| # OpenCV Zoo Benchmark | |
| Benchmarking the speed of OpenCV DNN inferring different models in the zoo. Result of each model includes the time of its preprocessing, inference and postprocessing stages. | |
| Data for benchmarking will be downloaded and loaded in [data](./data) based on given config. | |
| ## Preparation | |
| 1. Install `python >= 3.6`. | |
| 2. Install dependencies: `pip install -r requirements.txt`. | |
| 3. Download data for benchmarking. | |
| 1. Download all data: `python download_data.py` | |
| 2. Download one or more specified data: `python download_data.py face text`. Available names can be found in `download_data.py`. | |
| 3. You can also download all data from https://pan.baidu.com/s/18sV8D4vXUb2xC9EG45k7bg (code: pvrw). Please place and extract data packages under [./data](./data). | |
| ## Benchmarking | |
| **Linux**: | |
| ```shell | |
| export PYTHONPATH=$PYTHONPATH:.. | |
| # Single config | |
| python benchmark.py --cfg ./config/face_detection_yunet.yaml | |
| # All configs | |
| python benchmark.py --all | |
| # All configs but only fp32 models (--fp32, --fp16, --int8 are available for now) | |
| python benchmark.py --all --fp32 | |
| # All configs but exclude some of them (fill with config name keywords, not sensitive to upper/lower case, seperate with colons) | |
| python benchmark.py --all --cfg_exclude wechat | |
| python benchmark.py --all --cfg_exclude wechat:dasiamrpn | |
| # All configs but exclude some of the models (fill with exact model names, sensitive to upper/lower case, seperate with colons) | |
| python benchmark.py --all --model_exclude license_plate_detection_lpd_yunet_2023mar_int8.onnx:human_segmentation_pphumanseg_2023mar_int8.onnx | |
| # All configs with overwritten backend and target (run with --help to get available combinations) | |
| python benchmark.py --all --cfg_overwrite_backend_target 1 | |
| ``` | |
| **Windows**: | |
| - CMD | |
| ```shell | |
| set PYTHONPATH=%PYTHONPATH%;.. | |
| python benchmark.py --cfg ./config/face_detection_yunet.yaml | |
| ``` | |
| - PowerShell | |
| ```shell | |
| $env:PYTHONPATH=$env:PYTHONPATH+";.." | |
| python benchmark.py --cfg ./config/face_detection_yunet.yaml | |
| ``` | |
| ## Detailed Results | |
| Benchmark is done with latest `opencv-python==4.8.0.74` and `opencv-contrib-python==4.8.0.74` on the following platforms. Some models are excluded because of support issues. | |
| ### Intel 12700K | |
| Specs: [details](https://www.intel.com/content/www/us/en/products/sku/134594/intel-core-i712700k-processor-25m-cache-up-to-5-00-ghz/specifications.html) | |
| - CPU: 8 Performance-cores, 4 Efficient-cores, 20 threads | |
| - Performance-core: 3.60 GHz base freq, turbo up to 4.90 GHz | |
| - Efficient-core: 2.70 GHz base freq, turbo up to 3.80 GHz | |
| CPU: | |
| ``` | |
| $ python3 benchmark.py --all | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_OPENCV | |
| target=cv.dnn.DNN_TARGET_CPU | |
| mean median min input size model | |
| 0.73 0.81 0.58 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx'] | |
| 0.85 0.78 0.58 [160, 120] YuNet with ['face_detection_yunet_2023mar_int8.onnx'] | |
| 4.52 4.70 4.25 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 6.67 7.25 4.25 [150, 150] SFace with ['face_recognition_sface_2021dec_int8.onnx'] | |
| 2.53 2.33 2.18 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 3.77 3.71 2.18 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july_int8.onnx'] | |
| 3.91 3.84 3.65 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 4.66 4.99 3.65 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb_int8.onnx'] | |
| 8.21 8.97 6.22 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 8.73 10.08 6.22 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar_int8.onnx'] | |
| 4.33 4.70 3.65 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 4.20 4.05 3.19 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 4.87 3.92 3.19 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr_int8.onnx'] | |
| 5.30 6.19 3.19 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr_int8.onnx'] | |
| 24.26 23.81 23.25 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 29.45 30.19 23.25 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan_int8.onnx'] | |
| 9.06 8.40 7.64 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 10.25 12.59 7.64 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar_int8.onnx'] | |
| 44.85 45.84 43.06 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 46.10 47.53 43.06 [416, 416] NanoDet with ['object_detection_nanodet_2022nov_int8.onnx'] | |
| 144.89 149.58 125.71 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 143.83 146.39 119.75 [640, 640] YoloX with ['object_detection_yolox_2022nov_int8.onnx'] | |
| 23.43 22.82 20.90 [1280, 720] DaSiamRPN with ['object_tracking_dasiamrpn_kernel_cls1_2021nov.onnx', 'object_tracking_dasiamrpn_kernel_r1_2021nov.onnx', 'object_tracking_dasiamrpn_model_2021nov.onnx'] | |
| 12.99 13.11 12.14 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 12.64 12.44 10.82 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb_int8.onnx'] | |
| 12.64 11.83 11.03 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 22.13 21.99 21.48 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 26.37 33.51 21.48 [128, 256] YoutuReID with ['person_reid_youtu_2021nov_int8.onnx'] | |
| 10.07 9.68 8.16 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx'] | |
| 1.19 1.30 1.07 [100, 100] WeChatQRCode with ['detect_2021nov.prototxt', 'detect_2021nov.caffemodel', 'sr_2021nov.prototxt', 'sr_2021nov.caffemodel'] | |
| 80.97 80.06 73.20 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 80.73 85.47 72.06 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| 17.97 16.18 12.43 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx'] | |
| 19.54 20.66 12.43 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx'] | |
| 17.73 24.25 9.65 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx'] | |
| 17.65 18.90 9.65 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2023feb_fp16.onnx'] | |
| 16.97 15.14 9.65 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2023feb_fp16.onnx'] | |
| 17.21 16.47 9.65 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2022oct_int8.onnx'] | |
| 17.68 14.54 9.65 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov_int8.onnx'] | |
| 17.31 16.09 9.65 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx'] | |
| ``` | |
| ### Rasberry Pi 4B | |
| Specs: [details](https://www.raspberrypi.com/products/raspberry-pi-4-model-b/specifications/) | |
| - CPU: Broadcom BCM2711, Quad core Cortex-A72 (ARM v8) 64-bit SoC @ 1.5 GHz. | |
| CPU: | |
| ``` | |
| $ python3 benchmark.py --all | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_OPENCV | |
| target=cv.dnn.DNN_TARGET_CPU | |
| mean median min input size model | |
| 5.96 5.93 5.90 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx'] | |
| 6.09 6.11 5.90 [160, 120] YuNet with ['face_detection_yunet_2023mar_int8.onnx'] | |
| 73.30 73.22 72.32 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 88.20 89.95 72.32 [150, 150] SFace with ['face_recognition_sface_2021dec_int8.onnx'] | |
| 32.33 32.20 31.99 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 39.82 40.78 31.99 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july_int8.onnx'] | |
| 108.37 108.31 106.93 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 75.91 78.95 49.78 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb_int8.onnx'] | |
| 76.29 77.10 75.21 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 77.33 77.73 75.21 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar_int8.onnx'] | |
| 66.22 66.09 65.90 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 59.91 60.72 54.63 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 62.83 54.85 54.63 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr_int8.onnx'] | |
| 62.47 62.13 54.63 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr_int8.onnx'] | |
| 625.82 667.05 425.55 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 508.92 667.04 373.14 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan_int8.onnx'] | |
| 147.19 146.62 146.31 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 143.70 155.87 139.90 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar_int8.onnx'] | |
| 214.87 214.19 213.21 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 212.90 212.93 209.55 [416, 416] NanoDet with ['object_detection_nanodet_2022nov_int8.onnx'] | |
| 1690.06 2303.34 1480.63 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 1489.54 1435.48 1308.12 [640, 640] YoloX with ['object_detection_yolox_2022nov_int8.onnx'] | |
| 564.90 580.35 527.49 [1280, 720] DaSiamRPN with ['object_tracking_dasiamrpn_kernel_cls1_2021nov.onnx', 'object_tracking_dasiamrpn_kernel_r1_2021nov.onnx', 'object_tracking_dasiamrpn_model_2021nov.onnx'] | |
| 356.63 357.29 354.42 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 217.52 229.39 101.61 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb_int8.onnx'] | |
| 198.63 198.25 196.68 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 417.23 434.54 388.38 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 381.72 394.15 308.62 [128, 256] YoutuReID with ['person_reid_youtu_2021nov_int8.onnx'] | |
| 194.47 195.18 191.67 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx'] | |
| 5.90 5.90 5.81 [100, 100] WeChatQRCode with ['detect_2021nov.prototxt', 'detect_2021nov.caffemodel', 'sr_2021nov.prototxt', 'sr_2021nov.caffemodel'] | |
| 2033.55 2454.13 1769.20 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 1896.61 1977.38 1769.20 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| 237.73 237.57 236.82 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx'] | |
| 265.16 270.22 236.82 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx'] | |
| 239.69 298.68 198.88 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx'] | |
| 234.90 249.29 198.88 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2023feb_fp16.onnx'] | |
| 227.47 200.42 198.88 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2023feb_fp16.onnx'] | |
| 226.39 213.26 198.88 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2022oct_int8.onnx'] | |
| 226.10 227.18 198.88 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov_int8.onnx'] | |
| 220.63 217.04 193.47 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx'] | |
| ``` | |
| ### Jetson Nano B01 | |
| Specs: [details](https://developer.nvidia.com/embedded/jetson-nano-developer-kit) | |
| - CPU: Quad-core ARM A57 @ 1.43 GHz | |
| - GPU: 128-core NVIDIA Maxwell | |
| CPU: | |
| ``` | |
| $ python3 benchmark.py --all | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_OPENCV | |
| target=cv.dnn.DNN_TARGET_CPU | |
| mean median min input size model | |
| 5.64 5.55 5.50 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx'] | |
| 5.91 6.00 5.50 [160, 120] YuNet with ['face_detection_yunet_2023mar_int8.onnx'] | |
| 61.32 61.38 61.08 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 76.85 78.69 61.08 [150, 150] SFace with ['face_recognition_sface_2021dec_int8.onnx'] | |
| 27.39 27.54 27.26 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 34.69 35.62 27.26 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july_int8.onnx'] | |
| 50.39 50.31 50.22 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 48.97 49.42 47.46 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb_int8.onnx'] | |
| 68.07 67.81 67.72 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 73.97 74.83 67.72 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar_int8.onnx'] | |
| 63.85 63.63 63.51 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 55.14 55.93 47.84 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 60.80 48.09 47.84 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr_int8.onnx'] | |
| 60.99 61.22 47.84 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr_int8.onnx'] | |
| 352.73 352.51 351.53 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 374.22 376.71 351.53 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan_int8.onnx'] | |
| 134.60 135.00 133.68 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 137.10 137.32 133.68 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar_int8.onnx'] | |
| 215.10 215.30 214.30 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 216.18 216.19 214.30 [416, 416] NanoDet with ['object_detection_nanodet_2022nov_int8.onnx'] | |
| 1207.83 1208.71 1203.64 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 1236.98 1250.21 1203.64 [640, 640] YoloX with ['object_detection_yolox_2022nov_int8.onnx'] | |
| 456.79 456.90 445.83 [1280, 720] DaSiamRPN with ['object_tracking_dasiamrpn_kernel_cls1_2021nov.onnx', 'object_tracking_dasiamrpn_kernel_r1_2021nov.onnx', 'object_tracking_dasiamrpn_model_2021nov.onnx'] | |
| 124.89 125.25 124.53 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 107.99 109.82 94.05 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb_int8.onnx'] | |
| 108.41 108.33 107.91 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 354.88 354.70 354.34 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 343.35 344.56 333.41 [128, 256] YoutuReID with ['person_reid_youtu_2021nov_int8.onnx'] | |
| 89.93 91.58 88.28 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx'] | |
| 5.69 5.72 5.66 [100, 100] WeChatQRCode with ['detect_2021nov.prototxt', 'detect_2021nov.caffemodel', 'sr_2021nov.prototxt', 'sr_2021nov.caffemodel'] | |
| 1070.55 1072.14 1055.67 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 1071.56 1071.38 1055.67 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| 258.11 258.13 257.64 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx'] | |
| 275.27 277.20 257.64 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx'] | |
| 254.90 295.88 221.12 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx'] | |
| 252.73 258.90 221.12 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2023feb_fp16.onnx'] | |
| 245.08 222.01 221.12 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2023feb_fp16.onnx'] | |
| 245.75 236.58 221.12 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2022oct_int8.onnx'] | |
| 248.42 251.65 221.12 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov_int8.onnx'] | |
| 244.31 236.64 221.12 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx'] | |
| ``` | |
| GPU (CUDA-FP32): | |
| <!-- config wechat is excluded due to its api does not support setting backend and target --> | |
| ``` | |
| $ python3 benchmark.py --all --fp32 --cfg_exclude wechat --cfg_overwrite_backend_target 1 | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_CUDA | |
| target=cv.dnn.DNN_TARGET_CUDA | |
| mean median min input size model | |
| 11.16 10.31 10.23 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx'] | |
| 24.82 24.90 24.33 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 14.39 14.44 13.83 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 24.52 24.01 23.84 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 69.63 69.88 64.73 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 29.06 29.10 28.80 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 28.54 28.57 27.88 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 99.05 99.65 93.60 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 54.24 55.24 52.87 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 63.63 63.43 63.32 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 371.45 378.00 366.39 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 77.50 77.73 76.16 [1280, 720] DaSiamRPN with ['object_tracking_dasiamrpn_kernel_cls1_2021nov.onnx', 'object_tracking_dasiamrpn_kernel_r1_2021nov.onnx', 'object_tracking_dasiamrpn_model_2021nov.onnx'] | |
| 33.85 33.90 33.61 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 38.16 37.33 37.10 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 91.65 91.98 89.90 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 91.40 92.74 89.76 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx'] | |
| 223.24 224.30 216.37 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 223.03 222.28 216.37 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| 44.24 45.21 41.87 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx'] | |
| 45.15 44.15 41.87 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx'] | |
| 36.82 46.54 21.75 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx'] | |
| ``` | |
| GPU (CUDA-FP16): | |
| <!-- config wechat is excluded due to its api does not support setting backend and target --> | |
| ``` | |
| $ python3 benchmark.py --all --fp32 --cfg_exclude wechat --cfg_overwrite_backend_target 2 | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_CUDA | |
| target=cv.dnn.DNN_TARGET_CUDA_FP16 | |
| mean median min input size model | |
| 25.41 25.43 25.31 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx'] | |
| 113.14 112.02 111.74 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 89.04 88.90 88.59 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 96.62 96.39 96.26 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 69.78 70.65 66.74 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 118.47 118.45 118.10 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 125.69 126.63 118.10 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 64.08 62.97 62.33 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 366.46 366.88 363.46 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 163.06 163.34 161.77 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 301.10 311.52 297.74 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 53.34 54.30 51.79 [1280, 720] DaSiamRPN with ['object_tracking_dasiamrpn_kernel_cls1_2021nov.onnx', 'object_tracking_dasiamrpn_kernel_r1_2021nov.onnx', 'object_tracking_dasiamrpn_model_2021nov.onnx'] | |
| 149.37 149.95 148.01 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 153.89 153.96 153.43 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 44.29 44.03 43.62 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 91.28 92.89 89.79 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx'] | |
| 254.78 256.13 245.60 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 254.98 255.20 245.60 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| 33.07 32.88 32.00 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx'] | |
| 33.88 33.64 32.00 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx'] | |
| 29.32 33.70 20.69 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx'] | |
| ``` | |
| ### Khadas VIM3 | |
| Specs: [details](https://www.khadas.com/vim3) | |
| - (SoC) CPU: Amlogic A311D, 2.2 GHz Quad core ARM Cortex-A73 and 1.8 GHz dual core Cortex-A53 | |
| - NPU: 5 TOPS Performance NPU INT8 inference up to 1536 MAC Supports all major deep learning frameworks including TensorFlow and Caffe | |
| CPU: | |
| ``` | |
| $ python3 benchmark.py --all | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_OPENCV | |
| target=cv.dnn.DNN_TARGET_CPU | |
| mean median min input size model | |
| 4.60 4.57 4.47 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx'] | |
| 5.10 5.15 4.47 [160, 120] YuNet with ['face_detection_yunet_2023mar_int8.onnx'] | |
| 53.88 52.80 51.99 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 67.86 67.67 51.99 [150, 150] SFace with ['face_recognition_sface_2021dec_int8.onnx'] | |
| 40.93 41.29 27.33 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 42.81 56.31 27.33 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july_int8.onnx'] | |
| 58.84 56.15 53.14 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 56.36 60.14 45.29 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb_int8.onnx'] | |
| 76.53 67.95 65.13 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 72.25 69.88 65.13 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar_int8.onnx'] | |
| 66.50 64.06 58.56 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 59.10 75.36 45.69 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 62.44 48.81 45.69 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr_int8.onnx'] | |
| 60.46 54.93 45.69 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr_int8.onnx'] | |
| 372.65 404.31 326.91 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 359.72 336.21 326.91 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan_int8.onnx'] | |
| 145.21 125.62 124.87 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 130.10 139.45 116.10 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar_int8.onnx'] | |
| 218.21 216.01 199.88 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 212.69 262.75 170.88 [416, 416] NanoDet with ['object_detection_nanodet_2022nov_int8.onnx'] | |
| 1110.87 1112.27 1085.31 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 1128.73 1157.12 1085.31 [640, 640] YoloX with ['object_detection_yolox_2022nov_int8.onnx'] | |
| 382.57 464.42 354.66 [1280, 720] DaSiamRPN with ['object_tracking_dasiamrpn_kernel_cls1_2021nov.onnx', 'object_tracking_dasiamrpn_kernel_r1_2021nov.onnx', 'object_tracking_dasiamrpn_model_2021nov.onnx'] | |
| 147.01 144.01 139.27 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 119.70 118.95 94.09 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb_int8.onnx'] | |
| 107.63 107.09 105.61 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 333.03 346.65 322.37 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 322.95 315.22 303.07 [128, 256] YoutuReID with ['person_reid_youtu_2021nov_int8.onnx'] | |
| 127.16 173.93 99.77 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx'] | |
| 975.49 977.45 952.43 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 970.16 970.83 928.66 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| 194.80 195.37 192.65 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx'] | |
| 209.49 208.33 192.65 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx'] | |
| 192.90 227.02 161.94 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx'] | |
| 192.52 197.03 161.94 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2023feb_fp16.onnx'] | |
| 185.92 168.22 161.94 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2023feb_fp16.onnx'] | |
| 185.01 183.14 161.94 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2022oct_int8.onnx'] | |
| 186.09 194.14 161.94 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov_int8.onnx'] | |
| 181.79 181.65 154.21 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx'] | |
| ``` | |
| NPU (TIMVX): | |
| <!-- config face_detection and licence_plate are excluded due to https://github.com/opencv/opencv_zoo/pull/190#discussion_r1257832066 --> | |
| ``` | |
| $ python3 benchmark.py --all --int8 --cfg_overwrite_backend_target 3 --cfg_exclude face_detection:license_plate | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_TIMVX | |
| target=cv.dnn.DNN_TARGET_NPU | |
| mean median min input size model | |
| 5.08 4.72 4.70 [160, 120] YuNet with ['face_detection_yunet_2023mar_int8.onnx'] | |
| 45.83 47.06 43.04 [150, 150] SFace with ['face_recognition_sface_2021dec_int8.onnx'] | |
| 29.20 27.55 26.25 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july_int8.onnx'] | |
| 18.47 18.16 17.96 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb_int8.onnx'] | |
| 28.25 28.35 27.98 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar_int8.onnx'] | |
| 149.05 155.10 144.42 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr_int8.onnx'] | |
| 147.40 147.49 135.90 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr_int8.onnx'] | |
| 75.91 79.27 71.98 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan_int8.onnx'] | |
| 30.98 30.56 29.36 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar_int8.onnx'] | |
| 117.71 119.69 107.37 [416, 416] NanoDet with ['object_detection_nanodet_2022nov_int8.onnx'] | |
| 379.46 366.19 360.02 [640, 640] YoloX with ['object_detection_yolox_2022nov_int8.onnx'] | |
| 33.90 36.32 31.71 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb_int8.onnx'] | |
| 40.34 41.50 38.47 [128, 256] YoutuReID with ['person_reid_youtu_2021nov_int8.onnx'] | |
| 239.68 239.31 236.03 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2022oct_int8.onnx'] | |
| 199.42 203.20 166.15 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov_int8.onnx'] | |
| 197.49 169.51 166.15 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx'] | |
| ``` | |
| ### Atlas 200 DK | |
| Specs: [details_en](https://e.huawei.com/uk/products/cloud-computing-dc/atlas/atlas-200), [details_cn](https://www.hiascend.com/zh/hardware/developer-kit) | |
| - (SoC) CPU: 8-core Coretext-A55 @ 1.6 GHz (max) | |
| - NPU: Ascend 310, dual DaVinci AI cores, 22/16/8 TOPS INT8. | |
| CPU: | |
| <!-- config wechat is excluded due to it needs building with opencv_contrib --> | |
| ``` | |
| $ python3 benchmark.py --all --cfg_exclude wechat | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_OPENCV | |
| target=cv.dnn.DNN_TARGET_CPU | |
| mean median min input size model | |
| 7.82 7.82 7.77 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx'] | |
| 8.57 8.77 7.77 [160, 120] YuNet with ['face_detection_yunet_2023mar_int8.onnx'] | |
| 92.21 92.11 91.87 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 122.07 126.02 91.87 [150, 150] SFace with ['face_recognition_sface_2021dec_int8.onnx'] | |
| 42.93 43.26 42.75 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 55.91 57.40 42.75 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july_int8.onnx'] | |
| 67.85 67.91 67.47 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 70.06 70.21 67.47 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb_int8.onnx'] | |
| 102.49 102.65 102.10 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 114.02 116.16 102.10 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar_int8.onnx'] | |
| 92.66 92.49 92.36 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 79.39 80.75 68.47 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 89.66 68.66 68.47 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr_int8.onnx'] | |
| 90.59 92.13 68.47 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr_int8.onnx'] | |
| 499.55 500.15 498.36 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 571.85 580.88 498.36 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan_int8.onnx'] | |
| 201.99 201.55 200.62 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 216.72 217.34 200.62 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar_int8.onnx'] | |
| 313.66 313.85 312.13 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 322.98 323.45 312.13 [416, 416] NanoDet with ['object_detection_nanodet_2022nov_int8.onnx'] | |
| 1875.33 1877.53 1871.26 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 1989.04 2005.25 1871.26 [640, 640] YoloX with ['object_detection_yolox_2022nov_int8.onnx'] | |
| 637.54 640.61 626.98 [1280, 720] DaSiamRPN with ['object_tracking_dasiamrpn_kernel_cls1_2021nov.onnx', 'object_tracking_dasiamrpn_kernel_r1_2021nov.onnx', 'object_tracking_dasiamrpn_model_2021nov.onnx'] | |
| 159.80 159.62 159.40 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 152.18 152.86 145.56 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb_int8.onnx'] | |
| 145.83 145.77 145.45 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 521.46 521.66 520.28 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 541.50 544.02 520.28 [128, 256] YoutuReID with ['person_reid_youtu_2021nov_int8.onnx'] | |
| 134.02 136.01 132.06 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx'] | |
| 1441.73 1442.80 1440.26 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 1436.45 1437.89 1430.58 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| 285.19 284.91 284.69 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx'] | |
| 318.96 323.30 284.69 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx'] | |
| 289.82 360.87 244.07 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx'] | |
| 285.40 303.13 244.07 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2023feb_fp16.onnx'] | |
| 274.67 244.47 243.87 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2023feb_fp16.onnx'] | |
| 277.84 262.99 243.87 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2022oct_int8.onnx'] | |
| 283.02 280.77 243.87 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov_int8.onnx'] | |
| 279.21 262.55 243.87 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx'] | |
| ``` | |
| NPU (CANN): | |
| ``` | |
| $ python3 benchmark.py --all --fp32 --cfg_exclude wechat:dasiamrpn:crnn --model_exclude pose_estimation_mediapipe_2023mar.onnx --cfg_overwrite_backend_target 4 | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_CANN | |
| target=cv.dnn.DNN_TARGET_NPU | |
| mean median min input size model | |
| 2.24 2.21 2.19 [160, 120] YuNet with ['face_detection_yunet_2022mar.onnx'] | |
| 2.66 2.66 2.64 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 2.19 2.19 2.16 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 6.27 6.22 6.17 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 6.94 6.94 6.85 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 5.15 5.13 5.10 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 5.41 5.42 5.10 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 6.99 6.99 6.95 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 7.63 7.64 7.43 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 20.62 22.09 19.16 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 28.59 28.60 27.91 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 5.17 5.26 5.09 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 16.45 16.44 16.31 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 5.58 5.57 5.54 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 17.15 17.18 16.83 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 17.95 18.61 16.83 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| ``` | |
| ### Toybrick RV1126 | |
| Specs: [details](https://t.rock-chips.com/en/portal.php?mod=view&aid=26) | |
| - CPU: Quard core ARM Cortex-A7, up to 1.5GHz | |
| - NPU (Not supported by OpenCV): 2.0TOPS, support 8bit / 16bit | |
| CPU: | |
| <!-- config wechat is excluded due to it needs building with opencv_contrib --> | |
| ``` | |
| $ python3 benchmark.py --all --cfg_exclude wechat | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_OPENCV | |
| target=cv.dnn.DNN_TARGET_CPU | |
| mean median min input size model | |
| 56.45 56.29 56.18 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx'] | |
| 48.83 49.41 41.52 [160, 120] YuNet with ['face_detection_yunet_2023mar_int8.onnx'] | |
| 1554.78 1545.63 1523.62 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 1215.44 1251.08 921.26 [150, 150] SFace with ['face_recognition_sface_2021dec_int8.onnx'] | |
| 612.58 613.61 587.83 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 502.02 513.29 399.51 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july_int8.onnx'] | |
| 525.72 532.34 502.00 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 415.87 442.23 318.14 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb_int8.onnx'] | |
| 1631.40 1635.83 1608.43 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 1115.29 1159.60 675.51 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar_int8.onnx'] | |
| 1546.54 1547.64 1516.69 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 1163.10 1227.05 816.99 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 980.56 852.38 689.31 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr_int8.onnx'] | |
| 837.72 778.61 507.03 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr_int8.onnx'] | |
| 11819.74 11778.79 11758.31 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 7742.66 8151.17 4442.93 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan_int8.onnx'] | |
| 3266.08 3250.08 3216.03 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 2260.88 2368.00 1437.58 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar_int8.onnx'] | |
| 2335.65 2342.12 2304.69 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 1903.82 1962.71 1533.79 [416, 416] NanoDet with ['object_detection_nanodet_2022nov_int8.onnx'] | |
| 37604.10 37569.30 37502.48 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 24229.20 25577.94 13483.54 [640, 640] YoloX with ['object_detection_yolox_2022nov_int8.onnx'] | |
| 14860.23 14988.15 14769.91 [1280, 720] DaSiamRPN with ['object_tracking_dasiamrpn_kernel_cls1_2021nov.onnx', 'object_tracking_dasiamrpn_kernel_r1_2021nov.onnx', 'object_tracking_dasiamrpn_model_2021nov.onnx'] | |
| 1133.44 1131.54 1124.83 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 883.96 919.07 655.33 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb_int8.onnx'] | |
| 1430.98 1424.55 1415.68 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 11131.81 11141.37 11080.20 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 7065.00 7461.37 3748.85 [128, 256] YoutuReID with ['person_reid_youtu_2021nov_int8.onnx'] | |
| 790.98 823.19 755.99 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx'] | |
| 49331.32 49285.30 49210.67 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 49327.34 49489.22 49210.67 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| 2183.70 2172.36 2156.29 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx'] | |
| 2225.19 2222.58 2156.29 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx'] | |
| 2214.03 2302.61 2156.29 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx'] | |
| 2203.45 2231.47 2150.19 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2023feb_fp16.onnx'] | |
| 2201.14 2188.00 2150.19 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2023feb_fp16.onnx'] | |
| 2029.28 2178.36 1268.17 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2022oct_int8.onnx'] | |
| 1923.12 2219.63 1268.17 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov_int8.onnx'] | |
| 1818.21 2196.98 1184.98 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx'] | |
| ``` | |
| ### Khadas Edge2 (with RK3588) | |
| Board specs: [details](https://www.khadas.com/edge2) | |
| SoC specs: [details](https://www.rock-chips.com/a/en/products/RK35_Series/2022/0926/1660.html) | |
| - CPU: 2.25GHz Quad Core ARM Cortex-A76 + 1.8GHz Quad Core Cortex-A55 | |
| - NPU (Not supported by OpenCV): Build-in 6 TOPS Performance NPU, triple core, support int4 / int8 / int16 / fp16 / bf16 / tf32 | |
| CPU: | |
| <!-- config wechat is excluded due to it needs building with opencv_contrib --> | |
| ``` | |
| $ python3 benchmark.py --all --cfg_exclude wechat | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_OPENCV | |
| target=cv.dnn.DNN_TARGET_CPU | |
| mean median min input size model | |
| 2.29 2.30 2.25 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx'] | |
| 2.62 2.64 2.25 [160, 120] YuNet with ['face_detection_yunet_2023mar_int8.onnx'] | |
| 28.19 28.12 28.01 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 36.68 37.80 28.01 [150, 150] SFace with ['face_recognition_sface_2021dec_int8.onnx'] | |
| 12.56 12.55 12.50 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 17.28 17.83 12.50 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july_int8.onnx'] | |
| 22.74 22.87 22.43 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 24.56 24.61 22.43 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb_int8.onnx'] | |
| 29.91 30.23 28.16 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 35.54 35.46 28.16 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar_int8.onnx'] | |
| 27.28 27.20 27.20 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 22.91 23.33 19.28 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 27.36 19.46 19.28 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr_int8.onnx'] | |
| 28.28 29.17 19.28 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr_int8.onnx'] | |
| 150.06 150.89 147.05 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 180.91 184.75 147.05 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan_int8.onnx'] | |
| 54.14 52.95 49.31 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 60.01 61.20 49.31 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar_int8.onnx'] | |
| 117.60 128.98 83.33 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 117.28 150.31 83.33 [416, 416] NanoDet with ['object_detection_nanodet_2022nov_int8.onnx'] | |
| 553.58 558.76 535.47 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 594.18 592.64 535.47 [640, 640] YoloX with ['object_detection_yolox_2022nov_int8.onnx'] | |
| 138.82 151.00 113.82 [1280, 720] DaSiamRPN with ['object_tracking_dasiamrpn_kernel_cls1_2021nov.onnx', 'object_tracking_dasiamrpn_kernel_r1_2021nov.onnx', 'object_tracking_dasiamrpn_model_2021nov.onnx'] | |
| 56.35 55.73 55.25 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 57.07 57.19 55.25 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb_int8.onnx'] | |
| 47.94 48.41 47.05 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 146.02 145.89 139.08 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 157.60 158.88 139.08 [128, 256] YoutuReID with ['person_reid_youtu_2021nov_int8.onnx'] | |
| 41.26 42.74 40.08 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx'] | |
| 384.47 401.25 360.71 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 377.91 381.15 336.30 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| 68.70 68.63 68.54 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx'] | |
| 78.17 80.48 68.54 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx'] | |
| 71.42 91.44 61.14 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx'] | |
| 70.07 76.28 61.14 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2023feb_fp16.onnx'] | |
| 67.69 61.72 61.14 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2023feb_fp16.onnx'] | |
| 68.29 65.04 61.14 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2022oct_int8.onnx'] | |
| 69.58 68.63 61.14 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov_int8.onnx'] | |
| 68.99 65.02 61.14 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx'] | |
| ``` | |
| ### Horizon Sunrise X3 PI | |
| Specs: [details_cn](https://developer.horizon.ai/sunrise) | |
| - CPU: ARM Cortex-A53，4xCore, 1.2G | |
| - BPU (aka NPU, not supported by OpenCV): (Bernoulli Arch) 2×Core，up to 1.0G, ~5Tops | |
| CPU: | |
| ``` | |
| $ python3 benchmark.py --all | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_OPENCV | |
| target=cv.dnn.DNN_TARGET_CPU | |
| mean median min input size model | |
| 10.15 10.07 10.04 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx'] | |
| 11.27 11.40 10.04 [160, 120] YuNet with ['face_detection_yunet_2023mar_int8.onnx'] | |
| 116.44 116.29 116.15 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 158.75 164.22 116.15 [150, 150] SFace with ['face_recognition_sface_2021dec_int8.onnx'] | |
| 55.42 55.80 55.27 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 76.04 78.44 55.27 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july_int8.onnx'] | |
| 91.39 95.06 90.66 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 95.54 95.39 90.66 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb_int8.onnx'] | |
| 135.16 134.82 134.75 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 148.05 149.55 134.75 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar_int8.onnx'] | |
| 115.69 115.73 115.38 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 99.37 100.71 85.65 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 111.02 85.94 85.65 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr_int8.onnx'] | |
| 112.94 112.72 85.65 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr_int8.onnx'] | |
| 641.92 643.42 640.64 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 700.42 708.18 640.64 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan_int8.onnx'] | |
| 251.52 250.97 250.36 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 261.00 280.82 250.36 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar_int8.onnx'] | |
| 395.23 398.77 385.68 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 406.28 416.58 385.68 [416, 416] NanoDet with ['object_detection_nanodet_2022nov_int8.onnx'] | |
| 2608.90 2612.42 2597.93 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 2609.88 2609.39 2597.93 [640, 640] YoloX with ['object_detection_yolox_2022nov_int8.onnx'] | |
| 809.55 814.66 794.67 [1280, 720] DaSiamRPN with ['object_tracking_dasiamrpn_kernel_cls1_2021nov.onnx', 'object_tracking_dasiamrpn_kernel_r1_2021nov.onnx', 'object_tracking_dasiamrpn_model_2021nov.onnx'] | |
| 228.95 228.74 228.35 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 227.97 228.61 226.76 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb_int8.onnx'] | |
| 192.29 192.26 191.74 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 660.62 662.28 659.49 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 646.25 647.89 631.03 [128, 256] YoutuReID with ['person_reid_youtu_2021nov_int8.onnx'] | |
| 182.57 185.52 179.71 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx'] | |
| 9.93 9.97 9.82 [100, 100] WeChatQRCode with ['detect_2021nov.prototxt', 'detect_2021nov.caffemodel', 'sr_2021nov.prototxt', 'sr_2021nov.caffemodel'] | |
| 1914.15 1913.70 1902.25 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 1920.07 1929.80 1902.25 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| 439.96 441.91 436.49 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx'] | |
| 465.56 466.86 436.49 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx'] | |
| 431.93 495.94 373.61 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx'] | |
| 432.47 435.40 373.61 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2023feb_fp16.onnx'] | |
| 418.75 375.76 373.61 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2023feb_fp16.onnx'] | |
| 421.81 410.25 373.61 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2022oct_int8.onnx'] | |
| 429.30 437.71 373.61 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov_int8.onnx'] | |
| 422.15 406.50 373.61 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx'] | |
| ``` | |
| ### MAIX-III AX-PI | |
| Specs: [details_en](https://wiki.sipeed.com/hardware/en/maixIII/ax-pi/axpi.html#Hardware), [details_cn](https://wiki.sipeed.com/hardware/zh/maixIII/ax-pi/axpi.html#%E7%A1%AC%E4%BB%B6%E5%8F%82%E6%95%B0) | |
| SoC specs: [details_cn](https://axera-tech.com/product/T7297367876123493768) | |
| - CPU: Quad cores ARM Cortex-A7 | |
| - NPU (Not supported by OpenCV): 14.4Tops@int4，3.6Tops@int8 | |
| CPU: | |
| <!-- config wechat is excluded due to it needs building with opencv_contrib --> | |
| ``` | |
| $ python3 benchmark.py --all --cfg_exclude wechat | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_OPENCV | |
| target=cv.dnn.DNN_TARGET_CPU | |
| mean median min input size model | |
| 83.67 83.60 83.50 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx'] | |
| 76.45 77.17 70.53 [160, 120] YuNet with ['face_detection_yunet_2023mar_int8.onnx'] | |
| 2102.93 2102.75 2102.23 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 1846.25 1872.36 1639.46 [150, 150] SFace with ['face_recognition_sface_2021dec_int8.onnx'] | |
| 825.27 825.74 824.83 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 752.57 759.68 693.90 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july_int8.onnx'] | |
| 742.35 742.87 741.42 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 630.16 641.82 539.73 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb_int8.onnx'] | |
| 2190.53 2188.01 2187.75 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 1662.81 1712.08 1235.22 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar_int8.onnx'] | |
| 2099.43 2099.39 2098.89 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 1589.86 1641.45 1181.62 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 1451.24 1182.16 1181.62 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr_int8.onnx'] | |
| 1277.21 1224.66 888.62 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr_int8.onnx'] | |
| 15832.31 15832.41 15830.59 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 11649.30 12067.68 8300.79 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan_int8.onnx'] | |
| 4376.55 4398.44 4371.68 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 3376.78 3480.89 2574.72 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar_int8.onnx'] | |
| 3422.70 3414.45 3413.72 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 3002.36 3047.94 2655.38 [416, 416] NanoDet with ['object_detection_nanodet_2022nov_int8.onnx'] | |
| 50678.08 50651.82 50651.19 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 36249.71 37771.22 24606.37 [640, 640] YoloX with ['object_detection_yolox_2022nov_int8.onnx'] | |
| 19974.99 19984.80 19948.63 [1280, 720] DaSiamRPN with ['object_tracking_dasiamrpn_kernel_cls1_2021nov.onnx', 'object_tracking_dasiamrpn_kernel_r1_2021nov.onnx', 'object_tracking_dasiamrpn_model_2021nov.onnx'] | |
| 1502.15 1501.98 1500.99 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 1300.15 1320.44 1137.60 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb_int8.onnx'] | |
| 1993.05 1993.98 1991.86 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 14925.56 14926.90 14912.28 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 10507.96 10944.15 6974.74 [128, 256] YoutuReID with ['person_reid_youtu_2021nov_int8.onnx'] | |
| 1113.51 1124.83 1106.81 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx'] | |
| 66015.47 65997.60 65993.81 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 66023.14 66034.99 65993.81 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| 3230.93 3228.61 3228.29 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx'] | |
| 3312.02 3323.17 3228.29 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx'] | |
| 3262.32 3413.03 3182.11 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx'] | |
| 3250.66 3298.06 3182.11 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2023feb_fp16.onnx'] | |
| 3231.37 3185.37 3179.37 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2023feb_fp16.onnx'] | |
| 3064.17 3213.91 2345.80 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2022oct_int8.onnx'] | |
| 2975.21 3227.38 2345.80 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov_int8.onnx'] | |
| 2862.33 3212.57 2205.48 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx'] | |
| ``` | |
| ### StarFive VisionFive 2 | |
| Specs: [details_cn](https://doc.rvspace.org/VisionFive2/PB/VisionFive_2/specification_pb.html), [details_en](https://doc-en.rvspace.org/VisionFive2/Product_Brief/VisionFive_2/specification_pb.html) | |
| - CPU: StarFive JH7110 with RISC-V quad-core CPU with 2 MB L2 cache and a monitor core, supporting RV64GC ISA, working up to 1.5 GHz | |
| - GPU: IMG BXE-4-32 MC1 with work frequency up to 600 MHz | |
| CPU: | |
| <!-- config wechat is excluded due to it needs building with opencv_contrib --> | |
| <!-- config dasiam is excluded due to opencv cannot find ffmpeg and its components --> | |
| ``` | |
| $ python3 benchmark.py --all --cfg_exclude wechat:dasiam | |
| Benchmarking ... | |
| backend=cv.dnn.DNN_BACKEND_OPENCV | |
| target=cv.dnn.DNN_TARGET_CPU | |
| mean median min input size model | |
| 41.10 41.09 41.04 [160, 120] YuNet with ['face_detection_yunet_2023mar.onnx'] | |
| 35.87 36.37 31.62 [160, 120] YuNet with ['face_detection_yunet_2023mar_int8.onnx'] | |
| 1050.45 1050.38 1050.01 [150, 150] SFace with ['face_recognition_sface_2021dec.onnx'] | |
| 832.25 854.08 657.41 [150, 150] SFace with ['face_recognition_sface_2021dec_int8.onnx'] | |
| 425.36 425.42 425.19 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july.onnx'] | |
| 351.86 372.26 292.72 [112, 112] FacialExpressionRecog with ['facial_expression_recognition_mobilefacenet_2022july_int8.onnx'] | |
| 348.67 347.98 347.67 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb.onnx'] | |
| 290.95 297.03 243.79 [224, 224] MPHandPose with ['handpose_estimation_mediapipe_2023feb_int8.onnx'] | |
| 1135.09 1135.25 1134.72 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar.onnx'] | |
| 788.33 822.69 509.67 [192, 192] PPHumanSeg with ['human_segmentation_pphumanseg_2023mar_int8.onnx'] | |
| 1065.61 1065.99 1065.30 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr.onnx'] | |
| 805.26 830.66 595.78 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr.onnx'] | |
| 687.98 609.35 514.14 [224, 224] MobileNet with ['image_classification_mobilenetv1_2022apr_int8.onnx'] | |
| 592.59 555.25 381.33 [224, 224] MobileNet with ['image_classification_mobilenetv2_2022apr_int8.onnx'] | |
| 8091.50 8090.44 8088.72 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan.onnx'] | |
| 5394.46 5666.14 3235.23 [224, 224] PPResNet with ['image_classification_ppresnet50_2022jan_int8.onnx'] | |
| 2270.14 2270.29 2267.51 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar.onnx'] | |
| 1584.83 1656.13 1033.23 [320, 240] LPD_YuNet with ['license_plate_detection_lpd_yunet_2023mar_int8.onnx'] | |
| 1732.53 1732.14 1731.47 [416, 416] NanoDet with ['object_detection_nanodet_2022nov.onnx'] | |
| 1434.56 1463.32 1194.57 [416, 416] NanoDet with ['object_detection_nanodet_2022nov_int8.onnx'] | |
| 26172.62 26160.04 26151.67 [640, 640] YoloX with ['object_detection_yolox_2022nov.onnx'] | |
| 17004.06 17909.88 9659.54 [640, 640] YoloX with ['object_detection_yolox_2022nov_int8.onnx'] | |
| 734.97 735.58 733.95 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb.onnx'] | |
| 609.61 621.69 508.04 [192, 192] MPPalmDet with ['palm_detection_mediapipe_2023feb_int8.onnx'] | |
| 961.41 962.26 960.39 [224, 224] MPPersonDet with ['person_detection_mediapipe_2023mar.onnx'] | |
| 7594.21 7590.75 7589.16 [128, 256] YoutuReID with ['person_reid_youtu_2021nov.onnx'] | |
| 4884.04 5154.38 2715.94 [128, 256] YoutuReID with ['person_reid_youtu_2021nov_int8.onnx'] | |
| 548.41 550.86 546.09 [256, 256] MPPose with ['pose_estimation_mediapipe_2023mar.onnx'] | |
| 34074.19 34077.97 34058.43 [640, 480] DB with ['text_detection_DB_IC15_resnet18_2021sep.onnx'] | |
| 34073.67 34069.82 34054.29 [640, 480] DB with ['text_detection_DB_TD500_resnet18_2021sep.onnx'] | |
| 1397.09 1396.95 1396.74 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2021sep.onnx'] | |
| 1428.65 1432.59 1396.74 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov.onnx'] | |
| 1429.56 1467.34 1396.74 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2021sep.onnx'] | |
| 1419.29 1450.55 1395.55 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2023feb_fp16.onnx'] | |
| 1421.72 1434.46 1395.55 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2023feb_fp16.onnx'] | |
| 1307.27 1415.63 807.66 [1280, 720] CRNN with ['text_recognition_CRNN_CH_2022oct_int8.onnx'] | |
| 1237.00 1395.68 807.66 [1280, 720] CRNN with ['text_recognition_CRNN_CN_2021nov_int8.onnx'] | |
| 1169.59 1415.29 774.09 [1280, 720] CRNN with ['text_recognition_CRNN_EN_2022oct_int8.onnx'] | |
| ``` | |