- Released a new series of PP-PicoDet models, it was used TAL/Task-aligned-Head and optimized PAN, which improved the accuracy and optimized CPU prediction speed. Moreover the training speed is greatly improved. **(2022.03.20)**
- Released a new series of PP-PicoDet models: **(2022.03.20)**
- (1) It was used TAL/Task-aligned-Head and optimized PAN, which greatly improved the accuracy;
- (2) Moreover optimized CPU prediction speed, and the training speed is greatly improved;
- (3) The export model includes post-processing, and the prediction directly outputs the result, without secondary development, and the migration cost is lower.
### Legacy Model
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@@ -28,24 +31,24 @@ We developed a series of lightweight models, named `PP-PicoDet`. Because of the
-<aname="latency">Latency:</a> All our models test on `Qualcomm Snapdragon 865(4xA77+4xA55)` with 4 threads by arm8 and with FP16. In the above table, test latency on [NCNN](https://github.com/Tencent/ncnn) and `Lite`->[Paddle-Lite](https://github.com/PaddlePaddle/Paddle-Lite). And testing latency with code: [MobileDetBenchmark](https://github.com/JiweiMaster/MobileDetBenchmark).
- PicoDet is trained on COCO train2017 dataset and evaluated on COCO val2017.
-PicoDet used 4 or 8 GPUs for training and all checkpoints are trained with default settings and hyperparameters.
-<aname="latency">Latency:</a> All our models test on `Intel-Xeon-Gold-6148` CPU with MKLDNN by 10 threads and `Qualcomm Snapdragon 865(4xA77+4xA55)` with 4 threads by arm8 and with FP16. In the above table, test CPU latency on Paddle-Inference and testing Mobile latency with `Lite`->[Paddle-Lite](https://github.com/PaddlePaddle/Paddle-Lite).
- PicoDet is trained on COCO train2017 dataset and evaluated on COCO val2017. And PicoDet used 4 GPUs for training and all checkpoints are trained with default settings and hyperparameters.
-Benchmark test: When testing the speed benchmark, the post-processing is not included in the exported model, you need to set `-o export.benchmark=True` or manually modify [runtime.yml](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/runtime.yml#L12).
</details>
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@@ -65,6 +68,7 @@ We developed a series of lightweight models, named `PP-PicoDet`. Because of the
