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glenn-jocher commited on Dec 23, 2020

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Update README.md (#1764)

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@@ -18,16 +18,14 @@ This repository represents Ultralytics open-source research into future object d
 ## Pretrained Checkpoints
-| Model | AP<sup>val</sup> | AP<sup>test</sup> | AP<sub>50</sub> | Speed<sub>GPU</sub> | FPS<sub>GPU</sub> || params | FLOPS |
 |---------- |------ |------ |------ | -------- | ------| ------ |------  |  :------: |
-| [YOLOv5s](https://github.com/ultralytics/yolov5/releases)    | 37.0     | 37.0     | 56.2     | **2.4ms** | **416** || 7.5M   | 13.2B
-| [YOLOv5m](https://github.com/ultralytics/yolov5/releases)    | 44.3     | 44.3     | 63.2     | 3.4ms     | 294     || 21.8M  | 39.4B
-| [YOLOv5l](https://github.com/ultralytics/yolov5/releases)    | 47.7     | 47.7     | 66.5     | 4.4ms     | 227     || 47.8M  | 88.1B
-| [YOLOv5x](https://github.com/ultralytics/yolov5/releases)    | **49.2** | **49.2** | **67.7** | 6.9ms     | 145     || 89.0M  | 166.4B
 | | | | | | || |
-| [YOLOv5x](https://github.com/ultralytics/yolov5/releases) + TTA|**50.8**| **50.8** | **68.9** | 25.5ms    | 39      || 89.0M  | 354.3B
-| | | | | | || |
-| [YOLOv3-SPP](https://github.com/ultralytics/yolov5/releases) | 45.6     | 45.5     | 65.2     | 4.5ms     | 222     || 63.0M  | 118.0B
 ** AP<sup>test</sup> denotes COCO [test-dev2017](http://cocodataset.org/#upload) server results, all other AP results denote val2017 accuracy.
 ** All AP numbers are for single-model single-scale without ensemble or TTA. **Reproduce mAP** by `python test.py --data coco.yaml --img 640 --conf 0.001 --iou 0.65`

 ## Pretrained Checkpoints
+| Model | AP<sup>val</sup> | AP<sup>test</sup> | AP<sub>50</sub> | Speed<sub>GPU</sub> | FPS<sub>GPU</sub> || params | GFLOPS |
 |---------- |------ |------ |------ | -------- | ------| ------ |------  |  :------: |
+| [YOLOv5s](https://github.com/ultralytics/yolov5/releases)    | 37.0     | 37.0     | 56.2     | **2.4ms** | **416** || 7.5M   | 17.5
+| [YOLOv5m](https://github.com/ultralytics/yolov5/releases)    | 44.3     | 44.3     | 63.2     | 3.4ms     | 294     || 21.8M  | 52.3
+| [YOLOv5l](https://github.com/ultralytics/yolov5/releases)    | 47.7     | 47.7     | 66.5     | 4.4ms     | 227     || 47.8M  | 117.2
+| [YOLOv5x](https://github.com/ultralytics/yolov5/releases)    | **49.2** | **49.2** | **67.7** | 6.9ms     | 145     || 89.0M  | 221.5
 | | | | | | || |
+| [YOLOv5x](https://github.com/ultralytics/yolov5/releases) + TTA|**50.8**| **50.8** | **68.9** | 25.5ms    | 39      || 89.0M  | 801.0
 ** AP<sup>test</sup> denotes COCO [test-dev2017](http://cocodataset.org/#upload) server results, all other AP results denote val2017 accuracy.
 ** All AP numbers are for single-model single-scale without ensemble or TTA. **Reproduce mAP** by `python test.py --data coco.yaml --img 640 --conf 0.001 --iou 0.65`