deepoptics | Project web-site with more infos and videos : link
kandi X-RAY | deepoptics Summary
kandi X-RAY | deepoptics Summary
deepoptics is a Python library. deepoptics has no bugs, it has no vulnerabilities and it has low support. However deepoptics build file is not available. You can download it from GitHub.
Project web-site with more infos and videos: link. Link to our group website with other VR, AR, and computational imaging projects: link.
Project web-site with more infos and videos: link. Link to our group website with other VR, AR, and computational imaging projects: link.
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Quality
Security
License
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Support
deepoptics has a low active ecosystem.
It has 55 star(s) with 20 fork(s). There are 6 watchers for this library.
It had no major release in the last 6 months.
There are 1 open issues and 0 have been closed. On average issues are closed in 230 days. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of deepoptics is current.
Quality
deepoptics has 0 bugs and 0 code smells.
Security
deepoptics has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
deepoptics code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
deepoptics does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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deepoptics releases are not available. You will need to build from source code and install.
deepoptics has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions are not available. Examples and code snippets are available.
deepoptics saves you 604 person hours of effort in developing the same functionality from scratch.
It has 1406 lines of code, 68 functions and 10 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed deepoptics and discovered the below as its top functions. This is intended to give you an instant insight into deepoptics implemented functionality, and help decide if they suit your requirements.
- Fit the model
- Get the data loss
- Build the graph
- Get training queue
- Calculate the PSFs
- Downsampling of an image
- Calculate circular aperture
- Attach summaries to a given variable
- Propagate the input field at a given distance
- Transposed tf fft
- Transpensor_tensor_tensor
- Get the PSFs for each point source
- Propagate the input field
- Create a zernike element
- Create a Fourier element
- Wrapper function for fft shift
- Build a height map element
- Get sensor image
- Image convolutional layer
- Convolution layer with depth - depersion
- Creates a fourier height map
- Build the height map
- Creates a wall height map
- Calculate the wavefront phase of a spherical wavefront
- Creates a laplace regularizer
- Build the phase map
Get all kandi verified functions for this library.
deepoptics Key Features
No Key Features are available at this moment for deepoptics.
deepoptics Examples and Code Snippets
No Code Snippets are available at this moment for deepoptics.
Community Discussions
No Community Discussions are available at this moment for deepoptics.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install deepoptics
You can download it from GitHub.
You can use deepoptics 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.
You can use deepoptics 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.
Support
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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