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@@ -6,48 +6,56 @@
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| 模型 | 模型大小 | 预测速度（毫秒） | Top1准确率（%） | Top5准确率（%） |
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| :----| :------- | :----------- | :--------- | :--------- |
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-| ResNet18| 46.9MB | - | 71.0 | 89.9 |
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-| ResNet34| 87.5MB | - | 74.6 | 92.1 |
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-| ResNet50| 102.7MB | - | 76.5 | 93.0 |
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-| ResNet101 |179.1MB | - | 77.6 | 93.6 |
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-| ResNet50_vd |102.8MB |- | 79.1 | 94.4 |
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-| ResNet101_vd| 179.2MB | - | 80.2 | 95.0 |
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-| ResNet50_vd_ssld |102.8MB | - | 82.4 | 96.1 |
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-| ResNet101_vd_ssld| 179.2MB | - | 83.7 | 96.7 |
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-| DarkNet53|166.9MB | - | 78.0 | 94.1 |
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-| MobileNetV1 | 16.0MB | - | 71.0 | 89.7 |
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-| MobileNetV2 | 14.0MB | - | 72.2 | 90.7 |
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-| MobileNetV3_large| 21.0MB | - | 75.3 | 93.2 |
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-| MobileNetV3_small | 12.0MB | - | 68.2 | 88.1 |
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-| MobileNetV3_large_ssld| 21.0MB | - | 79.0 | 94.5 |
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-| MobileNetV3_small_ssld | 12.0MB | - | 71.3 | 90.1 |
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-| Xception41 |92.4MB | - | 79.6 | 94.4 |
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-| Xception65 | 144.6MB | - | 80.3 | 94.5 |
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-| DenseNet121 | 32.8MB | - | 75.7 | 92.6 |
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-| DenseNet161|116.3MB | - | 78.6 | 94.1 |
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-| DenseNet201| 84.6MB | - | 77.6 | 93.7 |
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-| ShuffleNetV2 | 9.0MB | - | 68.8 | 88.5 |
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-| HRNet_W18 | 21.29MB | - | 76.9 | 93.4 |
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+| ResNet18| 46.2MB | 3.72882 | 71.0 | 89.9 |
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+| ResNet34| 87.9MB | 5.50876 | 74.6 | 92.1 |
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+| ResNet50| 103.4MB | 7.76659 | 76.5 | 93.0 |
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+| ResNet101 |180.4MB | 13.80876 | 77.6 | 93.6 |
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+| ResNet50_vd |103.5MB | 8.20476 | 79.1 | 94.4 |
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+| ResNet101_vd| 180.5MB | 14.24643 | 80.2 | 95.0 |
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+| ResNet50_vd_ssld |103.5MB | 7.79264 | 82.4 | 96.1 |
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+| ResNet101_vd_ssld| 180.5MB | 13.34580 | 83.7 | 96.7 |
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+| DarkNet53|167.4MB | 8.82047 | 78.0 | 94.1 |
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+| MobileNetV1 | 17.4MB | 3.42838 | 71.0 | 89.7 |
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+| MobileNetV2 | 15.0MB | 5.92667 | 72.2 | 90.7 |
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+| MobileNetV3_large| 22.8MB | 8.31428 | 75.3 | 93.2 |
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+| MobileNetV3_small | 12.5MB | 7.30689 | 68.2 | 88.1 |
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+| MobileNetV3_large_ssld| 22.8MB | 8.06651 | 79.0 | 94.5 |
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+| MobileNetV3_small_ssld | 12.5MB | 7.08837 | 71.3 | 90.1 |
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+| Xception41 | 109.2MB | 8.15611 | 79.6 | 94.4 |
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+| Xception65 | 161.6MB | 13.87017 | 80.3 | 94.5 |
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+| DenseNet121 | 33.1MB | 17.09874 | 75.7 | 92.6 |
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+| DenseNet161| 118.0MB | 22.79690 | 78.6 | 94.1 |
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+| DenseNet201| 84.1MB | 25.26089 | 77.6 | 93.7 |
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+| ShuffleNetV2 | 10.2MB | 15.40138 | 68.8 | 88.5 |
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+| HRNet_W18 | 21.29MB | | 45.25514 | 93.4 |
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## 目标检测模型
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-> 表中模型相关指标均为在MSCOCO数据集上使用PaddlePaddle Python预测接口测试得到（测试GPU型号为Nvidia Tesla V100测试得到,表中符号`-`表示相关指标暂未测试。
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+> 表中模型相关指标均为在MSCOCO数据集上使用PaddlePaddle Python预测接口测试得到（测试GPU型号为Nvidia Tesla P40测试得到,表中符号`-`表示相关指标暂未测试。
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| 模型 | 模型大小 | 预测时间(毫秒) | BoxAP（%） |
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|:-------|:-----------|:-------------|:----------|
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-|FasterRCNN-ResNet50|135.6MB| 78.450 | 35.2 |
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-|FasterRCNN-ResNet50_vd| 135.7MB | 79.523 | 36.4 |
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-|FasterRCNN-ResNet101| 211.7MB | 107.342 | 38.3 |
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-|FasterRCNN-ResNet50-FPN| 167.2MB | 44.897 | 37.2 |
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-|FasterRCNN-ResNet50_vd-FPN|168.7MB | 45.773 | 38.9 |
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-|FasterRCNN-ResNet101-FPN| 251.7MB | 55.782 | 38.7 |
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-|FasterRCNN-ResNet101_vd-FPN |252MB | 58.785 | 40.5 |
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-|FasterRCNN-HRNet_W18-FPN |115.5MB | 57.11 | 36 |
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-|YOLOv3-DarkNet53|252.4MB | 21.944 | 38.9 |
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-|YOLOv3-MobileNetv1 |101.2MB | 12.771 | 29.3 |
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-|YOLOv3-MobileNetv3|94.6MB | - | 31.6 |
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-| YOLOv3-ResNet34|169.7MB | 15.784 | 36.2 |
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+|FasterRCNN-ResNet50|136.0MB| 316.912 | 35.2 |
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+|FasterRCNN-ResNet50_vd| 136.1MB | 302.495 | 36.4 |
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+|FasterRCNN-ResNet101| 212.5MB | 339.153 | 38.3 |
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+|FasterRCNN-ResNet50-FPN| 167.7MB | 44.897 | 37.2 |
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+|FasterRCNN-ResNet50_vd-FPN|167.8MB | 73.219 | 38.9 |
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+|FasterRCNN-ResNet101-FPN| 244.2MB | 93.236 | 38.7 |
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+|FasterRCNN-ResNet101_vd-FPN |244.3MB | 96.424 | 40.5 |
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+|FasterRCNN-HRNet_W18-FPN |115.5MB | 81.592 | 36 |
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+|YOLOv3-DarkNet53|249.2MB | 320.738 | 38.9 |
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+|YOLOv3-MobileNetV1 |99.2MB | 349.461 | 29.3 |
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+|YOLOv3-MobileNetV3_large|100.7MB | 480.075 | 31.6 |
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+| YOLOv3-ResNet34|170.3MB | 417.680 | 36.2 |
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## 实例分割模型
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> 表中模型相关指标均为在MSCOCO数据集上测试得到。
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+| 模型 | 模型大小 | 预测时间(毫秒) | mIoU（%） |
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+|:-------|:-----------|:-------------|:----------|
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+|DeepLabv3+-MobileNetV2_x1.0|-| - | - |
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+|DeepLabv3+-Xception41|-| - | - |
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+|DeepLabv3+-Xception65|-| - | - |
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+|UNet|-| - | - |
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+|HRNet_w18|-| - | - |
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sunyanfang01