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Inference Speed

We summarize the model complexity and inference speed of major models in MMPose, including FLOPs, parameter counts and inference speeds on both CPU and GPU devices with different batch sizes. We also compare the mAP of different models on COCO human keypoint dataset, showing the trade-off between model performance and model complexity.

Comparison Rules

To ensure the fairness of the comparison, the comparison experiments are conducted under the same hardware and software environment using the same dataset. We also list the mAP (mean average precision) on COCO human keypoint dataset of the models along with the corresponding config files.

For model complexity information measurement, we calculate the FLOPs and parameter counts of a model with corresponding input shape. Note that some layers or ops are currently not supported, for example, DeformConv2d, so you may need to check if all ops are supported and verify that the flops and parameter counts computation is correct.

For inference speed, we omit the time for data pre-processing and only measure the time for model forwarding and data post-processing. For each model setting, we keep the same data pre-processing methods to make sure the same feature input. We measure the inference speed on both CPU and GPU devices. For topdown heatmap models, we also test the case when the batch size is larger, e.g., 10, to test model performance in crowded scenes.

The inference speed is measured with frames per second (FPS), namely the average iterations per second, which can show how fast the model can handle an input. The higher, the faster, the better.

Hardware

  • GPU: GeForce GTX 1660 SUPER

  • CPU: Intel(R) Core(TM) i7-8700 CPU @ 3.20GHz

Software Environment

  • Ubuntu 16.04

  • Python 3.8

  • PyTorch 1.10

  • CUDA 10.2

  • mmcv-full 1.3.17

  • mmpose 0.20.0

Model complexity information and inference speed results of major models in MMPose

Algorithm Model config Input size mAP Flops (GFLOPs) Params (M) GPU Inference Speed
(FPS)1
GPU Inference Speed
(FPS, bs=10)2
CPU Inference Speed
(FPS)
CPU Inference Speed
(FPS, bs=10)
topdown_heatmap Alexnet config (3, 192, 256) 0.397 1.42 5.62 229.21 ± 16.91 33.52 ± 1.14 13.92 ± 0.60 1.38 ± 0.02
topdown_heatmap CPM config (3, 192, 256) 0.623 63.81 31.3 11.35 ± 0.22 3.87 ± 0.07 0.31 ± 0.01 0.03 ± 0.00
topdown_heatmap CPM config (3, 288, 384) 0.65 143.57 31.3 7.09 ± 0.14 2.10 ± 0.05 0.14 ± 0.00 0.01 ± 0.00
topdown_heatmap Hourglass-52 config (3, 256, 256) 0.726 28.67 94.85 25.50 ± 1.68 3.99 ± 0.07 0.92 ± 0.03 0.09 ± 0.00
topdown_heatmap Hourglass-52 config (3, 384, 384) 0.746 64.5 94.85 14.74 ± 0.8 1.86 ± 0.06 0.43 ± 0.03 0.04 ± 0.00
topdown_heatmap HRNet-W32 config (3, 192, 256) 0.746 7.7 28.54 22.73 ± 1.12 6.60 ± 0.14 2.73 ± 0.11 0.32 ± 0.00
topdown_heatmap HRNet-W32 config (3, 288, 384) 0.76 17.33 28.54 22.78 ± 1.21 3.28 ± 0.08 1.35 ± 0.05 0.14 ± 0.00
topdown_heatmap HRNet-W48 config (3, 192, 256) 0.756 15.77 63.6 22.01 ± 1.10 3.74 ± 0.10 1.46 ± 0.05 0.16 ± 0.00
topdown_heatmap HRNet-W48 config (3, 288, 384) 0.767 35.48 63.6 15.03 ± 1.03 1.80 ± 0.03 0.68 ± 0.02 0.07 ± 0.00
topdown_heatmap LiteHRNet-30 config (3, 192, 256) 0.675 0.42 1.76 11.86 ± 0.38 9.77 ± 0.23 5.84 ± 0.39 0.80 ± 0.00
topdown_heatmap LiteHRNet-30 config (3, 288, 384) 0.7 0.95 1.76 11.52 ± 0.39 5.18 ± 0.11 3.45 ± 0.22 0.37 ± 0.00
topdown_heatmap MobilenetV2 config (3, 192, 256) 0.646 1.59 9.57 91.82 ± 10.98 17.85 ± 0.32 10.44 ± 0.80 1.05 ± 0.01
topdown_heatmap MobilenetV2 config (3, 288, 384) 0.673 3.57 9.57 71.27 ± 6.82 8.00 ± 0.15 5.01 ± 0.32 0.46 ± 0.00
topdown_heatmap MSPN-50 config (3, 192, 256) 0.723 5.11 25.11 59.65 ± 3.74 9.51 ± 0.15 3.98 ± 0.21 0.43 ± 0.00
topdown_heatmap 2xMSPN-50 config (3, 192, 256) 0.754 11.35 56.8 30.64 ± 2.61 4.74 ± 0.12 1.85 ± 0.08 0.20 ± 0.00
topdown_heatmap 3xMSPN-50 config (3, 192, 256) 0.758 17.59 88.49 20.90 ± 1.82 3.22 ± 0.08 1.23 ± 0.04 0.13 ± 0.00
topdown_heatmap 4xMSPN-50 config (3, 192, 256) 0.764 23.82 120.18 15.79 ± 1.14 2.45 ± 0.05 0.90 ± 0.03 0.10 ± 0.00
topdown_heatmap ResNest-50 config (3, 192, 256) 0.721 6.73 35.93 48.36 ± 4.12 7.48 ± 0.13 3.00 ± 0.13 0.33 ± 0.00
topdown_heatmap ResNest-50 config (3, 288, 384) 0.737 15.14 35.93 30.30 ± 2.30 3.62 ± 0.09 1.43 ± 0.05 0.13 ± 0.00
topdown_heatmap ResNest-101 config (3, 192, 256) 0.725 10.38 56.61 29.21 ± 1.98 5.30 ± 0.12 2.01 ± 0.08 0.22 ± 0.00
topdown_heatmap ResNest-101 config (3, 288, 384) 0.746 23.36 56.61 19.02 ± 1.40 2.59 ± 0.05 0.97 ± 0.03 0.09 ± 0.00
topdown_heatmap ResNest-200 config (3, 192, 256) 0.732 17.5 78.54 16.11 ± 0.71 3.29 ± 0.07 1.33 ± 0.02 0.14 ± 0.00
topdown_heatmap ResNest-200 config (3, 288, 384) 0.754 39.37 78.54 11.48 ± 0.68 1.58 ± 0.02 0.63 ± 0.01 0.06 ± 0.00
topdown_heatmap ResNest-269 config (3, 192, 256) 0.738 22.45 119.27 12.02 ± 0.47 2.60 ± 0.05 1.03 ± 0.01 0.11 ± 0.00
topdown_heatmap ResNest-269 config (3, 288, 384) 0.755 50.5 119.27 8.82 ± 0.42 1.24 ± 0.02 0.49 ± 0.01 0.05 ± 0.00
topdown_heatmap ResNet-50 config (3, 192, 256) 0.718 5.46 34 64.23 ± 6.05 9.33 ± 0.21 4.00 ± 0.10 0.41 ± 0.00
topdown_heatmap ResNet-50 config (3, 288, 384) 0.731 12.29 34 36.78 ± 3.05 4.48 ± 0.12 1.92 ± 0.04 0.19 ± 0.00
topdown_heatmap ResNet-101 config (3, 192, 256) 0.726 9.11 52.99 43.35 ± 4.36 6.44 ± 0.14 2.57 ± 0.05 0.27 ± 0.00
topdown_heatmap ResNet-101 config (3, 288, 384) 0.748 20.5 52.99 23.29 ± 1.83 3.12 ± 0.09 1.23 ± 0.03 0.11 ± 0.00
topdown_heatmap ResNet-152 config (3, 192, 256) 0.735 12.77 68.64 32.31 ± 2.84 4.88 ± 0.17 1.89 ± 0.03 0.20 ± 0.00
topdown_heatmap ResNet-152 config (3, 288, 384) 0.75 28.73 68.64 17.32 ± 1.17 2.40 ± 0.04 0.91 ± 0.01 0.08 ± 0.00
topdown_heatmap ResNetV1d-50 config (3, 192, 256) 0.722 5.7 34.02 63.44 ± 6.09 9.09 ± 0.10 3.82 ± 0.10 0.39 ± 0.00
topdown_heatmap ResNetV1d-50 config (3, 288, 384) 0.73 12.82 34.02 36.21 ± 3.10 4.30 ± 0.12 1.82 ± 0.04 0.16 ± 0.00
topdown_heatmap ResNetV1d-101 config (3, 192, 256) 0.731 9.35 53.01 41.48 ± 3.76 6.33 ± 0.15 2.48 ± 0.05 0.26 ± 0.00
topdown_heatmap ResNetV1d-101 config (3, 288, 384) 0.748 21.04 53.01 23.49 ± 1.76 3.07 ± 0.07 1.19 ± 0.02 0.11 ± 0.00
topdown_heatmap ResNetV1d-152 config (3, 192, 256) 0.737 13.01 68.65 31.96 ± 2.87 4.69 ± 0.18 1.87 ± 0.02 0.19 ± 0.00
topdown_heatmap ResNetV1d-152 config (3, 288, 384) 0.752 29.26 68.65 17.31 ± 1.13 2.32 ± 0.04 0.88 ± 0.01 0.08 ± 0.00
topdown_heatmap ResNext-50 config (3, 192, 256) 0.714 5.61 33.47 48.34 ± 3.85 7.66 ± 0.13 3.71 ± 0.10 0.37 ± 0.00
topdown_heatmap ResNext-50 config (3, 288, 384) 0.724 12.62 33.47 30.66 ± 2.38 3.64 ± 0.11 1.73 ± 0.03 0.15 ± 0.00
topdown_heatmap ResNext-101 config (3, 192, 256) 0.726 9.29 52.62 27.33 ± 2.35 5.09 ± 0.13 2.45 ± 0.04 0.25 ± 0.00
topdown_heatmap ResNext-101 config (3, 288, 384) 0.743 20.91 52.62 18.19 ± 1.38 2.42 ± 0.04 1.15 ± 0.01 0.10 ± 0.00
topdown_heatmap ResNext-152 config (3, 192, 256) 0.73 12.98 68.39 19.61 ± 1.61 3.80 ± 0.13 1.83 ± 0.02 0.18 ± 0.00
topdown_heatmap ResNext-152 config (3, 288, 384) 0.742 29.21 68.39 13.14 ± 0.75 1.82 ± 0.03 0.85 ± 0.01 0.08 ± 0.00
topdown_heatmap RSN-18 config (3, 192, 256) 0.704 2.27 9.14 47.80 ± 4.50 13.68 ± 0.25 6.70 ± 0.28 0.70 ± 0.00
topdown_heatmap RSN-50 config (3, 192, 256) 0.723 4.11 19.33 27.22 ± 1.61 8.81 ± 0.13 3.98 ± 0.12 0.45 ± 0.00
topdown_heatmap 2xRSN-50 config (3, 192, 256) 0.745 8.29 39.26 13.88 ± 0.64 4.78 ± 0.13 2.02 ± 0.04 0.23 ± 0.00
topdown_heatmap 3xRSN-50 config (3, 192, 256) 0.75 12.47 59.2 9.40 ± 0.32 3.37 ± 0.09 1.34 ± 0.03 0.15 ± 0.00
topdown_heatmap SCNet-50 config (3, 192, 256) 0.728 5.31 34.01 40.76 ± 3.08 8.35 ± 0.19 3.82 ± 0.08 0.40 ± 0.00
topdown_heatmap SCNet-50 config (3, 288, 384) 0.751 11.94 34.01 32.61 ± 2.97 4.19 ± 0.10 1.85 ± 0.03 0.17 ± 0.00
topdown_heatmap SCNet-101 config (3, 192, 256) 0.733 8.51 53.01 24.28 ± 1.19 5.80 ± 0.13 2.49 ± 0.05 0.27 ± 0.00
topdown_heatmap SCNet-101 config (3, 288, 384) 0.752 19.14 53.01 20.43 ± 1.76 2.91 ± 0.06 1.23 ± 0.02 0.12 ± 0.00
topdown_heatmap SeresNet-50 config (3, 192, 256) 0.728 5.47 36.53 54.83 ± 4.94 8.80 ± 0.12 3.85 ± 0.10 0.40 ± 0.00
topdown_heatmap SeresNet-50 config (3, 288, 384) 0.748 12.3 36.53 33.00 ± 2.67 4.26 ± 0.12 1.86 ± 0.04 0.17 ± 0.00
topdown_heatmap SeresNet-101 config (3, 192, 256) 0.734 9.13 57.77 33.90 ± 2.65 6.01 ± 0.13 2.48 ± 0.05 0.26 ± 0.00
topdown_heatmap SeresNet-101 config (3, 288, 384) 0.753 20.53 57.77 20.57 ± 1.57 2.96 ± 0.07 1.20 ± 0.02 0.11 ± 0.00
topdown_heatmap SeresNet-152 config (3, 192, 256) 0.73 12.79 75.26 24.25 ± 1.95 4.45 ± 0.10 1.82 ± 0.02 0.19 ± 0.00
topdown_heatmap SeresNet-152 config (3, 288, 384) 0.753 28.76 75.26 15.11 ± 0.99 2.25 ± 0.04 0.88 ± 0.01 0.08 ± 0.00
topdown_heatmap ShuffleNetV1 config (3, 192, 256) 0.585 1.35 6.94 80.79 ± 8.95 21.91 ± 0.46 11.84 ± 0.59 1.25 ± 0.01
topdown_heatmap ShuffleNetV1 config (3, 288, 384) 0.622 3.05 6.94 63.45 ± 5.21 9.84 ± 0.10 6.01 ± 0.31 0.57 ± 0.00
topdown_heatmap ShuffleNetV2 config (3, 192, 256) 0.599 1.37 7.55 82.36 ± 7.30 22.68 ± 0.53 12.40 ± 0.66 1.34 ± 0.02
topdown_heatmap ShuffleNetV2 config (3, 288, 384) 0.636 3.08 7.55 63.63 ± 5.72 10.47 ± 0.16 6.32 ± 0.28 0.63 ± 0.01
topdown_heatmap VGG16 config (3, 192, 256) 0.698 16.22 18.92 51.91 ± 2.98 6.18 ± 0.13 1.64 ± 0.03 0.15 ± 0.00
topdown_heatmap VIPNAS + ResNet-50 config (3, 192, 256) 0.711 1.49 7.29 34.88 ± 2.45 10.29 ± 0.13 6.51 ± 0.17 0.65 ± 0.00
topdown_heatmap VIPNAS + MobileNetV3 config (3, 192, 256) 0.7 0.76 5.9 53.62 ± 6.59 11.54 ± 0.18 1.26 ± 0.02 0.13 ± 0.00
Associative Embedding HigherHRNet-W32 config (3, 512, 512) 0.677 46.58 28.65 7.80 ± 0.67 / 0.28 ± 0.02 /
Associative Embedding HigherHRNet-W32 config (3, 640, 640) 0.686 72.77 28.65 5.30 ± 0.37 / 0.17 ± 0.01 /
Associative Embedding HigherHRNet-W48 config (3, 512, 512) 0.686 96.17 63.83 4.55 ± 0.35 / 0.15 ± 0.01 /
Associative Embedding Hourglass-AE config (3, 512, 512) 0.613 221.58 138.86 3.55 ± 0.24 / 0.08 ± 0.00 /
Associative Embedding HRNet-W32 config (3, 512, 512) 0.654 41.1 28.54 8.93 ± 0.76 / 0.33 ± 0.02 /
Associative Embedding HRNet-W48 config (3, 512, 512) 0.665 84.12 63.6 5.27 ± 0.43 / 0.18 ± 0.01 /
Associative Embedding MobilenetV2 config (3, 512, 512) 0.38 8.54 9.57 21.24 ± 1.34 / 0.81 ± 0.06 /
Associative Embedding ResNet-50 config (3, 512, 512) 0.466 29.2 34 11.71 ± 0.97 / 0.41 ± 0.02 /
Associative Embedding ResNet-50 config (3, 640, 640) 0.479 45.62 34 8.20 ± 0.58 / 0.26 ± 0.02 /
Associative Embedding ResNet-101 config (3, 512, 512) 0.554 48.67 53 8.26 ± 0.68 / 0.28 ± 0.02 /
Associative Embedding ResNet-101 config (3, 512, 512) 0.595 68.17 68.64 6.25 ± 0.53 / 0.21 ± 0.01 /
DeepPose ResNet-50 config (3, 192, 256) 0.526 4.04 23.58 82.20 ± 7.54 / 5.50 ± 0.18 /
DeepPose ResNet-101 config (3, 192, 256) 0.56 7.69 42.57 48.93 ± 4.02 / 3.10 ± 0.07 /
DeepPose ResNet-152 config (3, 192, 256) 0.583 11.34 58.21 35.06 ± 3.50 / 2.19 ± 0.04 /

1 Note that we run multiple iterations and record the time of each iteration, and the mean and standard deviation value of FPS are both shown.

2 The FPS is defined as the average iterations per second, regardless of the batch size in this iteration.

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