From 25da46eb89df922f4a619310b99ce893452c35fc Mon Sep 17 00:00:00 2001 From: AmberC0209 <55582609+AmberC0209@users.noreply.github.com> Date: Wed, 11 Dec 2024 12:47:38 +0800 Subject: [PATCH] update docs (#2629) --- .../doc_img_orientation_classification.md | 4 +- docs/support_list/model_list_npu.en.md | 22 ++++--- docs/support_list/model_list_npu.md | 3 +- docs/support_list/pipelines_list.en.md | 63 +++++++++++++++++++ docs/support_list/pipelines_list.md | 63 +++++++++++++++++++ 5 files changed, 142 insertions(+), 13 deletions(-) diff --git a/docs/module_usage/tutorials/ocr_modules/doc_img_orientation_classification.md b/docs/module_usage/tutorials/ocr_modules/doc_img_orientation_classification.md index ba65a0704..d3caa8f78 100644 --- a/docs/module_usage/tutorials/ocr_modules/doc_img_orientation_classification.md +++ b/docs/module_usage/tutorials/ocr_modules/doc_img_orientation_classification.md @@ -13,7 +13,7 @@ comments: true - + @@ -23,7 +23,7 @@ comments: true - + diff --git a/docs/support_list/model_list_npu.en.md b/docs/support_list/model_list_npu.en.md index 5fe92db5d..42f3920c9 100644 --- a/docs/support_list/model_list_npu.en.md +++ b/docs/support_list/model_list_npu.en.md @@ -360,13 +360,13 @@ PaddleX incorporates multiple pipelines, each containing several modules, and ea
模型Model Download Link模型模型下载链接 Top-1 Acc（%） GPU推理耗时（ms） CPU推理耗时 (ms)
PP-LCNet_x1_0_doc_oriInference Model/Trained ModelPP-LCNet_x1_0_doc_ori推理模型/训练模型 99.06 3.84845 9.23735
Note: The above accuracy metrics refer to Top-1 Accuracy on the [ImageNet-1k](https://www.image-net.org/index.php) validation set. -## [图像多标签分类模块](../module_usage/tutorials/cv_modules/image_multilabel_classification.md) +## [Image Multi-label Classification Module](../module_usage/tutorials/cv_modules/image_multilabel_classification.en.md) - - - + + + @@ -374,24 +374,26 @@ PaddleX incorporates multiple pipelines, each containing several modules, and ea - + + - + - + - - + +
模型名称mAP（%）模型存储大小Model NamemAP (%)Model Storage Size Model Download Link
CLIP_vit_base_patch16_448_ML 89.15 325.6 MInference Model/Trained Model
Inference Model/Training Model
PP-HGNetV2-B0_ML 80.98 39.6 MInference Model/Training Model
PP-HGNetV2-B4_ML 87.96 88.5 MInference Model/Trained Model
Inference Model/Training Model
PP-HGNetV2-B6_ML91.2591.06 286.5 MInference Model/Trained Model
Inference Model/Trained Model
Inference Model/Training Model
-注：以上精度指标为 [COCO2017](https://cocodataset.org/#home) 的多标签分类任务mAP。 +Note: The above accuracy metrics are for the multi-label classification task mAP of [COCO2017](https://cocodataset.org/#home). + ## Object Detection Module diff --git a/docs/support_list/model_list_npu.md b/docs/support_list/model_list_npu.md index b644af863..ebbc67e8b 100644 --- a/docs/support_list/model_list_npu.md +++ b/docs/support_list/model_list_npu.md @@ -379,6 +379,7 @@ PaddleX 内置了多条产线，每条产线都包含了若干模块，每个模 + @@ -389,7 +390,7 @@ PaddleX 内置了多条产线，每条产线都包含了若干模块，每个模 - +
PP-HGNetV2-B0_ML 80.98 39.6 M推理模型/训练模型
PP-HGNetV2-B4_ML 87.9691.06 286.5 M 推理模型/训练模型
推理模型/训练模型
注：以上精度指标为 [COCO2017](https://cocodataset.org/#home) 的多标签分类任务mAP。 diff --git a/docs/support_list/pipelines_list.en.md b/docs/support_list/pipelines_list.en.md index 032496012..f47dcc74d 100644 --- a/docs/support_list/pipelines_list.en.md +++ b/docs/support_list/pipelines_list.en.md @@ -306,6 +306,69 @@ comments: true Text Recognition + + General Image Recognition + Subject Detection + None + The general image recognition production line is designed to address open-domain target localization and recognition issues. It can effectively identify and differentiate various target objects in different environments and conditions, making it widely applicable in autonomous driving, intelligent security, medical image analysis, and industrial automation, among other fields. + + + + + + Image Features + + + Pedestrian Attribute Recognition + Pedestrian Detection + None + Pedestrian attribute recognition is a key function in computer vision systems used to locate and tag specific features of pedestrians in images or videos, such as gender, age, clothing color, and style. + + + + + + Pedestrian Attribute Recognition + + + Vehicle Attribute Recognition + Vehicle Detection + None + Vehicle attribute recognition is an important component of computer vision systems. Its main task is to locate and tag specific attributes of vehicles in images or videos, such as vehicle type, color, and license plate number. This task not only requires accurate detection of vehicles but also the recognition of detailed attribute information for each vehicle. + + + + + + Vehicle Attribute Recognition + + + Face Recognition + Face Detection + None + The facial recognition task is an important component of the computer vision field, aiming to realize automatic personal identity recognition through the analysis and comparison of facial features. + + + + + + Face Features + ## 2. Featured Pipelines diff --git a/docs/support_list/pipelines_list.md b/docs/support_list/pipelines_list.md index bc0a84eff..446140d07 100644 --- a/docs/support_list/pipelines_list.md +++ b/docs/support_list/pipelines_list.md @@ -308,6 +308,69 @@ comments: true 文本识别 + + 通用图像识别 + 主体检测 + 暂无 + 通用图像识别产线旨在解决开放域目标定位及识别问题，通用图像识别产线能够在不同的环境和条件下有效识别和区分各种目标物体，从而广泛应用于自动驾驶、智能安防、医疗影像分析以及工业自动化等多个领域。 + + + + + + 图像特征 + + + 行人属性识别 + 行人检测 + 暂无 + 行人属性识别是计算机视觉系统中的关键功能，用于在图像或视频中定位并标记行人的特定特征，如性别、年龄、衣物颜色和款式等。 + + + + + + 行人属性识别 + + + 车辆属性识别 + 车辆检测 + 暂无 + 车辆属性识别是计算机视觉系统中的重要组成部分，其主要任务是在图像或视频中定位并标记出车辆的特定属性，如车辆类型、颜色、车牌号等。该任务不仅要求准确检测出车辆，还需识别每辆车的详细属性信息。 + + + + + + 车辆属性识别 + + + 人脸识别 + 人脸检测 + 暂无 + 人脸识别任务是计算机视觉领域的重要组成部分，旨在通过分析和比较人脸特征，实现对个人身份的自动识别。 + + + + + + 人脸特征 +