An Api for Emotion recognition.

Overview

License: MIT Python 3.7|3.6|3.5|3.4 Deploy

PLAYEMO

Playemo was built from the ground-up with Flask, a python tool that makes it easy for developers to build APIs.


Use Cases

Is Python your language of choice? If so, we have a [fully-supported Python API client] that makes working with the playemo API an easy task!

There are many reasons to use the playemo API. The most common use case is to predict the emotion of a person from a single photograph. However, this can also be used as a facial detection engine which returns a cropped out image of the face detected in a single photograph.!

Authorization

All API requests require the use of an API key

To authenticate an API request, you should provide your the api_key=[API_KEY] as a GET parameter to authorize yourself to the API. But note that this is likely to leave traces in things like your history, if accessing the API through a browser.

GET /?api_key=12345678901234567890123456789012
Parameter Type Description
api_key string Required. Your Playemo API key

Responses

Many API endpoints return the JSON representation of the resources created or edited. However, if an invalid request is submitted, or some other error occurs, Playemo returns a JSON response in the following format:

{
  "error" : string,
  "success" : bool,
  "result"    : string
}

The error attribute contains a message commonly used to indicate errors or, in the case of deleting a resource, success that the resource was properly deleted.

The success attribute describes if the transaction was successful or not.

The result attribute contains any other metadata associated with the response. This will be an escaped string containing JSON data.

Status Codes

Playemo returns the following status codes in its API:

Status Code Description
200 OK
201 CREATED
400 BAD REQUEST
404 NOT FOUND
500 INTERNAL SERVER ERROR

Links

Please don't hesitate to file an issue if you see anything missing.

Screenshots

Home Page

Available Commands

In the project directory, you can run: python--version" : "check python version",

Since tensorflow supports python 3.7,3.6,3.5 or 3.4, i would advice you have python 3.6 installed on your machine.

pip install -r requirements.txt" : "required libaries installed",

This will install the the neccesarry libaries needed to run the application on your machine.

python app.py" : "python-scripts start",

The app is built using Flask so this command Runs the app in Development mode. Open http://localhost:5000 to view it in the browser. The page will reload if you make edits. You will also see any lint errors in the console.

Built With

  • Python
  • Flask
  • Mtcnn
  • TensorFlow
  • Keras
  • CSS
  • HTML

Future Updates

  • A playlist recommendation system based on Emotion predicted

Author

DERHNYEL

🤝 Support

Contributions, issues, and feature requests are welcome!

Give a ⭐️ if you like this project!

Owner
greek geek
greek geek
Supporting code for "Autoregressive neural-network wavefunctions for ab initio quantum chemistry".

naqs-for-quantum-chemistry This repository contains the codebase developed for the paper Autoregressive neural-network wavefunctions for ab initio qua

Tom Barrett 24 Dec 23, 2022
A comprehensive list of published machine learning applications to cosmology

ml-in-cosmology This github attempts to maintain a comprehensive list of published machine learning applications to cosmology, organized by subject ma

George Stein 290 Dec 29, 2022
3 Apr 20, 2022
IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales

IRON Kaggle project done while doing IRONHACK Bootcamp where we had to analyze and use a Machine Learning Project to predict future sales. In this case, we ended up using XGBoost because it was the o

1 Jan 04, 2022
An Active Automata Learning Library Written in Python

AALpy An Active Automata Learning Library AALpy is a light-weight active automata learning library written in pure Python. You can start learning auto

TU Graz - SAL Dependable Embedded Systems Lab (DES Lab) 78 Dec 30, 2022
Revisting Open World Object Detection

Revisting Open World Object Detection Installation See INSTALL.md. Dataset Our n

58 Dec 23, 2022
SOLO and SOLOv2 for instance segmentation, ECCV 2020 & NeurIPS 2020.

SOLO: Segmenting Objects by Locations This project hosts the code for implementing the SOLO algorithms for instance segmentation. SOLO: Segmenting Obj

Xinlong Wang 1.5k Dec 31, 2022
Codebase for testing whether hidden states of neural networks encode discrete structures.

structural-probes Codebase for testing whether hidden states of neural networks encode discrete structures. Based on the paper A Structural Probe for

John Hewitt 349 Dec 17, 2022
Ivy is a templated deep learning framework which maximizes the portability of deep learning codebases.

Ivy is a templated deep learning framework which maximizes the portability of deep learning codebases. Ivy wraps the functional APIs of existing frameworks. Framework-agnostic functions, libraries an

Ivy 8.2k Jan 02, 2023
Learning High-Speed Flight in the Wild

Learning High-Speed Flight in the Wild This repo contains the code associated to the paper Learning Agile Flight in the Wild. For more information, pl

Robotics and Perception Group 391 Dec 29, 2022
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]

Learning to Classify Images without Labels This repo contains the Pytorch implementation of our paper: SCAN: Learning to Classify Images without Label

Wouter Van Gansbeke 1.1k Dec 30, 2022
Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning"

CMSF Official Code for "Constrained Mean Shift Using Distant Yet Related Neighbors for Representation Learning" Requirements Python = 3.7.6 PyTorch

4 Nov 25, 2022
Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]

Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [BCNet, CVPR 2021] This is the official pytorch implementation of BCNet built on

Lei Ke 434 Dec 01, 2022
This is the repo for the paper `SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization'. (published in Bioinformatics'21)

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization This is the code for our paper ``SumGNN: Multi-typed Drug

Yue Yu 58 Dec 21, 2022
GNEE - GAT Neural Event Embeddings

GNEE - GAT Neural Event Embeddings This repository contains source code for the GNEE (GAT Neural Event Embeddings) method introduced in the paper: "Se

João Pedro Rodrigues Mattos 0 Sep 15, 2021
Benchmark library for high-dimensional HPO of black-box models based on Weighted Lasso regression

LassoBench LassoBench is a library for high-dimensional hyperparameter optimization benchmarks based on Weighted Lasso regression. Note: LassoBench is

Kenan Šehić 5 Mar 15, 2022
This app is a simple example of using Strealit to create a financial data web app.

Streamlit Demo: Finance Chart This app is a simple example of using Streamlit to create a financial data web app. This demo use streamlit, pandas and

91 Jan 02, 2023
Implementation of Rotary Embeddings, from the Roformer paper, in Pytorch

Rotary Embeddings - Pytorch A standalone library for adding rotary embeddings to transformers in Pytorch, following its success as relative positional

Phil Wang 110 Dec 30, 2022
Autoencoder - Reducing the Dimensionality of Data with Neural Network

autoencoder Implementation of the Reducing the Dimensionality of Data with Neural Network – G. E. Hinton and R. R. Salakhutdinov paper. Notes Aim to m

Jordan Burgess 13 Nov 17, 2022
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

This project is now archived. It's been fun working on it, but it's time for me to move on. Thank you for all the support and feedback over the last c

Max Pumperla 2.1k Jan 03, 2023