Facial-Expression | Detect the facial Expression ....

by vijayshankarrealdeal Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | Facial-Expression Summary

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

Detect the facial Expression....

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Facial-Expression has a low active ecosystem.

It has 2 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

Facial-Expression has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Facial-Expression is current.

Quality

Facial-Expression has 0 bugs and 0 code smells.

Security

Facial-Expression has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Facial-Expression code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Facial-Expression 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

Facial-Expression releases are not available. You will need to build from source code and install.

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

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Facial-Expression Key Features

No Key Features are available at this moment for Facial-Expression.

Facial-Expression Examples and Code Snippets

No Code Snippets are available at this moment for Facial-Expression.

Community Discussions

Trending Discussions on Facial-Expression

Getting Error after Epoch While running a training model for facial expression detection using keras

Add/Append value to specific index in a list

How to change shape of 3 Dimensional picture grayscale to 4 Dimensional

X.shape[1] size doesn't fit the expected value

QUESTION

Getting Error after Epoch While running a training model for facial expression detection using keras

Asked 2021-Mar-12 at 17:18

I'm working on the facial expression detection model with python 3.8.8 and TensorFlow 2.4.

My code:

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ANSWER

Answered 2021-Mar-08 at 13:47

The error message reports:

Source https://stackoverflow.com/questions/66520398

QUESTION

Add/Append value to specific index in a list

Asked 2020-Oct-27 at 04:26

I have the following list:

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ANSWER

Answered 2020-Oct-27 at 04:17

Do a[0].append('hi') because the list you want to is the 0th index in the list a.

Source https://stackoverflow.com/questions/64548237

QUESTION

How to change shape of 3 Dimensional picture grayscale to 4 Dimensional

Asked 2020-Jun-11 at 19:20

So I am doing face_emotion recognition. To do this I am using this kaggle scirpt and running on kaggle GPUS, here is the link Kaggle Face Emotion Detection. I run the exact same, and the shape I get is: (27345,48,48,1). The 27345 maybe a off a bit, but it's like this, and I understand the 48,48,1 as being a picture 48x48 pixels wide grayscale, and I can get that picture easily. The problem that persists is that the tensor is, or the shape of the layer, it's 4 DIM, and I have a 3Dim, how do I fix this, will having (1,48,48,1) work? If yes then how to get this type of editing to numpy shape to this. I have the face extracted from face_recognition library in Python. I am using keras, and this is my so far script to detect emotion:

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ANSWER

Answered 2020-Jun-11 at 19:20

Try this:

Source https://stackoverflow.com/questions/62330654

QUESTION

X.shape[1] size doesn't fit the expected value

Asked 2020-Apr-06 at 22:04

I'm currently working on my final degree project in robotics, and I decided to create an open-source robot capable of replicating human emotions. The robot is all set up and ready to receive orders, but I'm still busy coding it. I'm currently basing my code off this method. The idea is to extract 68 facial landmarks from a low FPS video feed (using RPi Camera V2), feed those landmarks to a trained SVM classifier and have it return a numeral from 0-6 depending on the expression it detected (Angry, Disgust, Fear, Happy, Sad, Surprise and Neutral). I'm testing out the capabilities of my model with some pictures I took using the RPi Camera, and this is what I've managed to put together so far in terms of code:

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ANSWER

Answered 2020-Apr-06 at 22:04

Solved it! Turns out my model was trained using a combination of HOG features and Dlib landmarks, however I was only feeding the landmarks to the predictor, which resulted in the size discrepancy.

Source https://stackoverflow.com/questions/61015323

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

Vulnerabilities

No vulnerabilities reported

Install Facial-Expression

You can download it from GitHub.
You can use Facial-Expression 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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