提交 2f52adf9 编写于 作者: D dongshuilong

update pp-shituv2 doc

上级 4ac1fafb
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## 近期更新 ## 近期更新
- 🔥️ 发布[PP-ShiTuV2](./docs/zh_CN/PPShiTu/PPShiTuV2_introduction.md),recall1精度提升8个点,覆盖[20+识别场景](./docs/zh_CN/introduction/ppshitu_application_scenarios.md),新增[库管理工具](./deploy/shitu_index_manager/)[Android Demo](./docs/zh_CN/quick_start/quick_start_recognition.md)全新体验。 - 🔥️ 2022.9.14 晚上8:30 **商超零售新革命-生鲜智能结算产业应用**,扫码进群获取直播链接
<div align="center">
<img src="https://user-images.githubusercontent.com/11568925/189877049-d17ddcea-22d2-44ab-91fe-36d12af3add8.png" width = "200" height = "200"/>
</div>
- 🔥️ 2022.9.13发布[PP-ShiTuV2](./docs/zh_CN/PPShiTu/PPShiTuV2_introduction.md),recall1精度提升8个点,覆盖[20+识别场景](./docs/zh_CN/introduction/ppshitu_application_scenarios.md),新增[库管理工具](./deploy/shitu_index_manager/)[Android Demo](./docs/zh_CN/quick_start/quick_start_recognition.md)全新体验。
- 2022.9.4 新增[生鲜产品自主结算范例库](./docs/zh_CN/samples/Fresh_Food_Recogniiton/README.md),具体内容可以在AI Studio上体验。 - 2022.9.4 新增[生鲜产品自主结算范例库](./docs/zh_CN/samples/Fresh_Food_Recogniiton/README.md),具体内容可以在AI Studio上体验。
- 2022.6.15 发布[PULC超轻量图像分类实用方案](docs/zh_CN/PULC/PULC_train.md),CPU推理3ms,精度比肩SwinTransformer,覆盖人、车、OCR场景九大常见任务。 - 2022.6.15 发布[PULC超轻量图像分类实用方案](docs/zh_CN/PULC/PULC_train.md),CPU推理3ms,精度比肩SwinTransformer,覆盖人、车、OCR场景九大常见任务。
- 2022.5.23 新增[人员出入管理范例库](https://aistudio.baidu.com/aistudio/projectdetail/4094475),具体内容可以在 AI Studio 上体验。 - 2022.5.23 新增[人员出入管理范例库](https://aistudio.baidu.com/aistudio/projectdetail/4094475),具体内容可以在 AI Studio 上体验。
- 2022.5.20 上线[PP-HGNet](./docs/zh_CN/models/PP-HGNet.md), [PP-LCNetv2](./docs/zh_CN/models/PP-LCNetV2.md) - 2022.5.20 上线[PP-HGNet](./docs/zh_CN/models/PP-HGNet.md), [PP-LCNetv2](./docs/zh_CN/models/PP-LCNetV2.md)
- [more](./docs/zh_CN/others/update_history.md) - [more](./docs/zh_CN/others/update_history.md)
## 特性 ## 特性
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...@@ -24,30 +24,32 @@ PP-ShiTu对原数据集进行了`Gallery`库和`Query`库划分,并生成了 ...@@ -24,30 +24,32 @@ PP-ShiTu对原数据集进行了`Gallery`库和`Query`库划分,并生成了
| 场景 |示例图|场景简介|Recall@1|场景库下载地址|原数据集下载地址| | 场景 |示例图|场景简介|Recall@1|场景库下载地址|原数据集下载地址|
|:---:|:---:|:---:|:---:|:---:|:---:| |:---:|:---:|:---:|:---:|:---:|:---:|
| 球类 | <img src="../../images/ppshitu_application_scenarios/Ball.jpg" height = "100"> |各种球类识别 | 0.9769 | [Balls](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Balls.tar) | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/balls-image-classification) | | 花 | <img src="../../images/ppshitu_application_scenarios/104flowers.jpeg" height = "100"> |104种花细分类识别 | 0.9788 | [104flowers](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/104flowers.tar) | [原数据下载地址](https://www.kaggle.com/datasets/msheriey/104-flowers-garden-of-eden) |
| 狗识别 | <img src="../../images/ppshitu_application_scenarios/DogBreeds.jpg" height = "100"> | 狗细分类识别,包括69种狗的图像 | 0.9606 | [DogBreeds](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/DogBreeds.tar) | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/70-dog-breedsimage-data-set) |
| 宝石 | <img src="../../images/ppshitu_application_scenarios/Gemstones.jpg" height = "100"> | 宝石种类识别 | 0.9653 | [Gemstones](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Gemstones.tar) | [原数据下载地址](https://www.kaggle.com/datasets/lsind18/gemstones-images) |
| 动物 | <img src="../../images/ppshitu_application_scenarios/AnimalImageDataset.jpg" height = "100"> |各种动物识别 | 0.9078 | [AnimalImageDataset](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/AnimalImageDataset.tar) | [原数据下载地址](https://www.kaggle.com/datasets/iamsouravbanerjee/animal-image-dataset-90-different-animals) |
| 鸟类 | <img src="../../images/ppshitu_application_scenarios/Bird400.jpg" height = "100"> |鸟细分类识别,包括400种各种姿态的鸟类图像 | 0.9673 | [Bird400](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Bird400.tar) | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/100-bird-species) |
| 交通工具 | <img src="../../images/ppshitu_application_scenarios/Vechicles.jpg" height = "100"> |车、船等交通工具粗分类识别 | 0.9307 | [Vechicles](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Vechicles.tar) | [原数据下载地址](https://www.kaggle.com/datasets/rishabkoul1/vechicle-dataset) | | 交通工具 | <img src="../../images/ppshitu_application_scenarios/Vechicles.jpg" height = "100"> |车、船等交通工具粗分类识别 | 0.9307 | [Vechicles](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Vechicles.tar) | [原数据下载地址](https://www.kaggle.com/datasets/rishabkoul1/vechicle-dataset) |
| 花 | <img src="../../images/ppshitu_application_scenarios/104flowers.jpeg" height = "100"> |104种花细分类识别 | 0.9788 | [104flowers](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/104flowrs.tar) | [原数据下载地址](https://www.kaggle.com/datasets/msheriey/104-flowers-garden-of-eden) | | 动物 | <img src="../../images/ppshitu_application_scenarios/AnimalImageDataset.jpg" height = "100"> |各种动物识别 | 0.9078 | [AnimalImageDataset](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/AnimalImageDataset.tar) | [原数据下载地址](https://www.kaggle.com/datasets/iamsouravbanerjee/animal-image-dataset-90-different-animals) |
| 运动种类 | <img src="../../images/ppshitu_application_scenarios/100sports.jpg" height = "100"> |100种运动图像识别 | 0.9413 | [100sports](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/100sports.tar) | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/sports-classification) |
| 乐器 | <img src="../../images/ppshitu_application_scenarios/MusicInstruments.jpg" height = "100"> |30种不同乐器种类识别 | 0.9467 | [MusicInstruments](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/MusicInstruments.tar) | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/musical-instruments-image-classification) |
| 宝可梦 | <img src="../../images/ppshitu_application_scenarios/Pokemon.png" height = "100"> |宝可梦神奇宝贝识别 | 0.9236 | [Pokemon](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Pokemon.tar) | [原数据下载地址](https://www.kaggle.com/datasets/lantian773030/pokemonclassification) |
| 船 | <img src="../../images/ppshitu_application_scenarios/Boat.jpg" height = "100"> |船种类识别 |0.9242 | [Boat](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Boat.tar) | [原数据下载地址](https://www.kaggle.com/datasets/imsparsh/dockship-boat-type-classification) |
| 鞋子 | <img src="../../images/ppshitu_application_scenarios/Shoes.jpeg" height = "100"> |鞋子种类识别,包括靴子、拖鞋等 | 0.9000 | [Shoes](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Shoes.tar) | [原数据下载地址](https://www.kaggle.com/datasets/noobyogi0100/shoe-dataset) |
| 巴黎建筑 | <img src="../../images/ppshitu_application_scenarios/Paris.jpg" height = "100"> |巴黎著名建筑景点识别,如:巴黎铁塔、圣母院等 | 1.000 | [Paris](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Paris.tar) | [原数据下载地址](https://www.kaggle.com/datasets/skylord/oxbuildings) |
| 蝴蝶 | <img src="../../images/ppshitu_application_scenarios/Butterfly.jpg" height = "100"> |75种蝴蝶细分类识别 | 0.9360 | [Butterfly](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Butterfly.tar) | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/butterfly-images40-species) |
| 野外植物 | <img src="../../images/ppshitu_application_scenarios/WildEdiblePlants.jpg" height = "100"> |野外植物识别 | 0.9758 | [WildEdiblePlants](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/WildEdiblePlants.tar) | [原数据下载地址](https://www.kaggle.com/datasets/ryanpartridge01/wild-edible-plants) |
| 天气 | <img src="../../images/ppshitu_application_scenarios/WeatherImageRecognition.jpg" height = "100"> |各种天气场景识别,如:雨天、打雷、下雪等 | 0.9924 | [WeatherImageRecognition](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/WeatherImageRecognition.tar) | [原数据下载地址](https://www.kaggle.com/datasets/jehanbhathena/weather-dataset) |
| 坚果 | <img src="../../images/ppshitu_application_scenarios/TreeNuts.jpg" height = "100"> |各种坚果种类识别 | 0.9412 | [TreeNuts](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/TreeNuts.tar) | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/tree-nuts-image-classification) |
| 时装 | <img src="../../images/ppshitu_application_scenarios/FashionProductsImage.jpg" height = "100"> |首饰、挎包、化妆品等时尚商品识别 | 0.9555 | [FashionProductImageSmall](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/FashionProductImageSmall.tar) | [原数据下载地址](https://www.kaggle.com/datasets/paramaggarwal/fashion-product-images-small) | | 时装 | <img src="../../images/ppshitu_application_scenarios/FashionProductsImage.jpg" height = "100"> |首饰、挎包、化妆品等时尚商品识别 | 0.9555 | [FashionProductImageSmall](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/FashionProductImageSmall.tar) | [原数据下载地址](https://www.kaggle.com/datasets/paramaggarwal/fashion-product-images-small) |
| 垃圾 | <img src="../../images/ppshitu_application_scenarios/Garbage12.jpg" height = "100"> |12种垃圾分类识别 | 0.9845 | [Garbage12](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Garbage12.tar) | [原数据下载地址](https://www.kaggle.com/datasets/mostafaabla/garbage-classification) | | 球类 | <img src="../../images/ppshitu_application_scenarios/Ball.jpg" height = "100"> |各种球类识别 | 0.9769 | [Balls](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Balls.tar) | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/balls-image-classification) |
| 航拍场景 | <img src="../../images/ppshitu_application_scenarios/AID.jpg" height = "100"> |各种航拍场景识别,如机场、火车站等 | 0.9797 | [AID](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/AID.tar) | [原数据下载地址](https://www.kaggle.com/datasets/jiayuanchengala/aid-scene-classification-datasets) | | 狗识别 | <img src="../../images/ppshitu_application_scenarios/DogBreeds.jpg" height = "100"> | 狗细分类识别,包括69种狗的图像 | 0.9606 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/70-dog-breedsimage-data-set) |
| 蔬菜 | <img src="../../images/ppshitu_application_scenarios/Veg200.jpg" height = "100"> |各种蔬菜识别 | 0.8929 | [Veg200](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Veg200.tar) | [原数据下载地址](https://www.kaggle.com/datasets/zhaoyj688/vegfru) | | 宝石 | <img src="../../images/ppshitu_application_scenarios/Gemstones.jpg" height = "100"> | 宝石种类识别 | 0.9653 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/lsind18/gemstones-images) |
| 商标 | <img src="../../images/ppshitu_application_scenarios/Logo3K.jpg" height = "100"> |两千多种logo识别 | 0.9313 | [Logo3k](https://paddle-imagenet-models-name.bj.bcebos.com/dygraph/rec/data/PP-ShiTuV2_application_dataset/Logo3k.tar) | [原数据下载地址](https://github.com/Wangjing1551/LogoDet-3K-Dataset) | | 鸟类 | <img src="../../images/ppshitu_application_scenarios/Bird400.jpg" height = "100"> |鸟细分类识别,包括400种各种姿态的鸟类图像 | 0.9673 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/100-bird-species) |
| 运动种类 | <img src="../../images/ppshitu_application_scenarios/100sports.jpg" height = "100"> |100种运动图像识别 | 0.9413 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/sports-classification) |
| 乐器 | <img src="../../images/ppshitu_application_scenarios/MusicInstruments.jpg" height = "100"> |30种不同乐器种类识别 | 0.9467 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/musical-instruments-image-classification) |
| 宝可梦 | <img src="../../images/ppshitu_application_scenarios/Pokemon.png" height = "100"> |宝可梦神奇宝贝识别 | 0.9236 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/lantian773030/pokemonclassification) |
| 船 | <img src="../../images/ppshitu_application_scenarios/Boat.jpg" height = "100"> |船种类识别 |0.9242 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/imsparsh/dockship-boat-type-classification) |
| 鞋子 | <img src="../../images/ppshitu_application_scenarios/Shoes.jpeg" height = "100"> |鞋子种类识别,包括靴子、拖鞋等 | 0.9000 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/noobyogi0100/shoe-dataset) |
| 巴黎建筑 | <img src="../../images/ppshitu_application_scenarios/Paris.jpg" height = "100"> |巴黎著名建筑景点识别,如:巴黎铁塔、圣母院等 | 1.000 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/skylord/oxbuildings) |
| 蝴蝶 | <img src="../../images/ppshitu_application_scenarios/Butterfly.jpg" height = "100"> |75种蝴蝶细分类识别 | 0.9360 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/butterfly-images40-species) |
| 野外植物 | <img src="../../images/ppshitu_application_scenarios/WildEdiblePlants.jpg" height = "100"> |野外植物识别 | 0.9758 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/ryanpartridge01/wild-edible-plants) |
| 天气 | <img src="../../images/ppshitu_application_scenarios/WeatherImageRecognition.jpg" height = "100"> |各种天气场景识别,如:雨天、打雷、下雪等 | 0.9924 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/jehanbhathena/weather-dataset) |
| 坚果 | <img src="../../images/ppshitu_application_scenarios/TreeNuts.jpg" height = "100"> |各种坚果种类识别 | 0.9412 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/gpiosenka/tree-nuts-image-classification) |
| 垃圾 | <img src="../../images/ppshitu_application_scenarios/Garbage12.jpg" height = "100"> |12种垃圾分类识别 | 0.9845 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/mostafaabla/garbage-classification) |
| 航拍场景 | <img src="../../images/ppshitu_application_scenarios/AID.jpg" height = "100"> |各种航拍场景识别,如机场、火车站等 | 0.9797 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/jiayuanchengala/aid-scene-classification-datasets) |
| 蔬菜 | <img src="../../images/ppshitu_application_scenarios/Veg200.jpg" height = "100"> |各种蔬菜识别 | 0.8929 | 添加技术交流群后即可获得 | [原数据下载地址](https://www.kaggle.com/datasets/zhaoyj688/vegfru) |
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