FaceDetection_CNN | Implement Yahoo Paper : Multi-view Face Detection Using

by pengdada Python Version: Current License: No License

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kandi X-RAY | FaceDetection_CNN Summary

FaceDetection_CNN is a Python library. FaceDetection_CNN has no bugs, it has no vulnerabilities and it has low support. However FaceDetection_CNN build file is not available. You can download it from GitHub.

Implement Yahoo Paper: Multi-view Face Detection Using Deep Convolutional Neural Networks 1. Image Preprocess aflw dataset[1]. Use iou>=0.5 as positive, iou0.3 as negative. You should download the aflw dataset by yourself. 2. Fine-tune Alex-Net using AFLW dataset. The model is in Baidu Yun: or Google Drive: 3. Convert fully connected layers into convolutional layers by reshaping layer parameters, see [2], you can use the convert_full_conv() function in test.py for converting. 4. Get heat map for each scale of image. 5. Process heat map by using non-maximal suppression to accurately localize the faces..

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FaceDetection_CNN has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

FaceDetection_CNN has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of FaceDetection_CNN is current.

Quality

FaceDetection_CNN has no bugs reported.

Security

FaceDetection_CNN has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

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FaceDetection_CNN does not have a standard license declared.

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Without a license, all rights are reserved, and you cannot use the library in your applications.

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FaceDetection_CNN releases are not available. You will need to build from source code and install.

FaceDetection_CNN has no build file. You will be need to create the build yourself to build the component from source.

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FaceDetection_CNN Key Features

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FaceDetection_CNN Examples and Code Snippets

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Install FaceDetection_CNN

You can download it from GitHub.
You can use FaceDetection_CNN like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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