motherboard QVL (certified vendor list).

A standard WhisperStation configuration features ultra-quiet fans and high efficiency energy provide, internal soundproofing, AMD Opteron or Intel Xeon processors, NVIDIA® Quadro® Professional graphics, and NVIDIA Tesla® GPUs for computation. Once again, 4 added CPU cores and the quicker Sandy Bridge architecture give the Z820 a significant functionality lead over the Z800, and a just staggering one particular more than the single-socket systems. You could use either cork-board or magnetic sheets as multi-goal workplace storage on your workstations. The excellent news though, Windows 10 Mobile build 15250 has now been produced available for users as component of the Windows Insider plan, and it now brings 3 new characteristics. It is a fine line to stroll, and I believe it really is a testament to HP’s technical provenance that they are able to succeed in the workstation business today.

When a product is ultimately completed and goes to production (often a workstation will take years from idea to completed product), the designers and engineers who participated have a celebration and everyone indicators the initial a single out of the factory—much like Detroit does with automobiles. In early 1990’s, Microsoft wanted to have a share of the profitable corporate and company market place but its operating system at that time MS-DOS and Windows three.x did have attributes to take on severe operating systems such as UNIX which had a huge chuck of the market place at that time. There’s really a lot of detail here, even generating drivers offered that have come directly from the graphics card manufacturer and not but tested by HP’s Workstation Graphics Lab.

The resource cannot move to an additional node simply because a cluster shared volume vetoed the operation. There are so many single threaded processes in Houdini (and most applications) that 30+ threads would be entirely wasted, and the reduce (not more than-clockable) CPU speeds will imply a quite measly functionality unless you’re in a position where it tends to make sense to buy into the vastly more pricey Xeons (feel $2k+ per CPU). Librarian and editor computer software is utilized for managing massive amounts of voice data for MIDI-controlled instruments. Microsoft is clearly targeting this new edition of Windows 10 to power users who are processing mass amounts of information every single day. But, the time of the isolated, burnt-out cubicle employee is drawing to a shut, and to compete with the happy, energized employees identified in trendy workplace spaces, ancient organizations are going to possess to come about sooner or later.

Filed under: General Tagged: computer work stations, hp z workstation raid 10, office workstation design photos from KelsusIT.com – Refurbished laptops, desktop computers , servers http://bit.ly/2Bvc9Ee via IFTTT

#KelsusIT.com – Refurbished laptops #desktop computers #servers

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file-formats-programming · 8 years ago

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Export Images in Multi-Threaded Environment & Converting EMF to WMF Format in .NET Apps

What’s new in this release?

Aspose team is pleased to announce the new release of Aspose.Imaging for .NET 16.12.0. The major development in this release is support for exporting images in multi-threaded environment. This release supports converting EMF metafile to WMF format. Support for DNG format has also been incorporated in this release. It now supports exporting images in multi-threaded environment. Aspose.Imaging for .Net ensure the optimized performance of operations during execution of code in multi-threaded environment. All imaging option classes (e.g. BmpOptions, TiffOptions, JpegOptions, etc.) in the Aspose.Imaging for .Net now implement IDisposable interface. Therefore it is a must that developer properly dispose off the imaging options class object in case Source property is set. Aspose.Imaging now supports SyncRoot property while working in multi-threaded environment. Developer can use this property to synchronize access to the source stream. Developers can convert EMF to WMF format using this release. Moreover, it also supports the DNG (Digital Negative) image format (.dng). It is a publicly available archival format for the raw files generated by digital cameras. DNG helps ensure that photographers will be able to access their files in the future. Aspose.Imaging for .Net provides the DngImage class to load DNG files and same can be used to convert the DNG to raster formats. It also enhanced reading PSD layers, processing of JPEG format images, Processing of Dicom format images, functionality to convert WMF to PNG format, rendering images in PSD file, saving TIFF frames, Compatibility of image saved using Aspose.Imaging on MS Windows 8 and reading JPEG pixels has been greatly improved. The main new and improved features added in this release are listed below

Convert EMF to WMF

ThreadSafe API support stage 1

DNG format support

Thread safe API for TIFF images

Could not read layers in PSD file.

JPEG format performance improvents

Remove Imaging Drawing engine

Iamprovements of performance and memory usage for Dicom

Converting WMF to PNG format is not showing correct output [.Net]

Exception when opening image in separate thread

Aspose.Imaging 4.0.0: Image.Load method is not thread-safe

Improve performance of jpeg file format

Aspose.Imaging is not showing correct resolution of PSD image

License as Embedded resource is not working

Incorrect saving result while using Image.Save(string path, ImageOptionsBase options, Rectangle boundsRectangle).

Unify Metered API usage. Enable COMPACT configuration for Dynabic.Metering module.

Can't do subsequent resizing of rotated WEBP image

Converting WMF to PNG format destroying vertical text on Y-axis

Exception in PNG encoder

Jpeg pixels read by Aspose.Imaging differs from pixels read by System.Drawing

Saved jpeg is displayed incorrectly on Windows 8

Random ImageSaveException: Cannot decode strip 0. Details:, at TiffFrame.Save

Newly added documentation pages and articles

Some new tips and articles have now been added into Aspose.Imaging for .NET documentation that may guide users briefly how to use Aspose.Imaging for performing different tasks like the followings

Export Images in Multi Threaded Environment

Converting EMF to WMF Format

Overview:Aspose.Imaging for .NET

Aspose.Imaging for .NET is an image processing & manipulation component that allows developers to create, edit, draw or convert images in their .NET application. It allows developers to convert image files to PSD, BMP, JPEG, PNG, TIFF and GIF formats. Moreover a set of pens, brushes and fonts can be used to draw images or add new elements & text to existing images. Aspose.Imaging for .NET works well with both web & windows applications. Moreover, it adds the support for Silverlight platform.

More about Aspose.Imaging for .NET

Homepage of Aspose.Imaging for .NET

Download Aspose.Imaging for .NET

#Export Images in Multi-Threaded Environment #Convert EMF to WMF #DNG Image Support #reading PSD layers #Processing JPEG images #Processing Dicom images #.NET Imaging API

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rlxtechoff · 3 years ago

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#IFTTT #Blogger

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mobileexpressnow · 8 years ago

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KOTLIN, Python, and React Native among the Top 10 Programming Languages to Look Out For in 2018

In our Mobile app development industry, if there is anything that grows at par with the continuous app entries in the stores and the frequent updates, it is the increasing number of programming languages to support the mushrooming.

Based on the usability and ranking factors, I have listed down 10 Programming Languages that will define the next year.

Let’s cut to the chase:

Here is the list of Top 10 Programming Languages that will dominate the app development market in the year 2018.

Swift 4.0

Java 8

KOTLIN

React Native

Python

Node.Js

Haskell

MATLAB

JavaScript

1. Swift 4.0

Swift 4 is based on the strong points of Swift 3, providing better stability and robustness, offering source code compatibility with the Swift 3 language. It has brought in enhancements to the library, and have additional features like serialization and archival. Taking iPhone app development companies to the next level.

The new version has been introduced with new workflow features and complete API for the Swift Manager Package

Features –

It is now possible to develop a number of packages before you tag your official release. Also, it easier now to work on branch of packages at the same time.

The package products are now formalized, which makes it possible to have a closer look at what the libraries that are published to the clients by the package.

To negate the effect of hostile manifests, Swift package now appears in sandbox that prevent file system modification and network access.

Swift, in comparison to Objective-C is gaining popularity with each passing day (as you can see in the image below), and is expected to completely surpass Objective-C iOS app development language soon.

2. Java 8

Java 8 is an upgrade to Java’s programming model and is a coordinated advancement of the Java language, JVM, and libraries. The language, which is used for Android app development includes features promoting ease of use, productivity, security, improved performance, and improved polyglot programming.

Features –

Virtual Extension Methods and Lambda Expression

One of the most noteworthy features of the Java SE 8 language is its implementation of the Lambda expressions and the various related supporting features for both the platform and Java programming language.

Time and Date API

The new API allows developers to manage time and date in a much cleaner, easier to understand, and natural way.

Nashhorn JavaScript Engine

A fresh high performance, lightweight implementation of the JavaScript engine has been integrated to the JDK and has been made available to the Java applications through existing APIs.

Improved Security

This has replaced the present hand-maintained document of the caller sensitive methods with the mechanism, which accurately identifies the methods and allow the callers to be discoverable reliably.

3. Kotlin

The now official Google programming language, Kotlin is used for developing multi-platform applications. With the help of the language, one can create apps for JVM, Android, Native, and Browser. Since the announcement of it becoming the official language, Kotlin has been adopted by a number of companies for their apps. Since it’s very new in the industry, we recently wrote an article to help make it easy for the developers to make the switch from Java to Kotlin.

Read – Kotlin for Android App Development – The Whys and Hows and Bonus Tips

Features –

Java Interoperability

Kotlin is 100% interoperable with Java, making it easy for the Java developers to learn the language. The platform gives the developers an option to paste their code and it converts the Java code into Kotlin’s.

Zero Runtime Overhead

The language has concentrated extensions to the Java library. Most of its functions are in-line which simply become inline code.

Null Safety

Kotlin eliminates the side-effects of code’s null reference. The language does not compile the codes that returns or assigns a null.

Extension Functions

Developers can add methods in classes without bringing any changes to their source code. One can add the methods on the per user basis in the classes.

4. React Native

React Native is the framework, which uses React to define the user interface for the native devices. With the help of React Native one can build applications, which runs on both iOS and Android devices using JavaScript.

Features –

Code Reuse

The language gives you the freedom to use the same code for both iOS and Android.

Live Reload

It allows you to see the most recent change that you have made to the code, immediately.

Strong Performance

The language makes use of the Graphics Processing Unit, which makes it well tuned for mobile apps in terms of the speed advantage it offers.

Modular Architecture

Its interface helps developers in looking into someone else’s project and building upon it. It gives the benefit of flexibility as it takes less time for the developers to understand the programming logic and edit it.

5. Python

It is a general purpose language that has a variety of uses ranging from mathematical computing, such as – NumPy, SymPy, and Orange; Desktop Graphical UI – Panda3D, Pygame and in Web Development – Bottle and Django.

Python is known for its clean syntax and short length of code, and is the the most wanted programming language.

Features –

Easy to Learn

The language has a simple and elegant syntax which is much easier to write and read as compared to the other programming languages like C#, Java, and C++. For a newbie it is every easy to start with Python solely because of its easy syntax.

Open Source

The developers can freely use the language, even for their commercial uses. Other than using and distributing the software that are written in it, you can also make changes in the source code.

Portable

Python can be moved from one platform to another and run in them without any changes.

It can run seamlessly on platforms including Mac OS X, Windows, and Linux.

Standard Libraries

Python has standard libraries which save developers’ time in writing all the code themselves. Suppose you want to connect MySQL database on the web server, now instead of writing the whole code by yourself, you can make use of the MySQLdb library.

6. R

It is an open source program which is used to perform statistical operations. R is a command line driven program, meaning that developers enter command at the prompt and every command is implemented one at a time.

Features –

R supports object oriented programming with the generic functions and procedural programming with functions.

It can print the analysis reports in form of graph in both hardcopy and on-screen.

Its programming features consist of exporting data, database input, viewing data, missing data, variable labels, etc.

Packages form an element of R programming language. Thus, they are helpful in collecting the sets of R functions in a particular unit.

7. Node.Js

Node.js is the cross-platform, open-source JavaScript run-time environment for implementing JavaScript code on the server side.

It makes use of an event-focused, non-blocking I/O model, which makes it efficient and lightweight, ideal for data-concentrated real-time apps that can run across series of distributed devices.

Features –

Event Driven

All APIs in the Node.js library are event driven, meaning the Node.js server doesn’t have to wait for the API to return data. Server moves to next API after calling it and the notification mechanism of the Node.js events help servers in getting a response from the last API call.

Fast

Built on Google Chrome’s V8 JavaScript engine, the language’s library code execution’s speed is very fast.

Scalable

Node.js make use of one thread program, which can offer service to a large number of requests than its traditional servers such as Apache HTTP Server.

Zero Buffering

The Node.js application don’t buffer any data. They output all the data in portions.

8. Haskell

Haskell is a functional programming language. It is a first commercial language to enter the functional programming domain. It is a mix of a number of generalizable functions which define what a program is supposed to do., allowing the lower layers handle the mundane details such as iteration.

As compared to other similar programming languages, Haskell offers support for –

Lazy Evaluation

Monadic side-effects

Syntax based on the layout

Type classes

Pure functions by default

On the top of it, Huskell is one of the top 15 loved programming languages according to Stack Overflow Developer Survey.

9. MATLAB

The proprietary programming language allows plotting of data and functions, matrix manipulations, development of user interfaces, implementation of algorithms, and interfacing with the programs written in the other languages that includes C++, C, C#, Fortran, Java, and Python.

It is one of the most superior language in the programs used for scientific and mathematical purposes. According to statistics Google Trends, this language will continue to remain in the market.

Features –

Offers interactive environment for design, iterative exploration, and problem solving.

Provide library of functions for fourier analysis, optimization, numerical integration, and Linear algebra among others.

Give development tool for bettering the code quality, maintainability, and maximizing their performances.

Provide function for integration of MATLAB algorithms with the external languages and applications like Java, C, .NET, and Microsoft Excel.

10. JavaScript

It allows developing applications for mobile, desktop and web, as well as build interactive websites. When compared to Python or Java, JavaScript is easier to learn and implement because of all of the accessible UI features. It has many convenient and flexible libraries, among which React.js, Angular.js, and Vue.js are the most trending ones.

JavaScript is one of the most used programming languages by developers, ranking on the top with 62.5% in the <a href=”http://ift.tt/2hvE0Qp; rel=”nofollow”>Stack Overflow Developer Survey</a> (as you can see in the graph given below).

Features-

Universal Support

All modern web browsers support JavaScript, thanks to built-in interpreters.

Dynamic

Just like many other scripting languages, JavaScript is dynamically typed. Here, a type is linked with each value and not just with each expression. Moreover, JavaScript includes an eval function that performs statements provided as strings at run-time.

Imperative and Structured

This programming language supports almost all the structured programming syntax from C, except scoping (right now, it had only function scoping with var).

Prototype-based (Object-oriented)

JavaScript is nearly object-based with an object considered as an associative array, combined with a prototype. Each string in case of JavaScript serves the name for an object property, with two ways to specify the name. A property can be added, deleted or rebound at run-time, and most of the properties of an object can be computed using a for…in loop.

From ease of development to the richness of the end application, there are a number of reasons why the world continues to see advancements programming languages – making them newer and better.

Learning and using the ones mentioned in the article will definitely help you win the rat race to delivering top ranking apps.

The post KOTLIN, Python, and React Native among the Top 10 Programming Languages to Look Out For in 2018 appeared first on Appinventiv Official Blog - Mobile App Development Company.

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olumina · 8 years ago

Text

KOTLIN, Python, and React Native among the Top 10 Programming Languages to Look Out For in 2018

Based on the usability and ranking factors, I have listed down 10 Programming Languages that will define the next year.

Let’s cut to the chase:

Here is the list of Top 10 Programming Languages that will dominate the app development market in the year 2018.

Swift 4.0

Java 8

KOTLIN

React Native

Python

Node.Js

Haskell

MATLAB

JavaScript

1. Swift 4.0

The new version has been introduced with new workflow features and complete API for the Swift Manager Package

Features –

It is now possible to develop a number of packages before you tag your official release. Also, it easier now to work on branch of packages at the same time.

The package products are now formalized, which makes it possible to have a closer look at what the libraries that are published to the clients by the package.

To negate the effect of hostile manifests, Swift package now appears in sandbox that prevent file system modification and network access.

2. Java 8

Features –

Virtual Extension Methods and Lambda Expression

Time and Date API

The new API allows developers to manage time and date in a much cleaner, easier to understand, and natural way.

Nashhorn JavaScript Engine

A fresh high performance, lightweight implementation of the JavaScript engine has been integrated to the JDK and has been made available to the Java applications through existing APIs.

Improved Security

This has replaced the present hand-maintained document of the caller sensitive methods with the mechanism, which accurately identifies the methods and allow the callers to be discoverable reliably.

3. Kotlin

Read – Kotlin for Android App Development – The Whys and Hows and Bonus Tips

Features –

Java Interoperability

Zero Runtime Overhead

The language has concentrated extensions to the Java library. Most of its functions are in-line which simply become inline code.

Null Safety

Kotlin eliminates the side-effects of code’s null reference. The language does not compile the codes that returns or assigns a null.

Extension Functions

Developers can add methods in classes without bringing any changes to their source code. One can add the methods on the per user basis in the classes.

4. React Native

Features –

Code Reuse

The language gives you the freedom to use the same code for both iOS and Android.

Live Reload

It allows you to see the most recent change that you have made to the code, immediately.

Strong Performance

The language makes use of the Graphics Processing Unit, which makes it well tuned for mobile apps in terms of the speed advantage it offers.

Modular Architecture

5. Python

Python is known for its clean syntax and short length of code, and is the the most wanted programming language.

Features –

Easy to Learn

Open Source

The developers can freely use the language, even for their commercial uses. Other than using and distributing the software that are written in it, you can also make changes in the source code.

Portable

Python can be moved from one platform to another and run in them without any changes.

It can run seamlessly on platforms including Mac OS X, Windows, and Linux.

Standard Libraries

6. R

Features –

R supports object oriented programming with the generic functions and procedural programming with functions.

It can print the analysis reports in form of graph in both hardcopy and on-screen.

Its programming features consist of exporting data, database input, viewing data, missing data, variable labels, etc.

Packages form an element of R programming language. Thus, they are helpful in collecting the sets of R functions in a particular unit.

7. Node.Js

Node.js is the cross-platform, open-source JavaScript run-time environment for implementing JavaScript code on the server side.

It makes use of an event-focused, non-blocking I/O model, which makes it efficient and lightweight, ideal for data-concentrated real-time apps that can run across series of distributed devices.

Features –

Event Driven

Fast

Built on Google Chrome’s V8 JavaScript engine, the language’s library code execution’s speed is very fast.

Scalable

Node.js make use of one thread program, which can offer service to a large number of requests than its traditional servers such as Apache HTTP Server.

Zero Buffering

The Node.js application don’t buffer any data. They output all the data in portions.

8. Haskell

As compared to other similar programming languages, Haskell offers support for –

Lazy Evaluation

Monadic side-effects

Syntax based on the layout

Type classes

Pure functions by default

On the top of it, Huskell is one of the top 15 loved programming languages according to Stack Overflow Developer Survey.

9. MATLAB

It is one of the most superior language in the programs used for scientific and mathematical purposes. According to statistics Google Trends, this language will continue to remain in the market.

Features –

Offers interactive environment for design, iterative exploration, and problem solving.

Provide library of functions for fourier analysis, optimization, numerical integration, and Linear algebra among others.

Give development tool for bettering the code quality, maintainability, and maximizing their performances.

Provide function for integration of MATLAB algorithms with the external languages and applications like Java, C, .NET, and Microsoft Excel.

10. JavaScript

Features-

Universal Support

All modern web browsers support JavaScript, thanks to built-in interpreters.

Dynamic

Imperative and Structured

This programming language supports almost all the structured programming syntax from C, except scoping (right now, it had only function scoping with var).

Prototype-based (Object-oriented)

From ease of development to the richness of the end application, there are a number of reasons why the world continues to see advancements programming languages – making them newer and better.

Learning and using the ones mentioned in the article will definitely help you win the rat race to delivering top ranking apps.

The post KOTLIN, Python, and React Native among the Top 10 Programming Languages to Look Out For in 2018 appeared first on Appinventiv Official Blog - Mobile App Development Company.

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twobeemag · 8 years ago

Text

DNG Image Support & Exporting Images in Multi-Threaded Environment Using Aspose.Imaging for Java 17.1.0

DNG Image Support & Exporting Images in Multi-Threaded Environment Using Aspose.Imaging for Java 17.1.0 It supports exporting images in multi-threaded environment. It also supports the DNG (Digital Negative) image format (.dng). It is a publicly available archival format for the raw files generated by digital cameras. DNG helps ensure that photographers will be able to access their files in the…

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olumina · 8 years ago

Text

Top 10 Trendiest Programming Languages of 2018

Based on the usability and ranking factors, I have listed down 10 Programming Languages that will define the next year.

Let’s cut to the chase:

Here is the list of Top 10 Programming Languages that will dominate the app development market in the year 2018.

Swift 4.0

Java 8

KOTLIN

React Native

Python

Node.Js

Haskell

MATLAB

JavaScript

1. Swift 4.0

The new version has been introduced with new workflow features and complete API for the Swift Manager Package

Features –

It is now possible to develop a number of packages before you tag your official release. Also, it easier now to work on branch of packages at the same time.

The package products are now formalized, which makes it possible to have a closer look at what the libraries that are published to the clients by the package.

To negate the effect of hostile manifests, Swift package now appears in sandbox that prevent file system modification and network access.

2. Java 8

Features –

Virtual Extension Methods and Lambda Expression

Time and Date API

The new API allows developers to manage time and date in a much cleaner, easier to understand, and natural way.

Nashhorn JavaScript Engine

A fresh high performance, lightweight implementation of the JavaScript engine has been integrated to the JDK and has been made available to the Java applications through existing APIs.

Improved Security

This has replaced the present hand-maintained document of the caller sensitive methods with the mechanism, which accurately identifies the methods and allow the callers to be discoverable reliably.

3. Kotlin

Read – Kotlin for Android App Development – The Whys and Hows and Bonus Tips

Features –

Java Interoperability

Zero Runtime Overhead

The language has concentrated extensions to the Java library. Most of its functions are in-line which simply become inline code.

Null Safety

Kotlin eliminates the side-effects of code’s null reference. The language does not compile the codes that returns or assigns a null.

Extension Functions

Developers can add methods in classes without bringing any changes to their source code. One can add the methods on the per user basis in the classes.

4. React Native

Features –

Code Reuse

The language gives you the freedom to use the same code for both iOS and Android.

Live Reload

It allows you to see the most recent change that you have made to the code, immediately.

Strong Performance

The language makes use of the Graphics Processing Unit, which makes it well tuned for mobile apps in terms of the speed advantage it offers.

Modular Architecture

5. Python

Python is known for its clean syntax and short length of code, and is the the most wanted programming language.

Features –

Easy to Learn

Open Source

The developers can freely use the language, even for their commercial uses. Other than using and distributing the software that are written in it, you can also make changes in the source code.

Portable

Python can be moved from one platform to another and run in them without any changes.

It can run seamlessly on platforms including Mac OS X, Windows, and Linux.

Standard Libraries

6. R

Features –

R supports object oriented programming with the generic functions and procedural programming with functions.

It can print the analysis reports in form of graph in both hardcopy and on-screen.

Its programming features consist of exporting data, database input, viewing data, missing data, variable labels, etc.

Packages form an element of R programming language. Thus, they are helpful in collecting the sets of R functions in a particular unit.

7. Node.Js

Node.js is the cross-platform, open-source JavaScript run-time environment for implementing JavaScript code on the server side.

It makes use of an event-focused, non-blocking I/O model, which makes it efficient and lightweight, ideal for data-concentrated real-time apps that can run across series of distributed devices.

Features –

Event Driven

Fast

Built on Google Chrome’s V8 JavaScript engine, the language’s library code execution’s speed is very fast.

Scalable

Node.js make use of one thread program, which can offer service to a large number of requests than its traditional servers such as Apache HTTP Server.

Zero Buffering

The Node.js application don’t buffer any data. They output all the data in portions.

8. Haskell

As compared to other similar programming languages, Haskell offers support for –

Lazy Evaluation

Monadic side-effects

Syntax based on the layout

Type classes

Pure functions by default

On the top of it, Huskell is one of the top 15 loved programming languages according to Stack Overflow Developer Survey.

9. MATLAB

It is one of the most superior language in the programs used for scientific and mathematical purposes. According to statistics Google Trends, this language will continue to remain in the market.

Features –

Offers interactive environment for design, iterative exploration, and problem solving.

Provide library of functions for fourier analysis, optimization, numerical integration, and Linear algebra among others.

Give development tool for bettering the code quality, maintainability, and maximizing their performances.

Provide function for integration of MATLAB algorithms with the external languages and applications like Java, C, .NET, and Microsoft Excel.

10. JavaScript

Features-

Universal Support

All modern web browsers support JavaScript, thanks to built-in interpreters.

Dynamic

Imperative and Structured

This programming language supports almost all the structured programming syntax from C, except scoping (right now, it had only function scoping with var).

Prototype-based (Object-oriented)

From ease of development to the richness of the end application, there are a number of reasons why the world continues to see advancements programming languages – making them newer and better.

Learning and using the ones mentioned in the article will definitely help you win the rat race to delivering top ranking apps.

The post Top 10 Trendiest Programming Languages of 2018 appeared first on Appinventiv Official Blog - Mobile App Development Company.

0 notes