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modules/image/classification/DriverStatusRecognition/README.md
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| DriverStatusRecognition | ||
| 类别 图像 - 图像分类 | ||
| 网络 MobileNetV3_small_ssld | ||
| 数据集 分心司机检测数据集 | ||
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| # 模型概述 | ||
| 驾驶员状态识别（DriverStatusRecognition），该模型可挖掘出人在疲劳状态下的表情特征，然后将这些定性的表情特征进行量化，提取出面部特征点及特征指标作为判断依据，再结合实验数据总结出基于这些参数的识别方法，最后输入获取到的状态数据进行识别和判断。该PaddleHub Module支持API预测及命令行预测。 | ||
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| # 选择模型版本进行安装 | ||
| $ hub install DriverStatusRecognition==1.0.0 | ||
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| # 在线体验 | ||
| [AI Studio快速体验](https://aistudio.baidu.com/aistudio/projectdetail/1649513) | ||
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| # 命令行预测示例 | ||
| $ hub run DriverStatusRecognition --image 1.png --use_gpu True | ||
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| # Module API说明 | ||
| ## def predict(data) | ||
| 驾驶员状态识别预测接口，输入一张图像，输出该图像上驾驶员的状态 | ||
| ### 参数 | ||
| - data：dict类型，key为image，str类型，value为待检测的图片路径，list类型。 | ||
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| ### 返回 | ||
| - result：list类型，每个元素为对应输入图片的预测结果。预测结果为dict类型，key为该图片分类结果label，value为该label对应的概率 | ||
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| # 代码示例 | ||
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| ## API调用 | ||
| ~~~ | ||
| import cv2 | ||
| import paddlehub as hub | ||
| module = hub.Module(directory='DriverStatusRecognition') # 一行代码实现模型调用 | ||
| images = [cv2.imread('work/imgs/test/img_1622.jpg'), cv2.imread('work/imgs/test/img_14165.jpg'), cv2.imread('work/imgs/test/img_47183.jpg')] | ||
| results = module.predict(images=images) | ||
| for result in results: | ||
| print(result) | ||
| ~~~ | ||
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| ## 命令行调用 | ||
| ~~~ | ||
| $ hub run DriverStatusRecognition --image 1.png --use_gpu True | ||
| ~~~ | ||
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| # 效果展示 | ||
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| ## 原图 | ||
| <img src="/docs/imgs/Readme_Related/Image_Classification_Drivers.png"> | ||
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| ## 输出结果 | ||
| ~~~ | ||
| [{'category_id': 5, 'category': 'ch5', 'score': 0.47390476}] | ||
| [{'category_id': 2, 'category': 'ch2', 'score': 0.99997914}] | ||
| [{'category_id': 1, 'category': 'ch1', 'score': 0.99996376}] | ||
| ~~~ | ||
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| # 贡献者 | ||
| 郑博培、彭兆帅 | ||
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| # 依赖 | ||
| paddlepaddle >= 2.0.0<br> | ||
| paddlehub >= 2.0.0 | ||
| # DriverStatusRecognition | ||
|
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||
| |模型名称|DriverStatusRecognition| | ||
| | :--- | :---: | | ||
| |类别|图像-图像分类| | ||
| |网络|MobileNetV3_small_ssld| | ||
| |数据集|分心司机检测数据集| | ||
| |是否支持Fine-tuning|否| | ||
| |模型大小|6MB| | ||
| |最新更新日期|-| | ||
| |数据指标|-| | ||
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|
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| ## 一、模型基本信息 | ||
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|
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| - ### 模型介绍 | ||
|
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| - 驾驶员状态识别（DriverStatusRecognition），该模型可挖掘出人在疲劳状态下的表情特征，然后将这些定性的表情特征进行量化，提取出面部特征点及特征指标作为判断依据，再结合实验数据总结出基于这些参数的识别方法，最后输入获取到的状态数据进行识别和判断。该PaddleHub Module支持API预测及命令行预测。 | ||
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| ## 二、安装 | ||
|
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| - ### 1、环境依赖 | ||
|
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| - paddlepaddle >= 2.0.0 | ||
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| - paddlehub >= 2.0.0 | [如何安装paddlehub](../../../../docs/docs_ch/get_start/installation.rst) | ||
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| - paddlex >= 1.3.7 | ||
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| - ### 2、安装 | ||
|
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| - ```shell | ||
| $ hub install DriverStatusRecognition | ||
| ``` | ||
| - 如您安装时遇到问题，可参考：[零基础windows安装](../../../../docs/docs_ch/get_start/windows_quickstart.md) | ||
| | [零基础Linux安装](../../../../docs/docs_ch/get_start/linux_quickstart.md) | [零基础MacOS安装](../../../../docs/docs_ch/get_start/mac_quickstart.md) | ||
|
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| - ### 3、在线体验 | ||
| [AI Studio 快速体验](https://aistudio.baidu.com/aistudio/projectdetail/1649513) | ||
|
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| ## 三、模型API预测 | ||
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| - ### 1、命令行预测 | ||
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| - ```shell | ||
| $ hub run DriverStatusRecognition --input_path /PATH/TO/IMAGE | ||
| ``` | ||
| - 通过命令行方式实现图像分类模型的调用，更多请见 [PaddleHub命令行指令](../../../../docs/docs_ch/tutorial/cmd_usage.rst) | ||
|
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| - ### 2、预测代码示例 | ||
|
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| - ```python | ||
| import paddlehub as hub | ||
| import cv2 | ||
| classifier = hub.Module(name="DriverStatusRecognition") | ||
| images = [cv2.imread('/PATH/TO/IMAGE')] | ||
| results = classifier.predict(images=images) | ||
| for result in results: | ||
| print(result) | ||
| ``` | ||
| - ### 3、API | ||
| - ```python | ||
| def predict(images) | ||
| ``` | ||
| - 分类接口API。 | ||
| - **参数** | ||
| - images：list类型，待检测的图像。 | ||
| - **返回** | ||
| - result：list类型，每个元素为对应输入图片的预测结果。 | ||
| ## 四、更新历史 | ||
| * 1.0.0 | ||
| 初始发布 | ||
| - ```shell | ||
| $ hub install DriverStatusRecognition==1.0.0 | ||
| ``` |
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modules/image/classification/DriverStatusRecognition/requirements.txt
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| paddlex==1.3.7 | ||
| chardet |
154 changes: 90 additions & 64 deletions
154
modules/image/classification/SnakeIdentification/README.md
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| Original file line number | Diff line number | Diff line change |
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| SnakeIdentification | ||
| 类别 图像 - 图像分类 | ||
| 网络 ResNet50_vd_ssld | ||
| 数据集 蛇种数据集 | ||
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| # 模型概述 | ||
| 蛇种识别（SnakeIdentification），该模型可准确识别蛇的种类，并精准判断蛇的毒性。该PaddleHub Module支持API预测及命令行预测。 | ||
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| # 选择模型版本进行安装 | ||
| $ hub install SnakeIdentification==1.0.0 | ||
|
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| # 在线体验 | ||
| [AI Studio快速体验](https://aistudio.baidu.com/aistudio/projectdetail/1646951) | ||
|
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| # 命令行预测示例 | ||
| $ hub run SnakeIdentification --image 1.png --use_gpu True | ||
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| # Module API说明 | ||
| ## def predict(data) | ||
| 蛇种识别预测接口，输入一张图像，输出该图像上蛇的类别 | ||
| ### 参数 | ||
| - data：dict类型，key为image，str类型，value为待检测的图片路径，list类型。 | ||
|
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| ### 返回 | ||
| - result：list类型，每个元素为对应输入图片的预测结果。预测结果为dict类型，key为该图片分类结果label，value为该label对应的概率 | ||
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| # 代码示例 | ||
|
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| ## API调用 | ||
| ~~~ | ||
| import cv2 | ||
| import paddlehub as hub | ||
| module = hub.Module(name="SnakeIdentification") | ||
| images = [cv2.imread('snake_data/class_1/2421.jpg')] | ||
| # execute predict and print the result | ||
| results = module.predict(images=images) | ||
| for result in results: | ||
| print(result) | ||
| ~~~ | ||
|
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| ## 命令行调用 | ||
| ~~~ | ||
| $ hub run SnakeIdentification --image 1.png --use_gpu True | ||
| ~~~ | ||
|
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| # 效果展示 | ||
|
|
||
| ## 原图 | ||
| <img src="/docs/imgs/Readme_Related/Image_Classification_Snake.png"> | ||
|
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| ## 输出结果 | ||
| ~~~ | ||
| [{'category_id': 0, 'category': '水蛇', 'score': 0.9999205}] | ||
| ~~~ | ||
|
|
||
| # 贡献者 | ||
| 郑博培、彭兆帅 | ||
|
|
||
| # 依赖 | ||
| paddlepaddle >= 2.0.0<br> | ||
| paddlehub >= 2.0.0 | ||
| # SnakeIdentification | ||
|
|
||
| |模型名称|SnakeIdentification| | ||
| | :--- | :---: | | ||
| |类别|图像-图像分类| | ||
| |网络|ResNet50_vd_ssld| | ||
| |数据集|蛇种数据集| | ||
| |是否支持Fine-tuning|否| | ||
| |模型大小|84MB| | ||
| |最新更新日期|-| | ||
| |数据指标|-| | ||
|
|
||
|
|
||
| ## 一、模型基本信息 | ||
|
|
||
|
|
||
|
|
||
| - ### 模型介绍 | ||
|
|
||
| - 蛇种识别（SnakeIdentification），该模型可准确识别蛇的种类，并精准判断蛇的毒性。该PaddleHub Module支持API预测及命令行预测。 | ||
|
|
||
| ## 二、安装 | ||
|
|
||
| - ### 1、环境依赖 | ||
|
|
||
| - paddlepaddle >= 2.0.0 | ||
|
|
||
| - paddlehub >= 2.0.0 | [如何安装paddlehub](../../../../docs/docs_ch/get_start/installation.rst) | ||
|
|
||
| - paddlex >= 1.3.7 | ||
|
|
||
|
|
||
| - ### 2、安装 | ||
|
|
||
| - ```shell | ||
| $ hub install SnakeIdentification | ||
| ``` | ||
| - 如您安装时遇到问题，可参考：[零基础windows安装](../../../../docs/docs_ch/get_start/windows_quickstart.md) | ||
| | [零基础Linux安装](../../../../docs/docs_ch/get_start/linux_quickstart.md) | [零基础MacOS安装](../../../../docs/docs_ch/get_start/mac_quickstart.md) | ||
|
|
||
| - ### 3、在线体验 | ||
| [AI Studio 快速体验](https://aistudio.baidu.com/aistudio/projectdetail/1646951) | ||
|
|
||
| ## 三、模型API预测 | ||
|
|
||
| - ### 1、命令行预测 | ||
|
|
||
| - ```shell | ||
| $ hub run SnakeIdentification --input_path /PATH/TO/IMAGE | ||
| ``` | ||
| - 通过命令行方式实现图像分类模型的调用，更多请见 [PaddleHub命令行指令](../../../../docs/docs_ch/tutorial/cmd_usage.rst) | ||
|
|
||
| - ### 2、预测代码示例 | ||
|
|
||
| - ```python | ||
| import paddlehub as hub | ||
| import cv2 | ||
| classifier = hub.Module(name="SnakeIdentification") | ||
| images = [cv2.imread('/PATH/TO/IMAGE')] | ||
| results = classifier.predict(images=images) | ||
| for result in results: | ||
| print(result) | ||
| ``` | ||
| - ### 3、API | ||
| - ```python | ||
| def predict(images) | ||
| ``` | ||
| - 分类接口API。 | ||
| - **参数** | ||
| - images：list类型，待检测的图像。 | ||
| - **返回** | ||
| - result：list类型，每个元素为对应输入图片的预测结果。 | ||
| ## 四、更新历史 | ||
| * 1.0.0 | ||
| 初始发布 | ||
| - ```shell | ||
| $ hub install SnakeIdentification==1.0.0 | ||
| ``` |
1 change: 1 addition & 0 deletions
1
modules/image/classification/SnakeIdentification/requirements.txt
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1 @@ | ||
| paddlex==1.3.7 |
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