From 01f5042e6113ab76892bd37513e6d7e03817d2e4 Mon Sep 17 00:00:00 2001 From: littletomatodonkey Date: Thu, 17 Sep 2020 14:49:41 +0000 Subject: [PATCH] fix typo --- README_en.md | 13 +++++-------- docs/en/update_history_en.md | 2 +- 2 files changed, 6 insertions(+), 9 deletions(-) diff --git a/README_en.md b/README_en.md index 8f3c0221..3e76dd17 100644 --- a/README_en.md +++ b/README_en.md @@ -8,7 +8,7 @@ PaddleClas is a toolset for image classification tasks prepared for the industry **Recent update** -- 2020.07.17 Add `HRNet_W48_C_ssld` pretrained model, whose Top-1 Acc on ImageNet1k dataset reaches 83.62%. Add `ResNet34_vd_ssld` pretrained model, whose Top-1 Acc on ImageNet1k dataset reaches 79.72%. +- 2020.09.17 Add `HRNet_W48_C_ssld` pretrained model, whose Top-1 Acc on ImageNet1k dataset reaches 83.62%. Add `ResNet34_vd_ssld` pretrained model, whose Top-1 Acc on ImageNet1k dataset reaches 79.72%. - 2020.09.07 Add `HRNet_W18_C_ssld` pretrained model, whose Top-1 Acc on ImageNet1k dataset reaches 81.16%. - 2020.07.14 Add `Res2Net200_vd_26w_4s_ssld` pretrained model, whose Top-1 Acc on ImageNet1k dataset reaches 85.13%. Add `Fix_ResNet50_vd_ssld_v2` pretrained model, whose Top-1 Acc on ImageNet1k dataset reaches 84.00%. - 2020.06.17 Add English documents. @@ -17,24 +17,21 @@ PaddleClas is a toolset for image classification tasks prepared for the industry - [more](./docs/zh_CN/update_history.md) -## Rich model zoo - - ## Features - Rich model zoo. Based on the ImageNet1k classification dataset, PaddleClas provides 24 series of classification network structures and training configurations, 122 models' pretrained weights and their evaluation metrics. -- SSLD Knowledge Distillation. Based on this SSLD distillation strategy, the accuracy of the distillation model is generally increased by more than 3%. +- SSLD Knowledge Distillation. Based on this SSLD distillation strategy, the accuracy of the distilled model is generally increased by more than 3%. - Data augmentation: PaddleClas provides detailed introduction of 8 data augmentation algorithms such as AutoAugment, Cutout, Cutmix, code reproduction and effect evaluation in a unified experimental environment. -- Pretrained model with 100,000 categories: Baidu self-developed and open sourced the `ResNet50_vd` model trained on a 100,000-category dataset. In some practical scenarios, the accuracy based on the pretrained weights can be increased by up to 30%. +- Pretrained model with 100,000 categories: Based on `ResNet50_vd` model, Baidu open sourced the `ResNet50_vd` pretrained model trained on a 100,000-category dataset. In some practical scenarios, the accuracy based on the pretrained weights can be increased by up to 30%. - A variety of training modes, including multi-machine training, mixed precision training, etc. - A variety of inference and deployment solutions, including TensorRT inference, Paddle-Lite inference, model service deployment, model quantification, Paddle Hub, etc. -- Support Linux, Windows, MacOS and other systems. +- Support Linux, Windows, macOS and other systems. ## Tutorials @@ -67,7 +64,7 @@ PaddleClas is a toolset for image classification tasks prepared for the industry - [Data augmentation](./docs/en/advanced_tutorials/image_augmentation/ImageAugment_en.md) - Applications - [Transfer learning](./docs/en/application/transfer_learning_en.md) - - [pretrained model with 100,000 categories](./docs/en/application/transfer_learning_en.md) + - [Pretrained model with 100,000 categories](./docs/en/application/transfer_learning_en.md) - [Generic object detection](./docs/en/application/object_detection_en.md) - FAQ - General image classification problems (coming soon) diff --git a/docs/en/update_history_en.md b/docs/en/update_history_en.md index 1f7a1c33..582b7634 100644 --- a/docs/en/update_history_en.md +++ b/docs/en/update_history_en.md @@ -1,6 +1,6 @@ # Release Notes -* 2020.09.07 +* 2020.09.17 * Add `HRNet_W48_C_ssld` pretrained model, whose Top-1 Acc on ImageNet1k dataset reaches 83.62%. * Add `ResNet34_vd_ssld` pretrained model, whose Top-1 Acc on ImageNet1k dataset reaches 79.72%. -- GitLab