8.[Source Directory does not Contain CMakeLists.txt (Windows)](#source-directory-does-not-contain-cmakelists.txt-windows)
9.[How Should I Link my IP Camera?](#how-should-i-link-my-ip-camera)
10.[Difference between BODY_25 vs. COCO vs. MPI](#difference-between-body_25-vs.-coco-vs.-mpi)
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@@ -89,3 +90,8 @@ Note: OpenPose library is not an executable, but a library. So instead clicking
**Q: How Should I Link my IP Camera with http protocol?.**
**A**: Usually with `http://CamIP:PORT_NO./video?x.mjpeg`.
### Difference between BODY_25 vs. COCO vs. MPI
COCO model will eventually be removed. BODY_25 model is faster, more accurate, and it includes foot keypoints. However, COCO requires less memory on GPU (being able to fit into 2GB GPUs with the default settings) and it runs faster on CPU-only mode. MPI model is only meant for people requiring the MPI-keypoint structure. It is also slower than BODY_25 and far less accurate.
1.**Note: OpenPose has been tested extensively with CUDA 8.0 and cuDNN 5.1**. We highly recommend using those versions to minimize potential installation issues. Other versions should also work, but we do not provide support about any CUDA/cuDNN installation/compilation issue, as well as problems relate dto their integration into OpenPose.
- Ubuntu: Run `sudo ubuntu/install_cuda.sh` or alternatively download and install it from their website.
- Windows: Install CUDA 8.0 after Visual Studio 2015 is installed to assure that the CUDA installation will generate all necessary files for VS. If CUDA was already installed, re-install it.
-**Important installation tips**:
- New Nvidia model GPUs (e.g., Nvidia V, GTX 2080, any Nvidia with Volta or Turing architecture, etc.) require at least CUDA 9.
- (Windows issue, reported Sep 2018): If your computer hangs when installing CUDA drivers, try installing first the [Nvidia drivers](http://www.nvidia.com/Download/index.aspx), and then installing CUDA without the Graphics Driver flag.
- (Windows): If CMake returns and error message similar to `CUDA_TOOLKIT_ROOT_DIR not found or specified` or any other CUDA component missing, then: 1) Re-install Visual Studio 2015; 2) Reboot your PC; 3) Re-install CUDA.
- Ubuntu: Run `sudo ubuntu/install_cudnn.sh` or alternatively download and install it from their website.
- Windows (and Ubuntu if manual installation): In order to manually install it, just unzip it and copy (merge) the contents on the CUDA folder, usually `/usr/local/cuda/` in Ubuntu and `C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0` in Windows.
5. AMD GPU version prerequisites:
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@@ -273,6 +274,8 @@ OpenPose displays the FPS in the basic GUI. However, more complex speed metrics
#### COCO and MPI Models
By default, the body COCO and MPI models are not downloaded. You can download them by turning on the `DOWNLOAD_BODY_COCO_MODEL` or `DOWNLOAD_BODY_MPI_MODEL` flags. It's slightly faster but less accurate and has less keypoints than the COCO body model.
Note: Check the differences between these models in [doc/faq.md#difference-between-body_25-vs.-coco-vs.-mpi](./faq.md#difference-between-body_25-vs.-coco-vs.-mpi).
#### Python API
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@@ -295,7 +298,7 @@ export MKL_NUM_THREADS="8"
export OMP_NUM_THREADS="8"
```
Do note that increasing the number of threads results in more memory use. You can check the [OpenPose benchmark](https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/doc/faq.md#speed-up-and-benchmark) for more information about speed and memory requirements in several CPUs and GPUs.
Do note that increasing the number of threads results in more memory use. You can check the [doc/faq.md#speed-up-memory-reduction-and-benchmark](./faq.md#speed-up-memory-reduction-and-benchmark) for more information about speed and memory requirements in several CPUs and GPUs.
17. Deprecated flag `--write_keypoint_json` removed (`--write_json` is the equivalent since version 1.2.1).
18. Speed up of cvMatToOpOutput and opOutputToCvMat: op::Datum::outputData is now H x W x C instead of C x H x W, making it much faster to be copied to/from op::Datum::cvOutputData.
19. Much faster GUI display by adding the `WITH_OPENCV_WITH_OPENGL` flag to tell whether to use OpenGL support for OpenCV.
20. Turned security check error into warning when using dynamic `net_resolution` for `image_dir` in CPU/OpenCL versions.
20. Turned sanity check error into warning when using dynamic `net_resolution` for `image_dir` in CPU/OpenCL versions.
21. Minimized CPU usage when queues are empty or full, in order to prevent problems such as general computer slow down, overheating, or excesive power usage.
2. Functions or parameters renamed:
1. Removed scale parameter from hand and face rectangle extractor (causing wrong results if custom `--output_resolution`).
2.`tutorial_wrapper` renamed as `tutorial_api_cpp` as well as new examples were added.
2.`tutorial_python` renamed as `tutorial_api_python` as well as new examples were added.
3.`tutorial_pose` and `tutorial_thread` renamed as `tutorial_developer`, not meant to be used by users, but rather for OpenPose developers.
7. Added a virtual destructor to almost all clases, so they can be inherited. Exceptions (for performance reasons): Array, Point, Rectangle, CvMatToOpOutput, OpOutputToCvMat.
8. Auxiliary classes in errorAndLog turned into namespaces (Profiler must be kept as class to allow static parameters).
2. Functions or parameters renamed:
1. By default, python example `tutorial_developer/python_2_pose_from_heatmaps.py` was using 2 scales starting at -1x736, changed to 1 scale at -1x368.
2. WrapperStructPose default parameters changed to match those of the OpenPose demo binary.