From 13a84060cf860a4cb0aea78510553c7db3658051 Mon Sep 17 00:00:00 2001 From: Marcos Luciano Date: Mon, 21 Dec 2020 11:55:42 -0300 Subject: [PATCH] Fix text * readme.md * customModels.md * multipleInferences.md --- customModels.md | 6 +++--- multipleInferences.md | 2 +- readme.md | 6 ++---- 3 files changed, 6 insertions(+), 8 deletions(-) diff --git a/customModels.md b/customModels.md index 5cc24e3..42fed77 100644 --- a/customModels.md +++ b/customModels.md @@ -21,10 +21,10 @@ How to edit DeepStream files to your custom model ## ### Editing default model -1. Donwload [my native folder](https://github.com/marcoslucianops/DeepStream-Yolo/tree/master/native), rename to yolo and move to your deepstream/sources folder. +1. Download [my native folder](https://github.com/marcoslucianops/DeepStream-Yolo/tree/master/native), rename to yolo and move to your deepstream/sources folder. 2. Copy and remane your obj.names file to labels.txt to deepstream/sources/yolo directory 3. Copy your yolo.cfg and yolo.weights files to deepstream/sources/yolo directory. -4. Edit config_infer_primary.txt for your model (example for YOLOv4) +4. Edit config_infer_primary.txt for your model ``` [property] ... @@ -305,7 +305,7 @@ deepstream-app -c deepstream_app_config.txt You can get metadata from deepstream in Python and C++. For C++, you need edit deepstream-app or deepstream-test code. For Python your need install and edit [this](https://github.com/NVIDIA-AI-IOT/deepstream_python_apps). -You need manipulate NvDsObjectMeta ([Python](https://docs.nvidia.com/metropolis/deepstream/python-api/PYTHON_API/NvDsMeta/NvDsObjectMeta.html) [C++](https://docs.nvidia.com/metropolis/deepstream/sdk-api/Meta/_NvDsObjectMeta.html)), NvDsFrameMeta ([Python](https://docs.nvidia.com/metropolis/deepstream/python-api/PYTHON_API/NvDsMeta/NvDsFrameMeta.html) [C++](https://docs.nvidia.com/metropolis/deepstream/sdk-api/Meta/_NvDsFrameMeta.html)) and NvOSD_RectParams ([Python](https://docs.nvidia.com/metropolis/deepstream/python-api/PYTHON_API/NvDsOSD/NvOSD_RectParams.html) [C++](https://docs.nvidia.com/metropolis/deepstream/sdk-api/OSD/Data_Structures/_NvOSD_FrameRectParams.html)) to get label, position, etc. of bboxs. +You need manipulate NvDsObjectMeta ([Python](https://docs.nvidia.com/metropolis/deepstream/python-api/PYTHON_API/NvDsMeta/NvDsObjectMeta.html)/[C++](https://docs.nvidia.com/metropolis/deepstream/sdk-api/Meta/_NvDsObjectMeta.html)), NvDsFrameMeta ([Python](https://docs.nvidia.com/metropolis/deepstream/python-api/PYTHON_API/NvDsMeta/NvDsFrameMeta.html)/[C++](https://docs.nvidia.com/metropolis/deepstream/sdk-api/Meta/_NvDsFrameMeta.html)) and NvOSD_RectParams ([Python](https://docs.nvidia.com/metropolis/deepstream/python-api/PYTHON_API/NvDsOSD/NvOSD_RectParams.html)/[C++](https://docs.nvidia.com/metropolis/deepstream/sdk-api/OSD/Data_Structures/_NvOSD_FrameRectParams.html)) to get label, position, etc. of bboxs. In C++ deepstream-app application, your code need be in analytics_done_buf_prob function. In C++/Python deepstream-test application, your code need be in osd_sink_pad_buffer_probe/tiler_src_pad_buffer_probe function. diff --git a/multipleInferences.md b/multipleInferences.md index 1737934..825de28 100644 --- a/multipleInferences.md +++ b/multipleInferences.md @@ -1,7 +1,7 @@ # Multiple YOLO inferences How to use multiples GIE's on DeepStream -1. Donwload [my native folder](https://github.com/marcoslucianops/DeepStream-Yolo/tree/master/native), rename to yolo and move to your deepstream/sources folder. +1. Download [my native folder](https://github.com/marcoslucianops/DeepStream-Yolo/tree/master/native), rename to yolo and move to your deepstream/sources folder. 2. Make a folder, in deepstream/sources/yolo directory, named pgie (where you will put files of primary inference). 3. Make a folder, for each secondary inference, in deepstream/sources/yolo directory, named sgie* (* = 1, 2, 3, etc.; depending on the number of secondary inferences; where you will put files of others inferences). 4. Copy and remane each obj.names file to labels.txt in each inference directory (pgie, sgie*), according each inference type. diff --git a/readme.md b/readme.md index 0242dc7..c206eda 100644 --- a/readme.md +++ b/readme.md @@ -69,7 +69,6 @@ Torchvision 0.8.1 ``` DeepStream SDK: https://youtu.be/Qi_F_IYpuFQ - Darknet: https://youtu.be/AxJJ9fnJ7Xk | TensorRT | Precision | Resolution | IoU=0.5:0.95 | IoU=0.5 | IoU=0.75 | FPS
(with display) | FPS
(without display) | @@ -173,9 +172,9 @@ pre-cluster-threshold = 0.25 (CONF_THRESH) ## ### Native TensorRT conversion -Donwload [my native folder](https://github.com/marcoslucianops/DeepStream-Yolo/tree/master/native), rename to yolo and move to your deepstream/sources folder. +Download [my native folder](https://github.com/marcoslucianops/DeepStream-Yolo/tree/master/native), rename to yolo and move to your deepstream/sources folder. -Donwload cfg and weights files from your model and move to deepstream/sources/yolo folder. +Download cfg and weights files from your model and move to deepstream/sources/yolo folder. * [YOLOv4x-Mish](https://github.com/AlexeyAB/darknet) [[cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov4x-mish.cfg)] [[weights](https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4x-mish.weights)] * [YOLOv4-CSP](https://github.com/WongKinYiu/ScaledYOLOv4/tree/yolov4-csp) [[cfg](https://raw.githubusercontent.com/AlexeyAB/darknet/master/cfg/yolov4-csp.cfg)] [[weights](https://github.com/AlexeyAB/darknet/releases/download/darknet_yolo_v4_pre/yolov4-csp.weights)] @@ -254,5 +253,4 @@ Note: If your model are listed in native tab, you can use [my native folder](htt ## For commercial DeepStream SDK projects, contact me at email address available in GitHub. - My projects: https://www.youtube.com/MarcosLucianoTV \ No newline at end of file