isabella232 / jetson_benchmarks

Jetson Benchmark

Benchmarks Targeted for Jetson Xavier NX (Using GPU+2DLA)

The script will run following Benchmarks:

• Names : Input Image Resolution
  
• Inception V4 : 299x299
  
• ResNet-50 : 224x224
  
• OpenPose : 256x456
  
• VGG-19 : 224x224
  
• YOLO-V3 : 608x608
  
• Super Resolution : 481x321
  
• Unet : 256x256
  

For benchmark results on all NVIDIA Jetson Products; please have a look at NVIDIA jetson_benchmark webpage

Following scripts are included:

1. Install Requirements for running benchmark script (install_requirements.sh)
2. CSV files containing parameters (benchmark_csv folder)
3. Download Model (utils/download_models.py)
4. Running Benchmark Script (benchmarks.py)

Version Dependencies:

• JetPack 4.4
  
• TensorRT 7
  

Set up instructions

git clone https://github.com/NVIDIA-AI-IOT/jetson_benchmarks.git
cd jetson_benchmarks
mkdir models # Open folder to store models (Optional)

Install Requirements

sudo sh install_requirements.sh
Note: All libraries will be installed for python3

Download Models

python3 utils/download_models.py --all --csv_file_path <path-to>/benchmark_csv/nx-benchmarks.csv --save_dir <absolute-path-to-downloaded-models>

Running Benchmarks

Running All Benchmark Models at Once

sudo python3 benchmark.py --all --csv_file_path <path-to>/benchmark_csv/nx-benchmarks.csv --model_dir <absolute-path-to-downloaded-models>

Sample Output

Model Name	FPS
inception_v4	311.73
vgg19_N2	66.43
super_resolution_bsd500	150.46
unet-segmentation	145.42
pose_estimation	237.1
yolov3-tiny-416	546.69
ResNet50_224x224	824.02
ssd-mobilenet-v1	887.6

Running Individual Benchmark Model

1. For Inception V4
   sudo python3 benchmark.py --model_name inception_v4 --csv_file_path <path-to>/benchmark_csv/nx-benchmarks.csv --model_dir <absolute-path-to-downloaded-models>
   

2. For VGG19
   sudo python3 benchmark.py --model_name vgg19 --csv_file_path <path-to>/benchmark_csv/nx-benchmarks.csv --model_dir <absolute-path-to-downloaded-models>
   

3. For Super Resolution
   sudo python3 benchmark.py --model_name super_resolution --csv_file_path <path-to>/benchmark_csv/nx-benchmarks.csv --model_dir <absolute-path-to-downloaded-models>
   

4. For UNET Segmentation
   sudo python3 benchmark.py --model_name unet --csv_file_path <path-to>/benchmark_csv/nx-benchmarks.csv --model_dir <absolute-path-to-downloaded-models>
   

5. For Pose Estimation
   sudo python3 benchmark.py --model_name pose_estimation --csv_file_path <path-to>/benchmark_csv/nx-benchmarks.csv --model_dir <absolute-path-to-downloaded-models>
   

6. For Tiny-YOLO-V3
   sudo python3 benchmark.py --model_name tiny-yolov3 --csv_file_path <path-to>/benchmark_csv/nx-benchmarks.csv --model_dir <absolute-path-to-downloaded-models>
   

7. For ResNet-50
   sudo python3 benchmark.py --model_name resnet --csv_file_path <path-to>/benchmark_csv/nx-benchmarks.csv --model_dir <absolute-path-to-downloaded-models>
   

8. For SSD-MobileNet-V1 Segmentation
   sudo python3 benchmark.py --model_name ssd-mobilenet-v1 --csv_file_path <path-to>/benchmark_csv/nx-benchmarks.csv --model_dir <absolute-path-to-downloaded-models>
   

For Jetson AGX Xavier

Please follow setup, and installation requirements.

Download Models

python3 utils/download_models.py --all --csv_file_path <path-to>/benchmark_csv/xavier-benchmarks.csv --save_dir <absolute-path-to-downloaded-models>

Running All Benchmark Models at Once on Jetson AGX Xavier

sudo python3 benchmark.py --all --csv_file_path <path-to>/benchmark_csv/xavier-benchmarks.csv \
                          --model_dir <absolute-path-to-downloaded-models> \
                          --jetson_devkit xavier \
                          --gpu_freq 1377000000 --dla_freq 1395200000 --power_mode 0

For Jetson TX2 and Jeston Nano

Please follow setup, and installation requirements.

Download Models

python3 utils/download_models.py --all --csv_file_path <path-to>/benchmark_csv/tx2-nano-benchmarks.csv --save_dir <absolute-path-to-downloaded-models>

Running All Benchmark Models at Once on Jetson TX2

sudo python3 benchmark.py --all --csv_file_path <path-to>/benchmark_csv/tx2-nano-benchmarks.csv \
                            --model_dir <absolute-path-to-downloaded-models> \
                            --jetson_devkit tx2 \
                            --gpu_freq 1122000000 --power_mode 3 --precision fp16

Running All Benchmark Models at Once on Jetson Nano

sudo python3 benchmark.py --all --csv_file_path <path-to>/benchmark_csv/tx2-nano-benchmarks.csv \
                            --model_dir <absolute-path-to-downloaded-models> \
                            --jetson_devkit nano \
                            --gpu_freq 921600000 --power_mode 0 --precision fp16