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Partial Jetson Nano benchmark

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* Minor changes in YOLOv5.md
This commit is contained in:
Marcos Luciano
2020-12-22 23:07:10 -03:00
parent cb99cf3254
commit 01bc853660
2 changed files with 53 additions and 7 deletions
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5
YOLOv5.md
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@@ -31,6 +31,11 @@ pip3 install opencv-python
pip3 install matplotlib pip3 install matplotlib
``` ```
* Matplotlib (for Jetson plataform)
```
sudo apt-get install python3-matplotlib
```
* Scipy * Scipy
``` ```
pip3 install scipy pip3 install scipy

55
readme.md
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@@ -55,6 +55,10 @@ Request
### mAP/FPS comparison between models ### mAP/FPS comparison between models
DeepStream SDK YOLOv4: https://youtu.be/Qi_F_IYpuFQ
Darknet YOLOv4: https://youtu.be/AxJJ9fnJ7Xk
<details><summary>NVIDIA GTX 1050 (4GB Mobile)</summary> <details><summary>NVIDIA GTX 1050 (4GB Mobile)</summary>
``` ```
@@ -63,15 +67,11 @@ Driver 440.33
TensorRT 7.2.1 TensorRT 7.2.1
cuDNN 8.0.5 cuDNN 8.0.5
OpenCV 3.2.0 (libopencv-dev) OpenCV 3.2.0 (libopencv-dev)
OpenCV 4.4.0 (opencv-python) OpenCV Python 4.4.0 (opencv-python)
PyTorch 1.7.0 PyTorch 1.7.0
Torchvision 0.8.1 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<br />(with display) | FPS<br />(without display) | | TensorRT | Precision | Resolution | IoU=0.5:0.95 | IoU=0.5 | IoU=0.75 | FPS<br />(with display) | FPS<br />(without display) |
|:---------------:|:---------:|:----------:|:------------:|:-------:|:--------:|:-----------------------:|:--------------------------:| |:---------------:|:---------:|:----------:|:------------:|:-------:|:--------:|:-----------------------:|:--------------------------:|
| YOLOv5x | FP32 | 608 | 0.406 | 0.562 | 0.441 | 7.91 | 7.99 | | YOLOv5x | FP32 | 608 | 0.406 | 0.562 | 0.441 | 7.91 | 7.99 |
@@ -101,7 +101,7 @@ Darknet: https://youtu.be/AxJJ9fnJ7Xk
| YOLO-FastestXL | FP32 | 416 | 0.144 | 0.306 | 0.115 | 121.89 | 145.13 | | YOLO-FastestXL | FP32 | 416 | 0.144 | 0.306 | 0.115 | 121.89 | 145.13 |
| YOLO-FastestXL | FP32 | 320 | 0.136 | 0.279 | 0.117 | 162.65 | 199.75 | | YOLO-FastestXL | FP32 | 320 | 0.136 | 0.279 | 0.117 | 162.65 | 199.75 |
| YOLOv2 | FP32 | 608 | 0.286 | 0.534 | 0.274 | 23.92 | 25.47 | | YOLOv2 | FP32 | 608 | 0.286 | 0.534 | 0.274 | 23.92 | 25.47 |
| YOLOv2-Tiny | FP32 | 416 | 0.103 | 0.251 | 0.064 | 165.01 | 203.02 | | YOLOv2-Tiny | FP32 | 416 | 0.103 | 0.251 | 0.064 | 165.01 | 203.02 |
| Darknet | Precision | Resolution | IoU=0.5:0.95 | IoU=0.5 | IoU=0.75 | FPS<br />(with display) | FPS<br />(without display) | | Darknet | Precision | Resolution | IoU=0.5:0.95 | IoU=0.5 | IoU=0.75 | FPS<br />(with display) | FPS<br />(without display) |
|:---------------:|:---------:|:----------:|:------------:|:-------:|:--------:|:-----------------------:|:--------------------------:| |:---------------:|:---------:|:----------:|:------------:|:-------:|:--------:|:-----------------------:|:--------------------------:|
@@ -142,7 +142,48 @@ Darknet: https://youtu.be/AxJJ9fnJ7Xk
</details> </details>
<details><summary>NVIDIA Jetson Nano (4GB)</summary> <details><summary>NVIDIA Jetson Nano (4GB)</summary>
Coming soon
```
JetPack 4.4.1
CUDA 10.2
TensorRT 7.1.3
cuDNN 8.0
OpenCV 4.1.1
```
| TensorRT | Precision | Resolution | IoU=0.5:0.95 | IoU=0.5 | IoU=0.75 | FPS<br />(with display) | FPS<br />(without display) |
|:---------------:|:---------:|:----------:|:------------:|:-------:|:--------:|:-----------------------:|:--------------------------:|
| YOLOv4 | FP32 | 416 | 0.462 | 0.694 | 0.503 | 2.97 | 2.99 |
| YOLOv4 | FP16 | 416 | 0.462 | 0.694 | 0.504 | 4.89 | 4.96 |
| YOLOv4 | FP32 | 320 | 0.407 | 0.625 | 0.434 | | |
| YOLOv4 | FP16 | 320 | 0.408 | 0.625 | 0.435 | | |
| YOLOv3 | FP32 | 416 | 0.370 | 0.664 | 0.379 | | |
| YOLOv3 | FP16 | 416 | 0.370 | 0.664 | 0.378 | | |
| YOLOv4-Tiny | FP32 | 416 | 0.194 | 0.378 | 0.177 | 21.79 | 23.23 |
| YOLOv4-Tiny | FP16 | 416 | 0.194 | 0.378 | 0.177 | 24.76 | 26.18 |
| YOLOv3-Tiny-PRN | FP32 | 416 | 0.163 | 0.375 | 0.120 | 23.79 | 25.18 |
| YOLOv3-Tiny-PRN | FP16 | 416 | 0.163 | 0.375 | 0.119 | 26.08 | 27.96 |
| YOLOv3-Tiny | FP32 | 416 | 0.162 | 0.363 | 0.122 | 22.84 | 24.28 |
| YOLOv3-Tiny | FP16 | 416 | 0.162 | 0.363 | 0.122 | 25.47 | 27.18 |
| Darknet | Precision | Resolution | IoU=0.5:0.95 | IoU=0.5 | IoU=0.75 | FPS<br />(with display) | FPS<br />(without display) |
|:---------------:|:---------:|:----------:|:------------:|:-------:|:--------:|:-----------------------:|:--------------------------:|
| YOLOv4 | FP32 | 416 | | | | | |
| YOLOv4 | FP32 | 320 | | | | | |
| YOLOv3 | FP32 | 416 | | | | | |
| YOLOv4-Tiny | FP32 | 416 | | | | | |
| YOLOv3-Tiny-PRN | FP32 | 416 | | | | | |
| YOLOv3-Tiny | FP32 | 416 | | | | | |
| YOLOv2 | FP32 | 608 | | | | | |
| YOLOv2-Tiny | FP32 | 416 | | | | | |
| PyTorch | Precision | Resolution | IoU=0.5:0.95 | IoU=0.5 | IoU=0.75 | FPS<br />(with output) | FPS<br />(without output) |
|:-------:|:---------:|:----------:|:------------:|:-------:|:--------:|:----------------------:|:-------------------------:|
| YOLOv5s | FP32 | 416 | | | | | |
| YOLOv5s | FP16 | 416 | | | | | |
<br />
</details> </details>
<br /> <br />