DFace | Deep learning face detection and recognition | Machine Learning library
kandi X-RAY | DFace Summary
kandi X-RAY | DFace Summary
DFace is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow applications. DFace has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However DFace build file is not available. You can download it from GitHub.
DFace is an open source software for face detection and recognition. All features implemented by the pytorch (the facebook deeplearning framework). With PyTorch, we use a technique called reverse-mode auto-differentiation, which allows developer to change the way your network behaves arbitrarily with zero lag or overhead. DFace inherit these advanced characteristic, that make it dynamic and ease code review. DFace support GPU acceleration with NVIDIA cuda. We highly recommend you use the linux GPU version.It's very fast and extremely realtime. Our inspiration comes from several research papers on this topic, as well as current and past work such as Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks and face recognition topic FaceNet: A Unified Embedding for Face Recognition and Clustering.
DFace is an open source software for face detection and recognition. All features implemented by the pytorch (the facebook deeplearning framework). With PyTorch, we use a technique called reverse-mode auto-differentiation, which allows developer to change the way your network behaves arbitrarily with zero lag or overhead. DFace inherit these advanced characteristic, that make it dynamic and ease code review. DFace support GPU acceleration with NVIDIA cuda. We highly recommend you use the linux GPU version.It's very fast and extremely realtime. Our inspiration comes from several research papers on this topic, as well as current and past work such as Joint Face Detection and Alignment using Multi-task Cascaded Convolutional Networks and face recognition topic FaceNet: A Unified Embedding for Face Recognition and Clustering.
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DFace has a medium active ecosystem.
It has 1148 star(s) with 346 fork(s). There are 64 watchers for this library.
It had no major release in the last 12 months.
There are 32 open issues and 5 have been closed. On average issues are closed in 405 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of DFace is v0.5-sensible
Quality
DFace has 0 bugs and 108 code smells.
Security
DFace has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
DFace code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
DFace is licensed under the Apache-2.0 License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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DFace releases are available to install and integrate.
DFace has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions, examples and code snippets are available.
DFace saves you 1070 person hours of effort in developing the same functionality from scratch.
It has 2424 lines of code, 111 functions and 38 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed DFace and discovered the below as its top functions. This is intended to give you an instant insight into DFace implemented functionality, and help decide if they suit your requirements.
- Generate pnet data .
- Generate ground truth data .
- Detect RNet image .
- Generate image data .
- generate rnet data
- Generate sample data .
- Train an RNet .
- Train on a given model .
- Train the model .
- Visualize two images .
Get all kandi verified functions for this library.
DFace Key Features
No Key Features are available at this moment for DFace.
DFace Examples and Code Snippets
No Code Snippets are available at this moment for DFace.
Community Discussions
Trending Discussions on DFace
QUESTION
How to update a canvas in SWT every 100 milliseconds inside a KeyListener Java
Asked 2017-Dec-22 at 18:12
I'm writing a program which updates a canvas after every key press by regenerating a data structure (cube) and then painting this onto the canvas. If the user enters 'S' I want the canvas to display the cube after every turn (turn = one character of the solution string generated by the program) every 100ms and redraw this to the screen, have tried several different approaches but can't get it to work. This is my KeyListener code:
...ANSWER
Answered 2017-Dec-22 at 18:12You can't do updates in a loop like that because you must let the main SWT Display.readAndDispatch loop run since this is what actually updates the screen.
Instead use Display.timerExec to execute one step of the loop every 100ms:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install DFace
DFace has two major module, detection and recognition.In these two, We provide all tutorials about how to train a model and running. First setting a pytorch and cv2. We suggest Anaconda to make a virtual and independent python envirment.If you want to train on GPU,please install Nvidia cuda and cudnn.
Support
Based on cener loss or triplet loss implement the face conpare. Recommended Model is ResNet inception v2. Refer this Paper and FaceNetFace Anti-Spoofing, distinguish from face light and texture。Recomend with the LBP algorithm and SVM.3D mask Anti-Spoofing.Mobile first with caffe2 and c++.Tensor rt migration.Docker support, gpu version
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