更换文档检测模型

2024-08-27 14:42:45 +08:00
parent aea6f19951
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--- a/paddle_detection/configs/smalldet/visdrone/README.md
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+# VisDrone-DET 小目标检测模型
+
+PaddleDetection团队提供了针对VisDrone-DET小目标数航拍场景的基于PP-YOLOE的检测模型，用户可以下载模型进行使用。整理后的COCO格式VisDrone-DET数据集[下载链接](https://bj.bcebos.com/v1/paddledet/data/smalldet/visdrone.zip)，检测其中的10类，包括 `pedestrian(1), people(2), bicycle(3), car(4), van(5), truck(6), tricycle(7), awning-tricycle(8), bus(9), motor(10)`，原始数据集[下载链接](https://github.com/VisDrone/VisDrone-Dataset)。其他相关小目标数据集可参照 [DataDownload.md](../DataDownload.md)。
+
+**注意:**
+- VisDrone-DET数据集包括**train集6471张，val集548张，test_dev集1610张**，test-challenge集1580张(未开放检测框标注)，前三者均有开放检测框标注。
+- 模型均**只使用train集训练**，在val集和test_dev集上分别验证精度，test_dev集图片数较多，精度参考性较高。
+
+
+## 原图训练，原图评估：
+
+|    模型   | COCOAPI mAP<sup>val<br>0.5:0.95 | COCOAPI mAP<sup>val<br>0.5 | COCOAPI mAP<sup>test_dev<br>0.5:0.95 | COCOAPI mAP<sup>test_dev<br>0.5 | MatlabAPI mAP<sup>test_dev<br>0.5:0.95 | MatlabAPI mAP<sup>test_dev<br>0.5 | 下载  | 配置文件 |
+|:---------|:------:|:------:| :----: | :------:| :------: | :------:| :----: | :------:|
+|PP-YOLOE-s|  23.5  |  39.9  |  19.4  |  33.6   |  23.68   |  40.66  | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_s_80e_visdrone.pdparams) | [配置文件](./ppyoloe_crn_s_80e_visdrone.yml) |
+|PP-YOLOE-P2-Alpha-s|    24.4  |  41.6  |  20.1  |  34.7  |  24.55   |  42.19  | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_s_p2_alpha_80e_visdrone.pdparams) | [配置文件](./ppyoloe_crn_s_p2_alpha_80e_visdrone.yml) |
+|**PP-YOLOE+_SOD-s**|  **25.1**  |  **42.8**  |  **20.7**  |  **36.2**   |  **25.16**  |  **43.86**   | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_sod_crn_s_80e_visdrone.pdparams) | [配置文件](./ppyoloe_plus_sod_crn_s_80e_visdrone.yml) |
+|PP-YOLOE-l|  29.2  |  47.3  |  23.5  |  39.1   |  28.00   |  46.20  | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_80e_visdrone.pdparams) | [配置文件](./ppyoloe_crn_l_80e_visdrone.yml) |
+|PP-YOLOE-P2-Alpha-l|  30.1  |  48.9  |  24.3  |  40.8   |  28.47   |  48.16  | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_p2_alpha_80e_visdrone.pdparams) | [配置文件](./ppyoloe_crn_l_p2_alpha_80e_visdrone.yml) |
+|**PP-YOLOE+_SOD-l**|  **31.9**  |  **52.1**  |  **25.6**  |  **43.5**   |  **30.25**  |  **51.18**   | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_sod_crn_l_80e_visdrone.pdparams) | [配置文件](./ppyoloe_plus_sod_crn_l_80e_visdrone.yml) |
+|PP-YOLOE-Alpha-largesize-l|  41.9  |  65.0 |  32.3  |  53.0   |  37.13   |  61.15  | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_alpha_largesize_80e_visdrone.pdparams) | [配置文件](./ppyoloe_crn_l_alpha_largesize_80e_visdrone.yml) |
+|PP-YOLOE-P2-Alpha-largesize-l|  41.3  |  64.5  |  32.4  |  53.1   |  37.49   |  51.54  | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_p2_alpha_largesize_80e_visdrone.pdparams) | [配置文件](./ppyoloe_crn_l_p2_alpha_largesize_80e_visdrone.yml) |
+|PP-YOLOE+_largesize-l |  43.3  |  66.7 |  33.5  |  54.7   |  38.24   |  62.76  | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_l_largesize_80e_visdrone.pdparams) | [配置文件](./ppyoloe_plus_crn_l_largesize_80e_visdrone.yml) |
+|**PP-YOLOE+_SOD-largesize-l** |  42.7  |  65.9 |  **33.6**  |  **55.1**   |  **38.4**   |  **63.07**  | [下载链接](https://paddledet.bj.bcebos.com/models/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone.pdparams) | [配置文件](./ppyoloe_plus_sod_crn_l_largesize_80e_visdrone.yml) |
+
+**注意:**
+  - 上表中的模型均为**使用原图训练**，也**使用原图评估预测**，AP精度均为**原图验证集**上评估的结果。
+  - VisDrone-DET数据集**可使用原图训练，也可使用切图后训练**，通过数据集统计分布分析，推荐使用**原图训练**，推荐直接使用带**SOD**的模型配置文件去训练评估和预测部署，在显卡算力有限时也可使用切图后训练。
+  - 上表中的模型指标均是使用VisDrone-DET的train子集作为训练集，使用VisDrone-DET的val子集和test_dev子集作为验证集。
+  - **SOD**表示使用**基于向量的DFL算法**和针对小目标的**中心先验优化策略**，并**在模型的Neck结构中加入transformer**。
+  - **P2**表示增加P2层(1/4下采样层)的特征，共输出4个PPYOLOEHead。
+  - **Alpha**表示对CSPResNet骨干网络增加可一个学习权重参数Alpha参与训练。
+  - **largesize**表示使用**以1600尺度为基础的多尺度训练**和**1920尺度预测**，相应的训练batch_size也减小，以速度来换取高精度。
+  - MatlabAPI测试是使用官网评测工具[VisDrone2018-DET-toolkit](https://github.com/VisDrone/VisDrone2018-DET-toolkit)。
+
+<details>
+<summary> 快速开始 </summary>
+
+```shell
+# 训练
+python -m paddle.distributed.launch --log_dir=logs/ --gpus 0,1,2,3,4,5,6,7 tools/train.py -c configs/smalldet/visdrone/ppyoloe_plus_sod_crn_l_80e_visdrone.yml --amp --eval
+# 评估
+python tools/eval.py -c configs/smalldet/visdrone/ppyoloe_plus_sod_crn_l_80e_visdrone.yml -o weights=https://paddledet.bj.bcebos.com/models/ppyoloe_plus_sod_crn_l_80e_visdrone.pdparams
+# 预测
+python tools/infer.py -c configs/smalldet/visdrone/ppyoloe_plus_sod_crn_l_80e_visdrone.yml -o weights=https://paddledet.bj.bcebos.com/models/ppyoloe_plus_sod_crn_l_80e_visdrone.pdparams --infer_img=demo/visdrone_0000315_01601_d_0000509.jpg --draw_threshold=0.25
+```
+
+</details>
+
+
+## 子图训练，原图评估和拼图评估：
+
+|    模型   |       数据集     |  SLICE_SIZE  |  OVERLAP_RATIO  | 类别数  | mAP<sup>val<br>0.5:0.95 | AP<sup>val<br>0.5 | 下载链接  | 配置文件 |
+|:---------|:---------------:|:---------------:|:---------------:|:------:|:-----------------------:|:-------------------:|:---------:| :-----: |
+|PP-YOLOE-l(子图直接评估)| VisDrone-DET|  640 | 0.25 | 10 |  38.5(子图val) |  60.2 | [下载链接](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_crn_l_80e_sliced_visdrone_640_025.pdparams) | [配置文件](./ppyoloe_crn_l_80e_sliced_visdrone_640_025.yml) |
+|PP-YOLOE-l(原图直接评估)| VisDrone-DET|  640 | 0.25 | 10 |  29.7(原图val) |  48.5 | [下载链接](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_crn_l_80e_sliced_visdrone_640_025.pdparams) | [配置文件](../ppyoloe_crn_l_80e_sliced_visdrone_640_025.yml) |
+|PP-YOLOE-l (切图拼图评估)| VisDrone-DET|  640 | 0.25 | 10 | 37.3(原图val) | 59.5 | [下载链接](https://bj.bcebos.com/v1/paddledet/models/ppyoloe_crn_l_80e_sliced_visdrone_640_025.pdparams) | [配置文件](../ppyoloe_crn_l_80e_sliced_visdrone_640_025.yml) |
+
+**注意:**
+  - 上表中的模型均为使用**切图后的子图**训练，评估预测时分为两种，**直接使用原图**评估预测，和**使用子图自动拼成原图**评估预测，AP精度均为**原图验证集**上评估的结果。。
+  - **SLICE_SIZE**表示使用SAHI工具切图后子图的边长大小，**OVERLAP_RATIO**表示切图的子图之间的重叠率。
+  - VisDrone-DET的模型与[切图模型](../README.md#切图模型)表格中的VisDrone-DET是**同一个模型权重**，但此处AP精度是在**原图验证集**上评估的结果，需要提前修改`ppyoloe_crn_l_80e_sliced_visdrone_640_025.yml`里的`EvalDataset`的默认的子图验证集路径为以下**原图验证集路径**：
+  ```
+  EvalDataset:
+    !COCODataSet
+      image_dir: VisDrone2019-DET-val
+      anno_path: val.json
+      dataset_dir: dataset/visdrone
+  ```
+
+<details>
+<summary> 快速开始 </summary>
+
+```shell
+# 训练
+python -m paddle.distributed.launch --log_dir=logs/ --gpus 0,1,2,3,4,5,6,7 tools/train.py -c configs/smalldet/ppyoloe_crn_l_80e_sliced_visdrone_640_025.yml --amp --eval
+# 子图直接评估
+python tools/eval.py -c configs/smalldet/ppyoloe_crn_l_80e_sliced_visdrone_640_025.yml -o weights=https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_80e_sliced_visdrone_640_025.pdparams
+# 原图直接评估，注意需要提前修改此yml中的 `EvalDataset` 的默认的子图验证集路径 为 原图验证集路径：
+python tools/eval.py -c configs/smalldet/ppyoloe_crn_l_80e_sliced_visdrone_640_025.yml -o weights=https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_80e_sliced_visdrone_640_025.pdparams
+# 切图拼图评估，加上 --slice_infer，注意是使用的带 _slice_infer 后缀的yml配置文件
+python tools/eval.py -c configs/smalldet/ppyoloe_crn_l_80e_sliced_visdrone_640_025_slice_infer.yml -o weights=https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_80e_sliced_visdrone_640_025.pdparams --slice_infer
+# 切图拼图预测，加上 --slice_infer
+python tools/infer.py -c configs/smalldet/ppyoloe_crn_l_80e_sliced_visdrone_640_025.yml -o weights=https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_80e_sliced_visdrone_640_025.pdparams --infer_img=demo/visdrone_0000315_01601_d_0000509.jpg --draw_threshold=0.25 --slice_infer
+```
+
+</details>
+
+
+## 注意事项：
+  - PP-YOLOE模型训练过程中使用8 GPUs进行混合精度训练，如果**GPU卡数**或者**batch size**发生了改变，你需要按照公式 **lr<sub>new</sub> = lr<sub>default</sub> * (batch_size<sub>new</sub> * GPU_number<sub>new</sub>) / (batch_size<sub>default</sub> * GPU_number<sub>default</sub>)** 调整学习率。
+  - 具体使用教程请参考[ppyoloe](../../ppyoloe#getting-start)。
+  - MatlabAPI测试是使用官网评测工具[VisDrone2018-DET-toolkit](https://github.com/VisDrone/VisDrone2018-DET-toolkit)。
+
+
+## PP-YOLOE+_SOD 部署模型
+
+| 网络模型     | 输入尺寸 | 导出后的权重(w/o NMS) | ONNX(w/o NMS)  |
+| :-------- | :--------: | :---------------------: | :----------------: |
+| PP-YOLOE+_SOD-s |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/smalldet/ppyoloe_plus_sod_crn_s_80e_visdrone_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/smalldet/ppyoloe_plus_sod_crn_s_80e_visdrone_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/smalldet/ppyoloe_plus_sod_crn_s_80e_visdrone_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/smalldet/ppyoloe_plus_sod_crn_s_80e_visdrone_wo_nms.onnx) |
+| PP-YOLOE+_SOD-l |  640   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/smalldet/ppyoloe_plus_sod_crn_l_80e_visdrone_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/smalldet/ppyoloe_plus_sod_crn_l_80e_visdrone_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/smalldet/ppyoloe_plus_sod_crn_l_80e_visdrone_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/smalldet/ppyoloe_plus_sod_crn_l_80e_visdrone_wo_nms.onnx) |
+| PP-YOLOE+_SOD-largesize-l |  1920   | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/smalldet/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone_w_nms.zip) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/smalldet/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone_wo_nms.zip) | [( w/ nms)](https://paddledet.bj.bcebos.com/deploy/smalldet/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone_w_nms.onnx) &#124; [( w/o nms)](https://paddledet.bj.bcebos.com/deploy/smalldet/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone_wo_nms.onnx) |
+
+
+## 测速
+
+1.参考[Paddle Inference文档](https://www.paddlepaddle.org.cn/inference/master/user_guides/download_lib.html#python)，下载并安装与你的CUDA, CUDNN和TensorRT相应的wheel包。
+测速需要设置`--run_benchmark=True`, 你需要安装以下依赖`pip install pynvml psutil GPUtil`。
+导出ONNX，你需要安装以下依赖`pip install paddle2onnx`。
+
+2.运行以下命令导出**带NMS的模型和ONNX**，并使用TensorRT FP16进行推理和测速
+
+### 注意：
+
+- 由于NMS参数设置对速度影响极大，部署测速时可调整`keep_top_k`和`nms_top_k`，在只低约0.1 mAP精度的情况下加快预测速度，导出模型的时候也可这样设置：
+  ```
+  nms:
+    name: MultiClassNMS
+    nms_top_k: 1000 # 10000
+    keep_top_k: 100 # 500
+    score_threshold: 0.01
+    nms_threshold: 0.6
+  ```
+
+```bash
+# 导出带NMS的模型
+python tools/export_model.py -c configs/smalldet/visdrone/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone.yml -o weights=https://paddledet.bj.bcebos.com/models/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone.pdparams trt=True
+
+# 导出带NMS的ONNX
+paddle2onnx --model_dir output_inference/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone --model_filename model.pdmodel --params_filename model.pdiparams --opset_version 12 --save_file ppyoloe_plus_sod_crn_l_largesize_80e_visdrone.onnx
+
+# 推理单张图片
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone --image_file=demo/visdrone_0000315_01601_d_0000509.jpg --device=gpu --run_mode=trt_fp16
+
+# 推理文件夹下的所有图片
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone --image_dir=demo/ --device=gpu --run_mode=trt_fp16
+
+# 单张图片普通测速
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone --image_file=demo/visdrone_0000315_01601_d_0000509.jpg --device=gpu --run_benchmark=True
+
+# 单张图片TensorRT FP16测速
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone --image_file=demo/visdrone_0000315_01601_d_0000509.jpg --device=gpu --run_benchmark=True --run_mode=trt_fp16
+```
+
+3.运行以下命令导出**不带NMS的模型和ONNX**，并使用TensorRT FP16进行推理和测速，以及**ONNX下FP16测速**
+
+```bash
+# 导出带NMS的模型
+python tools/export_model.py -c configs/smalldet/visdrone/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone.yml -o weights=https://paddledet.bj.bcebos.com/models/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone.pdparams trt=True exclude_nms=True
+
+# 导出带NMS的ONNX
+paddle2onnx --model_dir output_inference/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone --model_filename model.pdmodel --params_filename model.pdiparams --opset_version 12 --save_file ppyoloe_plus_sod_crn_l_largesize_80e_visdrone.onnx
+
+# 推理单张图片
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone --image_file=demo/visdrone_0000315_01601_d_0000509.jpg --device=gpu --run_mode=trt_fp16
+
+# 推理文件夹下的所有图片
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone --image_dir=demo/ --device=gpu --run_mode=trt_fp16
+
+# 单张图片普通测速
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone --image_file=demo/visdrone_0000315_01601_d_0000509.jpg --device=gpu --run_benchmark=True
+
+# 单张图片TensorRT FP16测速
+CUDA_VISIBLE_DEVICES=0 python deploy/python/infer.py --model_dir=output_inference/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone --image_file=demo/visdrone_0000315_01601_d_0000509.jpg --device=gpu --run_benchmark=True --run_mode=trt_fp16
+
+# 单张图片ONNX TensorRT FP16测速
+/usr/local/TensorRT-8.0.3.4/bin/trtexec --onnx=ppyoloe_plus_sod_crn_l_largesize_80e_visdrone.onnx --workspace=4096 --avgRuns=10 --shapes=input:1x3x1920x1920 --fp16
+```
+
+**注意：**
+- TensorRT会根据网络的定义，执行针对当前硬件平台的优化，生成推理引擎并序列化为文件。该推理引擎只适用于当前软硬件平台。如果你的软硬件平台没有发生变化，你可以设置[enable_tensorrt_engine](https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/deploy/python/infer.py#L857)的参数`use_static=True`，这样生成的序列化文件将会保存在`output_inference`文件夹下，下次执行TensorRT时将加载保存的序列化文件。
+- PaddleDetection release/2.4及其之后的版本将支持NMS调用TensorRT，需要依赖PaddlePaddle release/2.3及其之后的版本
+
+
+# 引用
+```
+@ARTICLE{9573394,
+  author={Zhu, Pengfei and Wen, Longyin and Du, Dawei and Bian, Xiao and Fan, Heng and Hu, Qinghua and Ling, Haibin},
+  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
+  title={Detection and Tracking Meet Drones Challenge},
+  year={2021},
+  volume={},
+  number={},
+  pages={1-1},
+  doi={10.1109/TPAMI.2021.3119563}
+}
+```
--- a/paddle_detection/configs/smalldet/visdrone/ppyoloe_crn_l_80e_visdrone.yml
+++ b/paddle_detection/configs/smalldet/visdrone/ppyoloe_crn_l_80e_visdrone.yml
@@ -0,0 +1,45 @@
+_BASE_: [
+  '../../datasets/visdrone_detection.yml',
+  '../../runtime.yml',
+  '../../ppyoloe/_base_/optimizer_300e.yml',
+  '../../ppyoloe/_base_/ppyoloe_crn.yml',
+  '../../ppyoloe/_base_/ppyoloe_reader.yml',
+]
+log_iter: 100
+snapshot_epoch: 10
+weights: output/ppyoloe_crn_l_80e_visdrone/model_final
+
+pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_300e_coco.pdparams
+depth_mult: 1.0
+width_mult: 1.0
+
+
+TrainReader:
+  batch_size: 8
+
+EvalReader:
+  batch_size: 1
+
+TestReader:
+  batch_size: 1
+  fuse_normalize: True
+
+
+epoch: 80
+LearningRate:
+  base_lr: 0.01
+  schedulers:
+    - !CosineDecay
+      max_epochs: 96
+    - !LinearWarmup
+      start_factor: 0.
+      epochs: 1
+
+PPYOLOEHead:
+  static_assigner_epoch: -1
+  nms:
+    name: MultiClassNMS
+    nms_top_k: 10000
+    keep_top_k: 500
+    score_threshold: 0.01
+    nms_threshold: 0.6
--- a/paddle_detection/configs/smalldet/visdrone/ppyoloe_crn_l_alpha_largesize_80e_visdrone.yml
+++ b/paddle_detection/configs/smalldet/visdrone/ppyoloe_crn_l_alpha_largesize_80e_visdrone.yml
@@ -0,0 +1,58 @@
+_BASE_: [
+  'ppyoloe_crn_l_80e_visdrone.yml',
+]
+log_iter: 100
+snapshot_epoch: 10
+weights: output/ppyoloe_crn_l_alpha_largesize_80e_visdrone/model_final
+pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_300e_coco.pdparams
+
+
+CSPResNet:
+  use_alpha: True
+
+
+LearningRate:
+  base_lr: 0.0025
+
+
+worker_num: 2
+eval_height: &eval_height 1920
+eval_width: &eval_width 1920
+eval_size: &eval_size [*eval_height, *eval_width]
+
+TrainReader:
+  sample_transforms:
+    - Decode: {}
+    - RandomDistort: {}
+    - RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
+    - RandomCrop: {}
+    - RandomFlip: {}
+  batch_transforms:
+    - BatchRandomResize: {target_size: [1024, 1088, 1152, 1216, 1280, 1344, 1408, 1472, 1536, 1600, 1664, 1728, 1792, 1856, 1920], random_size: True, random_interp: True, keep_ratio: False}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
+    - Permute: {}
+    - PadGT: {}
+  batch_size: 2
+  shuffle: true
+  drop_last: true
+  use_shared_memory: true
+  collate_batch: true
+
+EvalReader:
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: *eval_size, keep_ratio: False, interp: 2}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
+    - Permute: {}
+  batch_size: 1
+
+TestReader:
+  inputs_def:
+    image_shape: [3, *eval_height, *eval_width]
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: *eval_size, keep_ratio: False, interp: 2}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
+    - Permute: {}
+  batch_size: 1
+  fuse_normalize: True
--- a/paddle_detection/configs/smalldet/visdrone/ppyoloe_crn_l_p2_alpha_80e_visdrone.yml
+++ b/paddle_detection/configs/smalldet/visdrone/ppyoloe_crn_l_p2_alpha_80e_visdrone.yml
@@ -0,0 +1,33 @@
+_BASE_: [
+  'ppyoloe_crn_l_80e_visdrone.yml',
+]
+log_iter: 100
+snapshot_epoch: 10
+weights: output/ppyoloe_crn_l_p2_alpha_80e_visdrone/model_final
+pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_300e_coco.pdparams
+
+
+TrainReader:
+  batch_size: 4
+
+EvalReader:
+  batch_size: 1
+
+TestReader:
+  batch_size: 1
+  fuse_normalize: True
+
+
+LearningRate:
+  base_lr: 0.005
+
+
+CSPResNet:
+  return_idx: [0, 1, 2, 3]
+  use_alpha: True
+
+CustomCSPPAN:
+  out_channels: [768, 384, 192, 64]
+
+PPYOLOEHead:
+  fpn_strides: [32, 16, 8, 4]
--- a/paddle_detection/configs/smalldet/visdrone/ppyoloe_crn_l_p2_alpha_largesize_80e_visdrone.yml
+++ b/paddle_detection/configs/smalldet/visdrone/ppyoloe_crn_l_p2_alpha_largesize_80e_visdrone.yml
@@ -0,0 +1,65 @@
+_BASE_: [
+  'ppyoloe_crn_l_80e_visdrone.yml',
+]
+log_iter: 100
+snapshot_epoch: 10
+weights: output/ppyoloe_crn_l_p2_alpha_largesize_80e_visdrone/model_final
+pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_crn_l_300e_coco.pdparams
+
+
+LearningRate:
+  base_lr: 0.005
+
+
+CSPResNet:
+  return_idx: [0, 1, 2, 3]
+  use_alpha: True
+
+CustomCSPPAN:
+  out_channels: [768, 384, 192, 64]
+
+PPYOLOEHead:
+  fpn_strides: [32, 16, 8, 4]
+
+
+worker_num: 2
+eval_height: &eval_height 1920
+eval_width: &eval_width 1920
+eval_size: &eval_size [*eval_height, *eval_width]
+
+TrainReader:
+  sample_transforms:
+    - Decode: {}
+    - RandomDistort: {}
+    - RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
+    - RandomCrop: {}
+    - RandomFlip: {}
+  batch_transforms:
+    - BatchRandomResize: {target_size: [1024, 1088, 1152, 1216, 1280, 1344, 1408, 1472, 1536, 1600, 1664, 1728, 1792, 1856, 1920, 1984, 2048], random_size: True, random_interp: True, keep_ratio: False}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
+    - Permute: {}
+    - PadGT: {}
+  batch_size: 1
+  shuffle: true
+  drop_last: true
+  use_shared_memory: true
+  collate_batch: true
+
+EvalReader:
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: *eval_size, keep_ratio: False, interp: 2}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
+    - Permute: {}
+  batch_size: 1
+
+TestReader:
+  inputs_def:
+    image_shape: [3, *eval_height, *eval_width]
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: *eval_size, keep_ratio: False, interp: 2}
+    - NormalizeImage: {mean: [0.485, 0.456, 0.406], std: [0.229, 0.224, 0.225], is_scale: True}
+    - Permute: {}
+  batch_size: 1
+  fuse_normalize: True
--- a/paddle_detection/configs/smalldet/visdrone/ppyoloe_crn_s_80e_visdrone.yml
+++ b/paddle_detection/configs/smalldet/visdrone/ppyoloe_crn_s_80e_visdrone.yml
@@ -0,0 +1,45 @@
+_BASE_: [
+  '../../datasets/visdrone_detection.yml',
+  '../../runtime.yml',
+  '../../ppyoloe/_base_/optimizer_300e.yml',
+  '../../ppyoloe/_base_/ppyoloe_crn.yml',
+  '../../ppyoloe/_base_/ppyoloe_reader.yml',
+]
+log_iter: 100
+snapshot_epoch: 10
+weights: output/ppyoloe_crn_s_80e_visdrone/model_final
+
+pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_crn_s_300e_coco.pdparams
+depth_mult: 0.33
+width_mult: 0.50
+
+
+TrainReader:
+  batch_size: 8
+
+EvalReader:
+  batch_size: 1
+
+TestReader:
+  batch_size: 1
+  fuse_normalize: True
+
+
+epoch: 80
+LearningRate:
+  base_lr: 0.01
+  schedulers:
+    - !CosineDecay
+      max_epochs: 96
+    - !LinearWarmup
+      start_factor: 0.
+      epochs: 1
+
+PPYOLOEHead:
+  static_assigner_epoch: -1
+  nms:
+    name: MultiClassNMS
+    nms_top_k: 10000
+    keep_top_k: 500
+    score_threshold: 0.01
+    nms_threshold: 0.6
--- a/paddle_detection/configs/smalldet/visdrone/ppyoloe_crn_s_p2_alpha_80e_visdrone.yml
+++ b/paddle_detection/configs/smalldet/visdrone/ppyoloe_crn_s_p2_alpha_80e_visdrone.yml
@@ -0,0 +1,32 @@
+_BASE_: [
+  'ppyoloe_crn_s_80e_visdrone.yml',
+]
+log_iter: 100
+snapshot_epoch: 10
+weights: output/ppyoloe_crn_s_p2_alpha_80e_visdrone/model_final
+pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_crn_s_300e_coco.pdparams
+
+
+TrainReader:
+  batch_size: 4
+
+EvalReader:
+  batch_size: 1
+
+TestReader:
+  batch_size: 1
+  fuse_normalize: True
+
+
+LearningRate:
+  base_lr: 0.005
+
+CSPResNet:
+  return_idx: [0, 1, 2, 3]
+  use_alpha: True
+
+CustomCSPPAN:
+  out_channels: [768, 384, 192, 64]
+
+PPYOLOEHead:
+  fpn_strides: [32, 16, 8, 4]
--- a/paddle_detection/configs/smalldet/visdrone/ppyoloe_plus_crn_l_largesize_80e_visdrone.yml
+++ b/paddle_detection/configs/smalldet/visdrone/ppyoloe_plus_crn_l_largesize_80e_visdrone.yml
@@ -0,0 +1,58 @@
+_BASE_: [
+  'ppyoloe_crn_l_80e_visdrone.yml',
+]
+log_iter: 100
+snapshot_epoch: 10
+weights: output/ppyoloe_plus_crn_l_largesize_80e_visdrone/model_final
+pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_l_80e_coco.pdparams
+
+
+CSPResNet:
+  use_alpha: True
+
+
+LearningRate:
+  base_lr: 0.0025
+
+
+worker_num: 2
+eval_height: &eval_height 1920
+eval_width: &eval_width 1920
+eval_size: &eval_size [*eval_height, *eval_width]
+
+TrainReader:
+  sample_transforms:
+    - Decode: {}
+    - RandomDistort: {}
+    - RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
+    - RandomCrop: {}
+    - RandomFlip: {}
+  batch_transforms:
+    - BatchRandomResize: {target_size: [1024, 1088, 1152, 1216, 1280, 1344, 1408, 1472, 1536, 1600, 1664, 1728, 1792, 1856, 1920], random_size: True, random_interp: True, keep_ratio: False}
+    - NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
+    - Permute: {}
+    - PadGT: {}
+  batch_size: 2
+  shuffle: true
+  drop_last: true
+  use_shared_memory: true
+  collate_batch: true
+
+EvalReader:
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: *eval_size, keep_ratio: False, interp: 2}
+    - NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
+    - Permute: {}
+  batch_size: 1
+
+TestReader:
+  inputs_def:
+    image_shape: [3, *eval_height, *eval_width]
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: *eval_size, keep_ratio: False, interp: 2}
+    - NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
+    - Permute: {}
+  batch_size: 1
+  fuse_normalize: True
--- a/paddle_detection/configs/smalldet/visdrone/ppyoloe_plus_sod_crn_l_80e_visdrone.yml
+++ b/paddle_detection/configs/smalldet/visdrone/ppyoloe_plus_sod_crn_l_80e_visdrone.yml
@@ -0,0 +1,58 @@
+_BASE_: [
+  '../../datasets/visdrone_detection.yml',
+  '../../runtime.yml',
+  '../../ppyoloe/_base_/optimizer_80e.yml',
+  '../../ppyoloe/_base_/ppyoloe_plus_crn.yml',
+  '../../ppyoloe/_base_/ppyoloe_plus_reader.yml'
+]
+log_iter: 100
+snapshot_epoch: 10
+weights: output/ppyoloe_plus_sod_crn_l_80e_visdrone/model_final
+
+pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_l_80e_coco.pdparams
+depth_mult: 1.0
+width_mult: 1.0
+
+TrainReader:
+  batch_size: 8
+
+EvalReader:
+  batch_size: 1
+
+TestReader:
+  batch_size: 1
+  fuse_normalize: True
+
+
+epoch: 80
+LearningRate:
+  base_lr: 0.01
+  schedulers:
+    - !CosineDecay
+      max_epochs: 96
+    - !LinearWarmup
+      start_factor: 0.
+      epochs: 1
+
+CustomCSPPAN:
+  num_layers: 4
+  use_trans: True
+
+PPYOLOEHead:
+  reg_range: [-2,8]
+  static_assigner_epoch: -1
+  static_assigner:
+    name: ATSSAssigner
+    topk: 9
+  assigner:
+    name: TaskAlignedAssigner_CR
+    center_radius: 1
+    topk: 13
+    alpha: 1.0
+    beta: 6.0
+  nms:
+    name: MultiClassNMS
+    nms_top_k: 10000
+    keep_top_k: 500
+    score_threshold: 0.01
+    nms_threshold: 0.6
--- a/paddle_detection/configs/smalldet/visdrone/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone.yml
+++ b/paddle_detection/configs/smalldet/visdrone/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone.yml
@@ -0,0 +1,56 @@
+_BASE_: [
+  'ppyoloe_plus_sod_crn_l_80e_visdrone.yml',
+]
+log_iter: 100
+snapshot_epoch: 10
+weights: output/ppyoloe_plus_sod_crn_l_largesize_80e_visdrone/model_final
+pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyoloe_plus_crn_l_80e_coco.pdparams
+
+PPYOLOEHead:
+  reg_range: [-2,20]
+  static_assigner_epoch: -1
+
+LearningRate:
+  base_lr: 0.00125
+
+worker_num: 2
+eval_height: &eval_height 1920
+eval_width: &eval_width 1920
+eval_size: &eval_size [*eval_height, *eval_width]
+
+TrainReader:
+  sample_transforms:
+    - Decode: {}
+    - RandomDistort: {}
+    - RandomExpand: {fill_value: [123.675, 116.28, 103.53]}
+    - RandomCrop: {}
+    - RandomFlip: {}
+  batch_transforms:
+    - BatchRandomResize: {target_size: [1024, 1088, 1152, 1216, 1280, 1344, 1408, 1472, 1536, 1600, 1664, 1728, 1792, 1856, 1920], random_size: True, random_interp: True, keep_ratio: False}
+    - NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
+    - Permute: {}
+    - PadGT: {}
+  batch_size: 1
+  shuffle: true
+  drop_last: true
+  use_shared_memory: true
+  collate_batch: true
+
+EvalReader:
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: *eval_size, keep_ratio: False, interp: 2}
+    - NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
+    - Permute: {}
+  batch_size: 1
+
+TestReader:
+  inputs_def:
+    image_shape: [3, *eval_height, *eval_width]
+  sample_transforms:
+    - Decode: {}
+    - Resize: {target_size: *eval_size, keep_ratio: False, interp: 2}
+    - NormalizeImage: {mean: [0., 0., 0.], std: [1., 1., 1.], norm_type: none}
+    - Permute: {}
+  batch_size: 1
+  fuse_normalize: True
--- a/paddle_detection/configs/smalldet/visdrone/ppyoloe_plus_sod_crn_s_80e_visdrone.yml
+++ b/paddle_detection/configs/smalldet/visdrone/ppyoloe_plus_sod_crn_s_80e_visdrone.yml
@@ -0,0 +1,58 @@
+_BASE_: [
+  '../../datasets/visdrone_detection.yml',
+  '../../runtime.yml',
+  '../../ppyoloe/_base_/optimizer_80e.yml',
+  '../../ppyoloe/_base_/ppyoloe_plus_crn.yml',
+  '../../ppyoloe/_base_/ppyoloe_plus_reader.yml'
+]
+log_iter: 100
+snapshot_epoch: 10
+weights: output/ppyoloe_plus_sod_crn_s_80e_visdrone/model_final
+
+pretrain_weights: https://bj.bcebos.com/v1/paddledet/models/ppyoloe_plus_crn_s_80e_coco.pdparams
+depth_mult: 0.33
+width_mult: 0.50
+
+TrainReader:
+  batch_size: 8
+
+EvalReader:
+  batch_size: 1
+
+TestReader:
+  batch_size: 1
+  fuse_normalize: True
+
+
+epoch: 80
+LearningRate:
+  base_lr: 0.01
+  schedulers:
+    - !CosineDecay
+      max_epochs: 96
+    - !LinearWarmup
+      start_factor: 0.
+      epochs: 1
+
+CustomCSPPAN:
+  num_layers: 4
+  use_trans: True
+
+PPYOLOEHead:
+  reg_range: [-2,8]
+  static_assigner_epoch: -1
+  static_assigner:
+    name: ATSSAssigner
+    topk: 9
+  assigner:
+    name: TaskAlignedAssigner_CR
+    center_radius: 1
+    topk: 13
+    alpha: 1.0
+    beta: 6.0
+  nms:
+    name: MultiClassNMS
+    nms_top_k: 10000
+    keep_top_k: 500
+    score_threshold: 0.01
+    nms_threshold: 0.6