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add benchmark results on Jetson Nano Orin (#224)
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‎benchmark/README.md

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@@ -813,28 +813,128 @@ mean median min input size model
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126.64 125.09 110.45 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx']
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```
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<!--
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### Jetson Nano Orin
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### NVIDIA Jetson Orin Nano
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Specs: https://www.nvidia.com/en-us/autonomous-machines/embedded-systems/jetson-orin/
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- CPU: 6-core Arm® Cortex®-A78AE v8.2 64-bit CPU, 1.5MB L2 + 4MB L3
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- GPU: 1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores, max freq 625MHz
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CPU:
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```
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59.30 58.45 57.90 [1280, 720] VitTrack with ['object_tracking_vittrack_2023sep.onnx']
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$ python3 benchmark.py --all
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Benchmarking ...
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backend=cv.dnn.DNN_BACKEND_OPENCV
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target=cv.dnn.DNN_TARGET_CPU
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mean median min input size model
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2.59 2.62 2.50 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx']
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2.98 2.97 2.50 [160, 120] YuNet with ['face_detection_yunet_2023mar_int8.onnx']
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20.05 24.76 19.75 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx']
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31.84 32.72 19.75 [150, 150] SFace with ['face_recognition_sface_2021dec_int8.onnx']
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9.15 9.22 9.04 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx']
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14.33 15.35 9.04 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july_int8.onnx']
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15.00 15.17 14.80 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx']
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18.37 18.63 14.80 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb_int8.onnx']
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24.86 25.09 24.12 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx']
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30.17 34.51 24.12 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar_int8.onnx']
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18.47 18.55 18.23 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx']
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17.08 17.30 15.80 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx']
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21.26 15.89 15.80 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr_int8.onnx']
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23.19 24.15 15.80 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr_int8.onnx']
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102.30 101.90 101.44 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx']
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142.33 146.24 101.44 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan_int8.onnx']
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39.91 39.01 38.46 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx']
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51.35 50.70 38.46 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar_int8.onnx']
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125.31 126.50 121.92 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx']
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132.95 133.67 121.92 [416, 416] NanoDet with ['object_detection_nanodet_2022nov_int8.onnx']
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400.91 430.48 384.87 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx']
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476.63 509.48 384.87 [640, 640] YoloX with ['object_detection_yolox_2022nov_int8.onnx']
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19.16 19.91 18.04 [1280, 720] VitTrack with ['object_tracking_vittrack_2023sep.onnx']
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27.73 26.93 26.72 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx']
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35.16 41.14 26.72 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb_int8.onnx']
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33.05 33.18 32.67 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx']
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93.58 94.02 92.36 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx']
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119.80 153.20 92.36 [128, 256] YoutuReID with ['person_reid_youtu_2021nov_int8.onnx']
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31.51 32.19 30.69 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx']
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3.53 3.53 3.51 [100, 100] WeChatQRCode with ['detect_2021nov.prototxt', 'detect_2021nov.caffemodel', 'sr_2021nov.prototxt', 'sr_2021nov.caffemodel']
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78.10 77.77 77.17 [640, 480] PPOCRDet with ['text_detection_cn_ppocrv3_2023may.onnx']
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78.03 78.38 77.17 [640, 480] PPOCRDet with ['text_detection_en_ppocrv3_2023may.onnx']
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99.09 79.42 77.17 [640, 480] PPOCRDet with ['text_detection_cn_ppocrv3_2023may_int8.onnx']
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112.82 116.06 77.17 [640, 480] PPOCRDet with ['text_detection_en_ppocrv3_2023may_int8.onnx']
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142.97 142.84 135.56 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx']
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144.53 148.52 135.56 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx']
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134.47 146.62 112.91 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx']
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136.37 131.39 112.91 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2023feb_fp16.onnx']
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132.08 117.15 109.24 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2023feb_fp16.onnx']
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135.17 130.23 109.24 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2022oct_int8.onnx']
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138.38 143.25 109.24 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov_int8.onnx']
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137.08 134.22 109.24 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx']
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```
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CUDA:
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GPU (CUDA-FP32):
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```
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13.69 13.69 13.04 [1280, 720] VitTrack with ['object_tracking_vittrack_2023sep.onnx']
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$ python3 benchmark.py --all --fp32 --cfg_exclude wechat --cfg_overwrite_backend_target 1
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Benchmarking ...
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backend=cv.dnn.DNN_BACKEND_CUDA
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target=cv.dnn.DNN_TARGET_CUDA
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mean median min input size model
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5.23 5.27 5.17 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx']
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7.59 7.62 7.55 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx']
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8.48 8.46 8.37 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx']
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12.29 13.04 11.11 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx']
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12.91 13.28 12.79 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx']
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8.41 8.42 8.35 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx']
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9.36 9.43 8.35 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx']
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32.58 32.71 31.11 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx']
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16.33 16.08 16.04 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx']
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24.46 24.35 24.01 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx']
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103.28 103.41 102.37 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx']
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19.75 19.78 19.10 [1280, 720] VitTrack with ['object_tracking_vittrack_2023sep.onnx']
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10.84 10.76 10.75 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx']
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14.50 14.50 14.36 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx']
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23.53 23.36 23.16 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx']
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26.54 27.22 25.99 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx']
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27.49 27.80 26.97 [640, 480] PPOCRDet with ['text_detection_cn_ppocrv3_2023may.onnx']
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27.53 27.75 26.95 [640, 480] PPOCRDet with ['text_detection_en_ppocrv3_2023may.onnx']
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15.66 16.30 15.41 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx']
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15.91 15.80 15.41 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx']
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13.58 16.70 9.48 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx']
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```
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CUDA-FP16:
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GPU (CUDA-FP16):
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```
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16.29 15.77 15.77 [1280, 720] VitTrack with ['object_tracking_vittrack_2023sep.onnx']
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$ python3 benchmark.py --all --fp32 --cfg_exclude wechat --cfg_overwrite_backend_target 2
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Benchmarking ...
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backend=cv.dnn.DNN_BACKEND_CUDA
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target=cv.dnn.DNN_TARGET_CUDA_FP16
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mean median min input size model
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5.00 5.04 4.92 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx']
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5.09 5.08 5.05 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx']
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6.81 6.86 6.66 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx']
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9.19 10.18 9.06 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx']
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16.20 16.62 15.93 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx']
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6.84 6.82 6.80 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx']
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7.46 7.87 6.80 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx']
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14.18 14.16 14.03 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx']
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13.35 13.10 13.04 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx']
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19.94 19.95 19.50 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx']
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72.25 72.91 70.99 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx']
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22.37 22.44 21.60 [1280, 720] VitTrack with ['object_tracking_vittrack_2023sep.onnx']
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8.92 8.92 8.84 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx']
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11.11 11.13 10.98 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx']
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13.22 13.23 13.12 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx']
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26.79 27.04 26.24 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx']
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19.71 19.75 19.47 [640, 480] PPOCRDet with ['text_detection_cn_ppocrv3_2023may.onnx']
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19.76 19.93 19.47 [640, 480] PPOCRDet with ['text_detection_en_ppocrv3_2023may.onnx']
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16.30 15.88 15.80 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx']
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16.36 16.51 15.80 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx']
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13.64 16.27 8.90 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx']
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```
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<!--
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### Atlas 200I DK
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CPU:

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