AlphaMatting | Shared Sampling for Real-time Alpha Matting | Binary Executable Format library

by volvet C++ Version: Current License: No License

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kandi X-RAY | AlphaMatting Summary

AlphaMatting is a C++ library typically used in Programming Style, Binary Executable Format applications. AlphaMatting has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Implementation of Shared Sampling for Real-time Alpha Matting -

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AlphaMatting has a low active ecosystem.

It has 75 star(s) with 29 fork(s). There are 8 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of AlphaMatting is current.

Quality

AlphaMatting has no bugs reported.

Security

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

License

AlphaMatting 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.

Reuse

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

Installation instructions are available. Examples and code snippets are not available.

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AlphaMatting Key Features

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AlphaMatting Examples and Code Snippets

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Community Discussions

Trending Discussions on AlphaMatting

Shape mismatch with vgg16 keras: expected ndim=4, found ndim=2, shape received [None, None]

QUESTION

Shape mismatch with vgg16 keras: expected ndim=4, found ndim=2, shape received [None, None]

Asked 2021-Jan-15 at 09:47

In trying to learn keras and deep learning, I want to create an image matting algorithm that uses an architecture similar to a modified autoencoder, where it takes two image inputs (a source image and a user-generated trimap) and produces one image output (the alpha values of the image foreground). The encoder part (of both inputs) is simple feature extraction using pre-trained VGG16. I want to train the decoder using the low-res alphamatting.com dataset.

Running the attached code produces an error: ValueError: Input 0 of layer block1_conv1 is incompatible with the layer: expected ndim=4, found ndim=2. Full shape received: [None, None]

I'm having trouble understanding this error. I verified that my twin_gen closure is producing image batches of shape (22, 256,256,3) for both inputs, so I would guess that the issue is that I have somehow created the model wrong, but I don't see where the error is. Can anyone help shed some light on how I could be seeing this error?

...

ANSWER

Answered 2021-Jan-15 at 09:47

First you didn't specify the input shape of VGG16 and you set include_top=False, so the default input shape will be (None, None ,3) for channels_last case.

PS: You can check the source code of keras.applications.VGG16 and keras.applications.imagenet_utils.obtain_input_shape for detail.

As you can see the output None shape by calling model.summary():

Source https://stackoverflow.com/questions/65729733

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install AlphaMatting

download OpenCV source code, and step into the directory.
cmake -G "Unix Makefiles"
make -j8
make install

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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