From 6eff044638272031294422330e404270034af103 Mon Sep 17 00:00:00 2001 From: zhiboniu <31800336+zhiboniu@users.noreply.github.com> Date: Fri, 19 Aug 2022 11:07:20 +0800 Subject: [PATCH] update ppvehicle modelzoo (#6679) * update ppvehicle modelzoo; test=document_fix * update pipeline pictures * update * fix platerec jetson trtfp16; test=document_fix * replace all --model_dir in pipeline docs; test=document_fix --- deploy/pipeline/README.md | 24 +++++++----------- .../docs/tutorials/PPVehicle_QUICK_STARTED.md | 17 +++++++------ .../pipeline/docs/tutorials/pphuman_action.md | 6 ++--- .../docs/tutorials/pphuman_action_en.md | 10 ++++---- .../docs/tutorials/pphuman_attribute.md | 8 +++--- .../docs/tutorials/pphuman_attribute_en.md | 6 ++--- deploy/pipeline/docs/tutorials/pphuman_mot.md | 6 ++--- .../pipeline/docs/tutorials/pphuman_mot_en.md | 6 ++--- .../pipeline/docs/tutorials/pphuman_mtmct.md | 3 +-- .../docs/tutorials/pphuman_mtmct_en.md | 3 +-- deploy/pipeline/pipe_utils.py | 3 ++- deploy/pipeline/pipeline.py | 1 + .../pipeline/ppvehicle/vehicle_plateutils.py | 1 + docs/images/pphumanv2.png | Bin 107458 -> 293938 bytes docs/images/ppvehicle.png | Bin 0 -> 130129 bytes 15 files changed, 45 insertions(+), 49 deletions(-) create mode 100644 docs/images/ppvehicle.png diff --git a/deploy/pipeline/README.md b/deploy/pipeline/README.md index 15acf2fa9..cbb2d86fb 100644 --- a/deploy/pipeline/README.md +++ b/deploy/pipeline/README.md @@ -62,7 +62,7 @@ | 打电话识别 | 单人ms | [目标检测](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip)
[基于人体id的图像分类](https://bj.bcebos.com/v1/paddledet/models/pipeline/PPHGNet_tiny_calling_halfbody.zip) | 目标检测:182M
基于人体id的图像分类:45M | -点击模型方案中的模型即可下载指定模型,下载后解压存放至`./output_inference`目录中 +点击模型方案中的模型即可下载指定模型,下载后解压存放至`./output_inference`目录中 @@ -71,20 +71,14 @@
端到端模型效果(点击展开) -| 任务 | 端到端速度(ms) | 模型方案 | 模型体积 | -| --------- | --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------- | -| 行人检测(高精度) | 25.1ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip) | 182M | -| 行人检测(轻量级) | 16.2ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_s_36e_pipeline.zip) | 27M | -| 行人跟踪(高精度) | 31.8ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip) | 182M | -| 行人跟踪(轻量级) | 21.0ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_s_36e_pipeline.zip) | 27M | -| 属性识别(高精度) | 单人8.5ms | [目标检测](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip)
[属性识别](https://bj.bcebos.com/v1/paddledet/models/pipeline/strongbaseline_r50_30e_pa100k.zip) | 目标检测:182M
属性识别:86M | -| 属性识别(轻量级) | 单人7.1ms | [目标检测](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip)
[属性识别](https://bj.bcebos.com/v1/paddledet/models/pipeline/strongbaseline_r50_30e_pa100k.zip) | 目标检测:182M
属性识别:86M | -| 摔倒识别 | 单人10ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip)
[关键点检测](https://bj.bcebos.com/v1/paddledet/models/pipeline/dark_hrnet_w32_256x192.zip)
[基于关键点行为识别](https://bj.bcebos.com/v1/paddledet/models/pipeline/STGCN.zip) | 多目标跟踪:182M
关键点检测:101M
基于关键点行为识别:21.8M | -| 闯入识别 | 31.8ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip) | 182M | -| 打架识别 | 19.7ms | [视频分类](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip) | 90M | -| 抽烟识别 | 单人15.1ms | [目标检测](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip)
[基于人体id的目标检测](https://bj.bcebos.com/v1/paddledet/models/pipeline/ppyoloe_crn_s_80e_smoking_visdrone.zip) | 目标检测:182M
基于人体id的目标检测:27M | -| 打电话识别 | 单人ms | [目标检测](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_pipeline.zip)
[基于人体id的图像分类](https://bj.bcebos.com/v1/paddledet/models/pipeline/PPHGNet_tiny_calling_halfbody.zip) | 目标检测:182M
基于人体id的图像分类:45M | - +| 任务 | 端到端速度(ms)| 模型方案 | 模型体积 | +| :---------: | :-------: | :------: |:------: | +| 车辆检测(高精度) | 25.7ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_ppvehicle.zip) | 182M | +| 车辆检测(轻量级) | 13.2ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_s_36e_ppvehicle.zip) | 27M | +| 车辆跟踪(高精度) | 40ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_ppvehicle.zip) | 182M | +| 车辆跟踪(轻量级) | 25ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_s_36e_ppvehicle.zip) | 27M | +| 车牌识别 | 4.68ms | [车牌检测](https://bj.bcebos.com/v1/paddledet/models/pipeline/ch_PP-OCRv3_det_infer.tar.gz)
[车牌字符识别](https://bj.bcebos.com/v1/paddledet/models/pipeline/ch_PP-OCRv3_rec_infer.tar.gz) | 车牌检测:3.9M
车牌字符识别: 12M | +| 车辆属性 | 7.31ms | [车辆属性](https://bj.bcebos.com/v1/paddledet/models/pipeline/vehicle_attribute_model.zip) | 7.2M | 点击模型方案中的模型即可下载指定模型,下载后解压存放至`./output_inference`目录中 diff --git a/deploy/pipeline/docs/tutorials/PPVehicle_QUICK_STARTED.md b/deploy/pipeline/docs/tutorials/PPVehicle_QUICK_STARTED.md index ec0a8b89f..1d45ff521 100644 --- a/deploy/pipeline/docs/tutorials/PPVehicle_QUICK_STARTED.md +++ b/deploy/pipeline/docs/tutorials/PPVehicle_QUICK_STARTED.md @@ -46,11 +46,13 @@ PP-Vehicle提供了目标检测、属性识别、行为识别、ReID预训练模 | 任务 | 端到端速度(ms)| 模型方案 | 模型体积 | | :---------: | :-------: | :------: |:------: | -| 车辆检测(高精度) | 25.1ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_ppvehicle.zip) | 182M | -| 车辆检测(轻量级) | 16.2ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_s_36e_ppvehicle.zip) | 27M | -| 车辆跟踪(高精度) | 31.8ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_ppvehicle.zip) | 182M | -| 车辆跟踪(轻量级) | 21.0ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_s_36e_ppvehicle.zip) | 27M | -| 闯入识别 | 31.8ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_ppvehicle.zip) | 多目标跟踪:182M | +| 车辆检测(高精度) | 25.7ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_ppvehicle.zip) | 182M | +| 车辆检测(轻量级) | 13.2ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_s_36e_ppvehicle.zip) | 27M | +| 车辆跟踪(高精度) | 40ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_l_36e_ppvehicle.zip) | 182M | +| 车辆跟踪(轻量级) | 25ms | [多目标跟踪](https://bj.bcebos.com/v1/paddledet/models/pipeline/mot_ppyoloe_s_36e_ppvehicle.zip) | 27M | +| 车牌识别 | 4.68ms | [车牌检测](https://bj.bcebos.com/v1/paddledet/models/pipeline/ch_PP-OCRv3_det_infer.tar.gz)
[车牌字符识别](https://bj.bcebos.com/v1/paddledet/models/pipeline/ch_PP-OCRv3_rec_infer.tar.gz) | 车牌检测:3.9M
车牌字符识别: 12M | +| 车辆属性 | 7.31ms | [车辆属性](https://bj.bcebos.com/v1/paddledet/models/pipeline/vehicle_attribute_model.zip) | 7.2M | + 下载模型后,解压至`./output_inference`文件夹。 @@ -97,7 +99,7 @@ VEHICLE_ATTR: **注意:** - 如果用户需要实现不同任务,可以在配置文件对应enable选项设置为True。 -- 如果用户仅需要修改模型文件路径,可以在命令行中加入 `--model_dir det=ppyoloe/` 即可,也可以手动修改配置文件中的相应模型路径,详细说明参考下方参数说明文档。 +- 如果用户仅需要修改模型文件路径,可以在命令行中--config后面紧跟着 `-o MOT.model_dir=ppyoloe/` 进行修改即可,也可以手动修改配置文件中的相应模型路径,详细说明参考下方参数说明文档。 ## 预测部署 @@ -111,7 +113,7 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_ppv # 车辆跟踪,指定配置文件路径,模型路径和测试视频,在配置文件```deploy/pipeline/config/infer_cfg_ppvehicle.yml```中的MOT部分enable设置为```True``` # 命令行中指定的模型路径优先级高于配置文件 -python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_ppvehicle.yml --video_file=test_video.mp4 --device=gpu --model_dir det=ppyoloe/ [--run_mode trt_fp16] +python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_ppvehicle.yml --video_file=test_video.mp4 --device=gpu [--run_mode trt_fp16] # 车辆属性识别,指定配置文件路径和测试视频,在配置文件```deploy/pipeline/config/infer_cfg_ppvehicle.yml```中的ATTR部分enable设置为```True``` python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_ppvehicle.yml --video_file=test_video.mp4 --device=gpu [--run_mode trt_fp16] @@ -130,7 +132,6 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_ppv |-------|-------|----------| | --config | Yes | 配置文件路径 | | -o | Option | 覆盖配置文件中对应的配置 | -| --model_dir | Option | 各任务模型路径,优先级高于配置文件, 例如`--model_dir det=better_det/ attr=better_attr/`| | --image_file | Option | 需要预测的图片 | | --image_dir | Option | 要预测的图片文件夹路径 | | --video_file | Option | 需要预测的视频,或者rtsp流地址 | diff --git a/deploy/pipeline/docs/tutorials/pphuman_action.md b/deploy/pipeline/docs/tutorials/pphuman_action.md index cf0c5af50..ee49282eb 100644 --- a/deploy/pipeline/docs/tutorials/pphuman_action.md +++ b/deploy/pipeline/docs/tutorials/pphuman_action.md @@ -60,12 +60,12 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pph 3. 若修改模型路径,有以下两种方式: - ```./deploy/pipeline/config/infer_cfg_pphuman.yml```下可以配置不同模型路径,关键点模型和摔倒行为识别模型分别对应`KPT`和`SKELETON_ACTION`字段,修改对应字段下的路径为实际期望的路径即可。 - - 命令行中增加`--model_dir`修改模型路径: + - 命令行中--config后面紧跟着增加`-o KPT.model_dir=xxx SKELETON_ACTION.model_dir=xxx `修改模型路径: ```python python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pphuman.yml \ + -o KPT.model_dir=./dark_hrnet_w32_256x192 SKELETON_ACTION.model_dir=./STGCN\ --video_file=test_video.mp4 \ - --device=gpu \ - --model_dir kpt=./dark_hrnet_w32_256x192 action=./STGCN + --device=gpu ``` 4. 启动命令中的完整参数说明,请参考[参数说明](./PPHuman_QUICK_STARTED.md)。 diff --git a/deploy/pipeline/docs/tutorials/pphuman_action_en.md b/deploy/pipeline/docs/tutorials/pphuman_action_en.md index 943a5c567..3eab1d447 100644 --- a/deploy/pipeline/docs/tutorials/pphuman_action_en.md +++ b/deploy/pipeline/docs/tutorials/pphuman_action_en.md @@ -72,13 +72,13 @@ SKELETON_ACTION: # Config for skeleton-based action recognition model 3. There are two ways to modify the model path: - In ```./deploy/pipeline/config/infer_cfg_pphuman.yml```, you can configurate different model paths,which is proper only if you match keypoint models and action recognition models with the fields of `KPT` and `SKELETON_ACTION` respectively, and modify the corresponding path of each field into the expected path. - - Add `--model_dir` in the command line to revise the model path: + - Add `-o KPT.model_dir=xxx SKELETON_ACTION.model_dir=xxx ` in the command line following the --config to change the model path: ```python - python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pphuman.yml \ - --video_file=test_video.mp4 \ - --device=gpu \ - --model_dir kpt=./dark_hrnet_w32_256x192 action=./STGCN +python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pphuman.yml \ + -o KPT.model_dir=./dark_hrnet_w32_256x192 SKELETON_ACTION.model_dir=./STGCN\ + --video_file=test_video.mp4 \ + --device=gpu ``` 4. For detailed parameter description, please refer to [Parameter Description](./PPHuman_QUICK_STARTED.md) diff --git a/deploy/pipeline/docs/tutorials/pphuman_attribute.md b/deploy/pipeline/docs/tutorials/pphuman_attribute.md index 16109606c..5e5f1dc61 100644 --- a/deploy/pipeline/docs/tutorials/pphuman_attribute.md +++ b/deploy/pipeline/docs/tutorials/pphuman_attribute.md @@ -59,12 +59,12 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pph 4. 若修改模型路径,有以下两种方式: - 方法一:```./deploy/pipeline/config/infer_cfg_pphuman.yml```下可以配置不同模型路径,属性识别模型修改ATTR字段下配置 - - 方法二:命令行中增加`--model_dir`修改模型路径: + - 方法二:命令行中--config后面紧跟着增加`-o ATTR.model_dir`修改模型路径: ```python -python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pphuman.yml \ +python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pphuman.yml + -o ATTR.model_dir=output_inference/PPLCNet_x1_0_person_attribute_945_infer/\ --video_file=test_video.mp4 \ - --device=gpu \ - --model_dir attr=output_inference/PPLCNet_x1_0_person_attribute_945_infer/ + --device=gpu ``` 测试效果如下: diff --git a/deploy/pipeline/docs/tutorials/pphuman_attribute_en.md b/deploy/pipeline/docs/tutorials/pphuman_attribute_en.md index 70c55de0e..fb402f757 100644 --- a/deploy/pipeline/docs/tutorials/pphuman_attribute_en.md +++ b/deploy/pipeline/docs/tutorials/pphuman_attribute_en.md @@ -55,12 +55,12 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pph 4. If you want to change the model path, there are two methods: - The first: In ```./deploy/pipeline/config/infer_cfg_pphuman.yml``` you can configurate different model paths. In attribute recognition models, you can modify the configuration in the field of ATTR. - - The second: Add `--model_dir` in the command line to change the model path: + - The second: Add `-o ATTR.model_dir` in the command line following the --config to change the model path: ```python python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pphuman.yml \ + -o ATTR.model_dir=output_inference/PPLCNet_x1_0_person_attribute_945_infer/\ --video_file=test_video.mp4 \ - --device=gpu \ - --model_dir attr=output_inference/PPLCNet_x1_0_person_attribute_945_infer/ + --device=gpu ``` The test result is: diff --git a/deploy/pipeline/docs/tutorials/pphuman_mot.md b/deploy/pipeline/docs/tutorials/pphuman_mot.md index 13a6c3f05..6380ffbbd 100644 --- a/deploy/pipeline/docs/tutorials/pphuman_mot.md +++ b/deploy/pipeline/docs/tutorials/pphuman_mot.md @@ -39,15 +39,15 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pph 4. 若修改模型路径,有以下两种方式: - ```./deploy/pipeline/config/infer_cfg_pphuman.yml```下可以配置不同模型路径,检测和跟踪模型分别对应`DET`和`MOT`字段,修改对应字段下的路径为实际期望的路径即可。 - - 命令行中增加`--model_dir`修改模型路径: + - 命令行中--config后面紧跟着增加`-o MOT.model_dir`修改模型路径: ```python python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pphuman.yml \ + -o MOT.model_dir=ppyoloe/\ --video_file=test_video.mp4 \ --device=gpu \ --region_type=horizontal \ --do_entrance_counting \ - --draw_center_traj \ - --model_dir det=ppyoloe/ + --draw_center_traj ``` **注意:** diff --git a/deploy/pipeline/docs/tutorials/pphuman_mot_en.md b/deploy/pipeline/docs/tutorials/pphuman_mot_en.md index c66ad6172..06e7ab014 100644 --- a/deploy/pipeline/docs/tutorials/pphuman_mot_en.md +++ b/deploy/pipeline/docs/tutorials/pphuman_mot_en.md @@ -39,16 +39,16 @@ python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pph 4. There are two ways to modify the model path: - In `./deploy/pipeline/config/infer_cfg_pphuman.yml`, you can configurate different model paths,which is proper only if you match keypoint models and action recognition models with the fields of `DET` and `MOT` respectively, and modify the corresponding path of each field into the expected path. - - Add `--model_dir` in the command line to revise the model path: + - Add `-o MOT.model_dir` in the command line following the --config to change the model path: ```python python deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pphuman.yml \ + -o MOT.model_dir=ppyoloe/\ --video_file=test_video.mp4 \ --device=gpu \ --region_type=horizontal \ --do_entrance_counting \ - --draw_center_traj \ - --model_dir det=ppyoloe/ + --draw_center_traj ``` **Note:** diff --git a/deploy/pipeline/docs/tutorials/pphuman_mtmct.md b/deploy/pipeline/docs/tutorials/pphuman_mtmct.md index 894c18ee0..e39d53fbd 100644 --- a/deploy/pipeline/docs/tutorials/pphuman_mtmct.md +++ b/deploy/pipeline/docs/tutorials/pphuman_mtmct.md @@ -18,10 +18,9 @@ python3 deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pp ```python python3 deploy/pipeline/pipeline.py - --config deploy/pipeline/config/infer_cfg_pphuman.yml + --config deploy/pipeline/config/infer_cfg_pphuman.yml -o REID.model_dir=reid_best/ --video_dir=[your_video_file_directory] --device=gpu - --model_dir reid=reid_best/ ``` ## 方案说明 diff --git a/deploy/pipeline/docs/tutorials/pphuman_mtmct_en.md b/deploy/pipeline/docs/tutorials/pphuman_mtmct_en.md index 0321d2a52..f67c1b67e 100644 --- a/deploy/pipeline/docs/tutorials/pphuman_mtmct_en.md +++ b/deploy/pipeline/docs/tutorials/pphuman_mtmct_en.md @@ -18,10 +18,9 @@ python3 deploy/pipeline/pipeline.py --config deploy/pipeline/config/infer_cfg_pp ```python python3 deploy/pipeline/pipeline.py - --config deploy/pipeline/config/infer_cfg_pphuman.yml + --config deploy/pipeline/config/infer_cfg_pphuman.yml -o REID.model_dir=reid_best/ --video_dir=[your_video_file_directory] --device=gpu - --model_dir reid=reid_best/ ``` ## Intorduction to the Solution diff --git a/deploy/pipeline/pipe_utils.py b/deploy/pipeline/pipe_utils.py index 8cc863aa5..e17f8aeab 100644 --- a/deploy/pipeline/pipe_utils.py +++ b/deploy/pipeline/pipe_utils.py @@ -88,7 +88,8 @@ class PipeTimer(Times): for k, v in self.module_time.items(): v_time = round(v.value(), 4) if v_time > 0 and k in ['det', 'mot', 'video_action']: - print("{} time(ms): {}".format(k, v_time * 1000)) + print("{} time(ms): {}; per frame average time(ms): {}".format( + k, v_time * 1000, v_time * 1000 / self.img_num)) elif v_time > 0: print("{} time(ms): {}; per trackid average time(ms): {}". format(k, v_time * 1000, v_time * 1000 / self.track_num)) diff --git a/deploy/pipeline/pipeline.py b/deploy/pipeline/pipeline.py index da2489682..3f0b8ce4a 100644 --- a/deploy/pipeline/pipeline.py +++ b/deploy/pipeline/pipeline.py @@ -465,6 +465,7 @@ class PipePredictor(object): self.cfg['crop_thresh']) if i > self.warmup_frame: self.pipe_timer.module_time['det'].end() + self.pipe_timer.track_num += len(det_res['boxes']) self.pipeline_res.update(det_res, 'det') if self.with_human_attr: diff --git a/deploy/pipeline/ppvehicle/vehicle_plateutils.py b/deploy/pipeline/ppvehicle/vehicle_plateutils.py index 4a7b792da..8a93c945c 100644 --- a/deploy/pipeline/ppvehicle/vehicle_plateutils.py +++ b/deploy/pipeline/ppvehicle/vehicle_plateutils.py @@ -139,6 +139,7 @@ def create_predictor(args, cfg, mode): min_input_shape = {"x": [1, 3, imgH, 10]} max_input_shape = {"x": [batch_size, 3, imgH, 2304]} opt_input_shape = {"x": [batch_size, 3, imgH, 320]} + config.exp_disable_tensorrt_ops(["transpose2"]) elif mode == "cls": min_input_shape = {"x": [1, 3, 48, 10]} max_input_shape = {"x": [batch_size, 3, 48, 1024]} diff --git a/docs/images/pphumanv2.png b/docs/images/pphumanv2.png index 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