Commit 946b1fe5 authored by Micaela Verucchi's avatar Micaela Verucchi
Browse files

Update READMEs



Signed-off-by: default avatarMicaela Verucchi <micaelaverucchi@gmail.com>
parent 69256992
......@@ -18,7 +18,7 @@ If you use tkDNN in your research, please cite the [following paper](https://iee
```
### What's new (20 July 2021)
- [x] Support to sematic segmentation [REAME](docs/README_seg.md)
- [x] Support to sematic segmentation [README](docs/README_seg.md)
- [ ] Support to TensorRT8 (WIP)
## FPS Results
......@@ -93,16 +93,21 @@ Results for COCO val 2017 (5k images), on RTX 2080Ti, with conf threshold=0.001
- [Known issues with tkDNN on Windows](#known-issues-with-tkdnn-on-windows)
## Dependencies
This branch works on every NVIDIA GPU that supports the following (latest tested) dependencies:
* CUDA 11.0 (or >= 10)
* cuDNN 8.0.4 (or >= 7.3)
* TensorRT 7.2.0 (or >=5)
* OpenCV 4.5.2 (or >=4)
* cmake 3.21 (or >= 3.15)
* yaml-cpp 0.5.2
* eigen3 3.3.4
* curl 7.58
```
sudo apt install libyaml-cpp-dev curl libeigen3-dev
## Dependencies
This branch works on every NVIDIA GPU that supports the dependencies:
* CUDA 10.0
* CUDNN 7.603
* TENSORRT 6.01
* OPENCV 3.4
* yaml-cpp 0.5.2 (sudo apt install libyaml-cpp-dev)
```
## About OpenCV
To compile and install OpenCV4 with contrib us the script ```install_OpenCV4.sh```. It will download and compile OpenCV in Download folder.
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......@@ -59,8 +59,9 @@ For other demo videos refer to [this playlist](https://www.youtube.com/playlist?
## FPS Results
Inference FPS of shelfnet with tkDNN, average of 1200 images on
Inference FPS of shelfnet with tkDNN, average of 1200 images on:
* RTX 2080Ti (CUDA 10.2, TensorRT 7.0.0, Cudnn 7.6.5);
* Xavier AGX, Jetpack 4.3 (CUDA 10.0, CUDNN 7.6.3, tensorrt 6.0.1 );
| Platform | Test | Phase | FP32, ms | FP32, FPS | FP16, ms | FP16, FPS | INT8, ms | INT8, FPS |
| :------: | :-----: | :-----: | :-----: | :-----: | :-----: | :-----: | :-----: | :-----: |
......@@ -72,6 +73,15 @@ Inference FPS of shelfnet with tkDNN, average of 1200 images on
| RTX 2080Ti | shelfnet 2048x2048 (B=4) | inf | 36.5015 | 27.3961 | 17.0534 | 58.6395 | 15.6061 | 64.0773 |
| RTX 2080Ti | shelfnet 2048x2048 (B=4) | post | 17.3917 | 57.4985 | 17.1649 | 58.2583 | 17.5539 | 56.9675 |
| RTX 2080Ti | shelfnet 2048x2048 (B=4) | tot | 79.3283 | 12.6058 | 59.5136 | 16.8029 | 59.0903 | 16.9233 |
| AGX Xavier | shelfnet 1024x1024 (B=1) | pre | 8.0174 | 124.729 | 7.5117 | 133.126 | 7.47333 | 133.809 |
| AGX Xavier | shelfnet 1024x1024 (B=1) | inf | 72.4173 | 13.8089 | 37.505 | 26.6631 | 31.3286 | 31.9197 |
| AGX Xavier | shelfnet 1024x1024 (B=1) | post | 8.89958 | 112.365 | 8.83576 | 113.176 | 9.42655 | 106.083 |
| AGX Xavier | shelfnet 1024x1024 (B=1) | tot | 89.3342 | 11.1939 | 53.8525 | 18.5692 | 48.2285 | 20.7346 |
| AGX Xavier | shelfnet 2048x2048 (B=4) | pre | 47.1454 | 21.211 | 21.6475 | 46.1947 | 21.4201 | 46.6851 |
| AGX Xavier | shelfnet 2048x2048 (B=4) | inf | 266.537 | 3.75183 | 128.321 | 7.79293 | 107.621 | 9.29185 |
| AGX Xavier | shelfnet 2048x2048 (B=4) | post | 44.0711 | 22.6906 | 40.1732 | 24.8922 | 39.873 | 25.0796 |
| AGX Xavier | shelfnet 2048x2048 (B=4) | tot | 357.753 | 2.79522 | 190.142 | 5.25922 | 168.914 | 5.92016 |
## Known issues
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