**Q: Out of memory error** - I get an error similar to: `Check failed: error == cudaSuccess (2 vs. 0) out of memory`.
**A**: Most probably cuDNN is not installed/enabled, the default Caffe model uses >12 GB of GPU memory, cuDNN reduces it to ~2 GB for BODY_25 and ~1.5 GB for COCO.
**A**: Most probably cuDNN is not installed/enabled, the default Caffe model uses >12 GB of GPU memory, cuDNN reduces it to ~2.2 GB for BODY_25 (default) and ~1.5 GB for COCO (`--model_pose COCO`). Note that you still need at least about 2.2 GB free for the default OpenPose to run. I.e., GPUs with only 2 GB will not fit the default OpenPose, and you will have to either switch to the `COCO` model (slower and less accurate), or reduce the `--net_resolution` (faster speed but also lower accuracy).
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@@ -162,6 +163,14 @@ git submodle update
#### Runtime Error with Turing GPU (Tesla T4) or Volta GPU
**Q**: When I start OpenPose, I receive a runtime error for new GPU architectures.
**A**: To solve this problem, 1) make sure you are using CUDA 10 or higher, and 2) change line 7 in `{OPENPOSE_PATH}/3rdparty/caffe/cmake/Cuda.cmake`, from `set(Caffe_known_gpu_archs "30 35 50 52 60 61")` to `set(Caffe_known_gpu_archs "30 35 50 52 60 61 75")`.
@@ -54,9 +54,14 @@ We add links to some community-based work based on OpenPose. Note: We do not sup
-[ROS example](https://github.com/firephinx/openpose_ros)(based on a very old OpenPose version). For questions and more details, read and post ONLY on [issue thread #51](https://github.com/CMU-Perceptual-Computing-Lab/openpose/issues/51).
- Docker Images. For questions and more details, read and post ONLY on [issue thread #347](https://github.com/CMU-Perceptual-Computing-Lab/openpose/issues/347).
- Dockerfile working with CUDA 10: [link 1](https://github.com/ExSidius/openpose-docker/blob/master/Dockerfile) and [link 2](https://cloud.docker.com/repository/docker/exsidius/openpose/general).
-[Dockerfile - OpenPose v1.4.0, OpenCV, CUDA 8, CuDNN 6, Python2.7](https://gist.github.com/moiseevigor/11c02c694fc0c22fccd59521793aeaa6).
-[Link 1](https://github.com/esemeniuc/openpose-docker), it claims to also include Python support. Read and post ONLY on [issue thread #1102](https://github.com/CMU-Perceptual-Computing-Lab/openpose/issues/1102).
-[Dockerfile - OpenPose v1.4.0, OpenCV, CUDA 8, CuDNN 5, Python2.7](https://github.com/tlkh/openpose). Read and post ONLY on [issue thread #1102](https://github.com/CMU-Perceptual-Computing-Lab/openpose/issues/1102).
-[Dockerfile - OpenPose v1.4.0, OpenCV, CUDA 8, CuDNN 6, Python2.7](https://gist.github.com/moiseevigor/11c02c694fc0c22fccd59521793aeaa6).
-[Google Colab helper script](https://github.com/CMU-Perceptual-Computing-Lab/openpose/issues/949#issue-387855863): Script to install OpenPose on Google Colab. Really useful when access to a computer powerful enough to run OpenPose is not possible, so one possible way to use OpenPose is to build it on a GPU-enabled Colab runtime and then run the programs there. For questions and more details, read and post ONLY on [issue thread #949](https://github.com/CMU-Perceptual-Computing-Lab/openpose/issues/949).
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@@ -168,7 +173,25 @@ make -j`nproc`
```
#### Windows
In order to build the project, open the Visual Studio solution (Windows), called `build/OpenPose.sln`. Then, set the configuration from `Debug` to `Release` and press the green triangle icon (alternatively press <kbd>F5</kbd>).
In order to build the project, select and run only one of the 2 following alternatives.
1.**CMake-GUI alternative (recommended)**: Open the Visual Studio solution (Windows), called `build/OpenPose.sln`. Then, set the configuration from `Debug` to `Release` and press the green triangle icon (alternatively press <kbd>F5</kbd>).
2. Command-line build alternative (not recommended). NOTE: The command line alternative is not officially supported, but it was added in [GitHub issue #1198](https://github.com/CMU-Perceptual-Computing-Lab/openpose/issues/1198). For any questions or bug report about this command-line version, comment in that GitHub issue.
1. Run "MSVS 2017 Developer Command Console"
```
openpose\mkdir build
cd build
cmake .. -G "Visual Studio 15 2017 Win64" -T v140
cmake --build . --config Release
copy x64\Release\* bin\
```
2. If you want to clean build
```
cmake --clean-first .
cmake --build . --config Release
copy x64\Release\* bin\
```
**VERY IMPORTANT NOTE**: In order to use OpenPose outside Visual Studio, and assuming you have not unchecked the `BUILD_BIN_FOLDER` flag in CMake, copy all DLLs from `{build_directory}/bin` into the folder where the generated `openpose.dll` and `*.exe` demos are, e.g., `{build_directory}x64/Release` for the 64-bit release version.
@@ -23,13 +23,13 @@ This module performs 3-D keypoint (body, face, and hand) reconstruction and rend
## Installation
Check [doc/installation.md#3d-reconstruction-module](./installation.md#3d-reconstruction-module) for installation steps.
Check [doc/installation.md#3d-reconstruction-module](../installation.md#3d-reconstruction-module) for installation steps.
## Non Linear Optimization
In order to increase the 3-D reconstruction accuracy, OpenPose optionally performs non-linear optimization if Ceres solver support is enabled (only available in Ubuntu for now). To enable it, check [doc/installation.md#3d-reconstruction-module](./installation.md#3d-reconstruction-module) for more details.
In order to increase the 3-D reconstruction accuracy, OpenPose optionally performs non-linear optimization if Ceres solver support is enabled (only available in Ubuntu for now). To enable it, check [doc/installation.md#3d-reconstruction-module](../installation.md#3d-reconstruction-module) for more details.
1. Highly improved 3D triangulation for >3 cameras by fixing some small bugs.
2. Added community-based support for Nvidia NVCaffe.
3. Increased accuracy very lightly for CUDA version (about 0.01%) by adapting the threshold in `process()` in `bodyPartConnectorBase.cu` to `defaultNmsThreshold`. This also removes any posibility of future bugs in that function for using a default NMS threshold higher than 0.15 (which was the hard-coded value used previously).
4. Increased mAP but reduced mAR (both about 0.01%) as well as reduction of false positives. Step 1: removed legs where only knee/ankle/feet are found. Step 2: If no people is found in an image, `removePeopleBelowThresholds` is re-run with `maximizePositives = true`.
5. Number of maximum people is not limited by the maximum number of max peaks anymore. However, the number of body part candidates for a specific keypoint (e.g., nose) is still limited to the number of max peaks.
2. Functions or parameters renamed:
1.`--3d_min_views` default value (-1) no longer means that all camera views are required. Instead, it will be equal to max(2, min(4, #cameras-1)). This should provide a good trade-off between recall and precission.
3. Main bugs fixed:
1. Windows: Added back support for OpenGL and Spinnaker, as well as DLLs for debug compilation.
2.`06_face_from_image.cpp` and `07_hand_from_image.cpp` working again, they stopped working in version 1.5.0 with the GPU image resize for the GUI.
4. Changes/additions that affect the compatibility with the OpenPose Unity Plugin:
