add ChArUco board pattern into calib3d/camera_calibration #23575
Added opportunity to calibrate camera using ChArUco board pattern in /samples/cpp/tutorial_code/calib3d/camera_calibration/caera_calibration.cpp
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
Added charuco board generation to gen_pattern.py #23363
added charuco board generation in gen_pattern.py
moved aruco_dict_utils.cpp to samples from opencv_contrib (https://github.com/opencv/opencv_contrib/pull/3464)
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
Added charuco pattern into calibrate.py #23587
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
Improve document of cv::RotatedRect for #23335#23342fix#23335
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
Add charuco pattern into calibration.cpp #23486
Added charuco pattern into calibration.cpp. Added charuco pattern with predefined aruco dictionary and with dictionary from file.
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [х] I agree to contribute to the project under Apache 2 License.
- [х] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [х] The PR is proposed to the proper branch
- [х] There is a reference to the original bug report and related work
- [х] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [х] The feature is well documented and sample code can be built with the project CMake
Add python sample of how to use Orbbec camera. #23531
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
Fix image loading in tutorials code #23442
Fixes https://github.com/opencv/opencv/issues/23378
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [X] I agree to contribute to the project under Apache 2 License.
- [X] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [X] The PR is proposed to the proper branch
- [X] There is a reference to the original bug report and related work
- [X] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [X] The feature is well documented and sample code can be built with the project CMake
Add multiview calibration [GSOC 2022]
### Pull Request Readiness Checklist
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
The usage tutorial is on Google Docs following this link: https://docs.google.com/document/d/1k6YpD0tpSVqnVnvU2nzE34K3cp_Po6mLWqXV06CUHwQ/edit?usp=sharing
Merge with https://github.com/opencv/opencv_contrib/pull/3446
Related issue: https://github.com/opencv/opencv/issues/11810
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [ ] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [ ] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
Usage of imread(): magic number 0, unchecked result
* docs: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()
* samples, apps: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()
* tests: rewrite 0/1 to IMREAD_GRAYSCALE/IMREAD_COLOR in imread()
* doc/py_tutorials: check imread() result
Fixes#22799
Replaces #21559 which was taken as a base
Connected PR in contrib: [#3388@contrib](https://github.com/opencv/opencv_contrib/pull/3388)
### Changes
OK, now this is more Odometry-related PR than Volume-related. Anyway,
* `Volume` class gets wrapped
* The same was done for helper classes like `VolumeSettings`, `OdometryFrame` and `OdometrySettings`
* `OdometryFrame` constructor signature changed to more convenient where depth goes on 1st place, RGB image on 2nd.
This works better for depth-only `Odometry` algorithms.
* `OdometryFrame` is checked for amount of pyramid layers inside `Odometry::compute()`
* `Odometry` was fully wrapped + more docs added
* Added Python tests for `Odometry`, `OdometryFrame` and `Volume`
* Added Python sample for `Volume`
* Minor fixes including better var names
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
[teset data in opencv_extra](https://github.com/opencv/opencv_extra/pull/1016)
NanoTrack is an extremely lightweight and fast object-tracking model.
The total size is **1.1 MB**.
And the FPS on M1 chip is **150**, on Raspberry Pi 4 is about **30**. (Float32 CPU only)
With this model, many users can run object tracking on the edge device.
The author of NanoTrack is @HonglinChu.
The original repo is https://github.com/HonglinChu/NanoTrack.
### Pull Request Readiness Checklist
See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request
- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
* cmake: Fix DirectX detection in mingw
The pragma comment directive is valid for MSVC only. So, the DirectX detection
fails in mingw. The failure is fixed by adding the required linking library
(here d3d11) in the try_compile() function in OpenCVDetectDirectX.cmake file.
Also add a message if the first DirectX check fails.
* gapi: Fix compilation with mingw
These changes remove MSVC specific pragma directive. The compilation fails at
linking time due to absence of proper linking library. The required libraries
are added in corresponding CMakeLists.txt file.
* samples: Fix compilation with mingw
These changes remove MSVC specific pragma directive. The compilation fails at
linking time due to absence of proper linking library. The required libraries
are added in corresponding CMakeLists.txt file.
Add -imshow-scale flag to resize the image when displaying the results.
Add -enable-k3 flag to enable or disable the estimation of the K3 distortion coefficient.
Add flags to set the camera intrinsic parameters as an initial guess (can allow converging to the correct camera intrinsic parameters).
Add -imshow-scale flag to resize the image when displaying the results.
Add -enable-k3 flag to enable or disable the estimation of the K3 distortion coefficient.
* videoio: add support for obsensor (Orbbec RGB-D Camera )
* obsensor: code format issues fixed and some code optimized
* obsensor: fix typo and format issues
* obsensor: fix crosses initialization error
Replaced sprintf with safer snprintf
* Straightforward replacement of sprintf with safer snprintf
* Trickier replacement of sprintf with safer snprintf
Some functions were changed to take another parameter: the size of the buffer, so that they can pass that size on to snprintf.
GSoC module to save and load point cloud
* Add functionality to read point cloud data from files
* address issues found on review, add tests for mesh, refactor
* enable fail-safe execution and empty arrays as output
* Some improvements for point cloud io module
Co-authored-by: Julie Bareeva <julia.bareeva@xperience.ai>
### Critical bugs fixed:
- `seam_finder.find()` returns None and overwrites `masks_warped`
- `indices` is only 1-dimensional
### Nice-to-have bugs fixed:
- avoid invalid value in sqrt and subsequent runtime warning
- avoid printing help string on each run (use argparse builtin behavior)
### New features:
- added graphcut seam finder support
### Test Summary:
Tested on Ubuntu 20.04 with python 3.8.10 and opencv-python-contrib 4.5.5.62
there is a recent change, how `std::vector<int>` is wrapped in python,
it used to be a 2d array (requirig that weird `[0]` indexing), now it is only 1d
Add support for 3D point cloud segmentation, using the USAC framework.
* Modify the RANSAC framework in usac such that RANSAC can be used in 3D point cloud segmentation.
* 1. Add support for 3D point cloud segmentation, using the USAC framework.
2. Add solvers, error estimators for plane model and sphere model.
* Added code samples to the comments of class SACSegmentation.
* 1. Update the segment interface parameters of SACSegmentation.
2. Fix some errors in variable naming.
* Add tests for plane detection.
* 1. Add tests for sphere segmentation.
2. Fix some bugs found by tests.
3. Rename "segmentation" to "sac segmentation".
4. Rename "detect" to "segment".
TODO: Too much duplicate code, the structure of the test needs to be rebuilt.
* 1. Use SIMD acceleration for plane model and sphere model error estimation.
2. Optimize the RansacQualityImpl#getScore function to avoid multiple calls to the error#getError function.
3. Fix a warning in test_sac_segmentation.cpp.
* 1. Fix the warning of ModelConstraintFunction ambiguity.
2. Fix warning: no previous declaration for'void cv::usac::modelParamsToUsacConfig(cv::Ptr<cv::usac::SimpleUsacConfig>&, const cv::Ptr<const cv::usac::Model>& )
* Fix a warning in test_sac_segmentation.cpp about direct comparison of different types of data.
* Add code comments related to the interpretation of model coefficients.
* Update the use of custom model constraint functions.
* Simplified test code structure.
* Update the method of checking plane models.
* Delete test for cylinder.
* Add some comments about UniversalRANSAC.
* 1. The RANSAC paper in the code comments is referenced using the bibtex format.
2. The sample code in the code comments is replaced using @snippet.
3. Change the public API class SACSegmentation to interface.
4. Clean up the old useless code.
* fix warning(no previous declaration) in 3d_sac_segmentation.cpp.
* Fix compilation errors caused by 3d_sac_segmentation.cpp.
* Move the function sacModelMinimumSampleSize() from ptcloud.hpp to sac_segmentation.cpp.
* 1. Change the interface for setting the number of threads to the interface for setting whether to be parallel.
2. Move interface implementation code in ptcloud_utils.hpp to ptcloud_utils.cpp.
* SACSegmentation no longer inherits Algorithm.
* Add the constructor and destructor of SACSegmentation.
* 1. For the declaration of the common API, the prefix and suffix of the parameter names no longer contain underscores.
2. Rename the function _getMatFromInputArray -> getPointsMatFromInputArray.
3. Change part of CV_CheckDepth to CV_CheckDepthEQ.
4. Remove the doxygen flag from the source code.
5. Update the loop termination condition of SIMD in the point cloud section of 3D module.
* fix warning: passing 'bool' chooses 'int' over 'size_t {aka unsigned int}' .
* fix warning: passing 'bool' chooses 'int' over 'size_t {aka unsigned int}' .
fix cvtColor-error
* fix gray image channel error
* fix gray image channel error
* fix cvtColor error after the video end
* fix cvtColor error after the video end and change next variable
* fix cvtColor error after the video end
* reset next variable
* fix cvtColor error after the video end
* fix cvtColor error after the video end
Avoid `SyntaxWarning` on Python >= 3.8
```
>>> "convolutional" == "convolutional"
True
>>> "convolutional" is "convolutional"
<stdin>:1: SyntaxWarning: "is" with a literal. Did you mean "=="?
True
```
Related to #21121
[GSoC] OpenCV.js: Accelerate OpenCV.js DNN via WebNN
* Add WebNN backend for OpenCV DNN Module
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Add WebNN head files into OpenCV 3rd partiy files
Create webnn.hpp
update cmake
Complete README and add OpenCVDetectWebNN.cmake file
add webnn.cpp
Modify webnn.cpp
Can successfully compile the codes for creating a MLContext
Update webnn.cpp
Update README.md
Update README.md
Update README.md
Update README.md
Update cmake files and
update README.md
Update OpenCVDetectWebNN.cmake and README.md
Update OpenCVDetectWebNN.cmake
Fix OpenCVDetectWebNN.cmake and update README.md
Add source webnn_cpp.cpp and libary libwebnn_proc.so
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
update dnn.cpp
update op_webnn
update op_webnn
Update op_webnn.hpp
update op_webnn.cpp & hpp
Update op_webnn.hpp
Update op_webnn
update the skeleton
Update op_webnn.cpp
Update op_webnn
Update op_webnn.cpp
Update op_webnn.cpp
Update op_webnn.hpp
update op_webnn
update op_webnn
Solved the problems of released variables.
Fixed the bugs in op_webnn.cpp
Implement op_webnn
Implement Relu by WebNN API
Update dnn.cpp for better test
Update elementwise_layers.cpp
Implement ReLU6
Update elementwise_layers.cpp
Implement SoftMax using WebNN API
Implement Reshape by WebNN API
Implement PermuteLayer by WebNN API
Implement PoolingLayer using WebNN API
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Implement poolingLayer by WebNN API and add more detailed logs
Update dnn.cpp
Update dnn.cpp
Remove redundant codes and add more logs for poolingLayer
Add more logs in the pooling layer implementation
Fix the indent issue and resolve the compiling issue
Fix the build problems
Fix the build issue
FIx the build issue
Update dnn.cpp
Update dnn.cpp
* Fix the build issue
* Implement BatchNorm Layer by WebNN API
* Update convolution_layer.cpp
This is a temporary file for Conv2d layer implementation
* Integrate some general functions into op_webnn.cpp&hpp
* Update const_layer.cpp
* Update convolution_layer.cpp
Still have some bugs that should be fixed.
* Update conv2d layer and fc layer
still have some problems to be fixed.
* update constLayer, conv layer, fc layer
There are still some bugs to be fixed.
* Fix the build issue
* Update concat_layer.cpp
Still have some bugs to be fixed.
* Update conv2d layer, fully connected layer and const layer
* Update convolution_layer.cpp
* Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron)
* Delete bib19450.aux
* Add WebNN backend for OpenCV DNN Module
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Add WebNN head files into OpenCV 3rd partiy files
Create webnn.hpp
update cmake
Complete README and add OpenCVDetectWebNN.cmake file
add webnn.cpp
Modify webnn.cpp
Can successfully compile the codes for creating a MLContext
Update webnn.cpp
Update README.md
Update README.md
Update README.md
Update README.md
Update cmake files and
update README.md
Update OpenCVDetectWebNN.cmake and README.md
Update OpenCVDetectWebNN.cmake
Fix OpenCVDetectWebNN.cmake and update README.md
Add source webnn_cpp.cpp and libary libwebnn_proc.so
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
Update dnn.cpp
update dnn.cpp
update op_webnn
update op_webnn
Update op_webnn.hpp
update op_webnn.cpp & hpp
Update op_webnn.hpp
Update op_webnn
update the skeleton
Update op_webnn.cpp
Update op_webnn
Update op_webnn.cpp
Update op_webnn.cpp
Update op_webnn.hpp
update op_webnn
update op_webnn
Solved the problems of released variables.
Fixed the bugs in op_webnn.cpp
Implement op_webnn
Implement Relu by WebNN API
Update dnn.cpp for better test
Update elementwise_layers.cpp
Implement ReLU6
Update elementwise_layers.cpp
Implement SoftMax using WebNN API
Implement Reshape by WebNN API
Implement PermuteLayer by WebNN API
Implement PoolingLayer using WebNN API
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Update pooling_layer.cpp
Implement poolingLayer by WebNN API and add more detailed logs
Update dnn.cpp
Update dnn.cpp
Remove redundant codes and add more logs for poolingLayer
Add more logs in the pooling layer implementation
Fix the indent issue and resolve the compiling issue
Fix the build problems
Fix the build issue
FIx the build issue
Update dnn.cpp
Update dnn.cpp
* Fix the build issue
* Implement BatchNorm Layer by WebNN API
* Update convolution_layer.cpp
This is a temporary file for Conv2d layer implementation
* Integrate some general functions into op_webnn.cpp&hpp
* Update const_layer.cpp
* Update convolution_layer.cpp
Still have some bugs that should be fixed.
* Update conv2d layer and fc layer
still have some problems to be fixed.
* update constLayer, conv layer, fc layer
There are still some bugs to be fixed.
* Update conv2d layer, fully connected layer and const layer
* Update convolution_layer.cpp
* Add OpenCV.js DNN module WebNN Backend (both using webnn-polyfill and electron)
* Update dnn.cpp
* Fix Error in dnn.cpp
* Resolve duplication in conditions in convolution_layer.cpp
* Fixed the issues in the comments
* Fix building issue
* Update tutorial
* Fixed comments
* Address the comments
* Update CMakeLists.txt
* Offer more accurate perf test on native
* Add better perf tests for both native and web
* Modify per tests for better results
* Use more latest version of Electron
* Support latest WebNN Clamp op
* Add definition of HAVE_WEBNN macro
* Support group convolution
* Implement Scale_layer using WebNN
* Add Softmax option for native classification example
* Fix comments
* Fix comments
Add DNN-based face detection and face recognition into modules/objdetect
* Add DNN-based face detector impl and interface
* Add a sample for DNN-based face detector
* add recog
* add notes
* move samples from samples/cpp to samples/dnn
* add documentation for dnn_face
* add set/get methods for input size, nms & score threshold and topk
* remove the DNN prefix from the face detector and face recognizer
* remove default values in the constructor of impl
* regenerate priors after setting input size
* two filenames for readnet
* Update face.hpp
* Update face_recognize.cpp
* Update face_match.cpp
* Update face.hpp
* Update face_recognize.cpp
* Update face_match.cpp
* Update face_recognize.cpp
* Update dnn_face.markdown
* Update dnn_face.markdown
* Update face.hpp
* Update dnn_face.markdown
* add regression test for face detection
* remove underscore prefix; fix warnings
* add reference & acknowledgement for face detection
* Update dnn_face.markdown
* Update dnn_face.markdown
* Update ts.hpp
* Update test_face.cpp
* Update face_match.cpp
* fix a compile error for python interface; add python examples for face detection and recognition
* Major changes for Vadim's comments:
* Replace class name FaceDetector with FaceDetectorYN in related failes
* Declare local mat before loop in modules/objdetect/src/face_detect.cpp
* Make input image and save flag optional in samples/dnn/face_detect(.cpp, .py)
* Add camera support in samples/dnn/face_detect(.cpp, .py)
* correct file paths for regression test
* fix convertion warnings; remove extra spaces
* update face_recog
* Update dnn_face.markdown
* Fix warnings and errors for the default CI reports:
* Remove trailing white spaces and extra new lines.
* Fix convertion warnings for windows and iOS.
* Add braces around initialization of subobjects.
* Fix warnings and errors for the default CI systems:
* Add prefix 'FR_' for each value name in enum DisType to solve the
redefinition error for iOS compilation; Modify other code accordingly
* Add bookmark '#tutorial_dnn_face' to solve warnings from doxygen
* Correct documentations to solve warnings from doxygen
* update FaceRecognizerSF
* Fix the error for CI to find ONNX models correctly
* add suffix f to float assignments
* add backend & target options for initializing face recognizer
* add checkeq for checking input size and preset size
* update test and threshold
* changes in response to alalek's comments:
* fix typos in samples/dnn/face_match.py
* import numpy before importing cv2
* add documentation to .setInputSize()
* remove extra include in face_recognize.cpp
* fix some bugs
* Update dnn_face.markdown
* update thresholds; remove useless code
* add time suffix to YuNet filename in test
* objdetect: update test code
Tutorial for parallel_for_ and Universal Intrinsic (GSoC '21)
* New parallel_for tutorial
* Universal Intrinsics Draft Tutorial
* Added draft of universal intrinsic tutorial
* * Added final markdown for parallel_for_new
* Added first half of universal intrinsic tutorial
* Fixed warnings in documentation and sample code for parallel_for_new
tutorial
* Restored original parallel_for_ tutorial and table_of_content_core
* Minor changes
* Added demonstration of 1-D vectorized convolution
* * Added 2-D convolution implementation and tutorial
* Minor changes in vectorized implementation of 1-D and 2-D convolution
* Minor changes to univ_intrin tutorial. Added new tutorials to the table of contents
* Minor changes
* Removed variable sized array initializations
* Fixed conversion warnings
* Added doxygen references, minor fixes
* Added jpg image for parallel_for_ doc
