phosphenes-simulation
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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✓Academic publication links
Links to: ieee.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (9.2%) to scientific vocabulary
Last synced: 10 months ago
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JSON representation
Repository
Basic Info
- Host: GitHub
- Owner: HeshamMoneer
- License: mit
- Language: Python
- Default Branch: main
- Size: 200 MB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Created over 4 years ago
· Last pushed over 2 years ago
Metadata Files
Readme
License
Citation
readme.md
Repository description
- This repo contains the work described in the paper Enhancing Facial Recognition in Visual Prostheses using Region of Interest Magnification and Caricaturing.
- The IEEE publication could be accessed here.
- The work is also described in the Thesis Eye Detection and Face Recognition for Visual Prostheses.
- The thesis could be found here.
To run the project
- clone the repo
- make sure to have python3 and pip commands on your local machine terminal
- run pip install --user pipenv
- fix the python version in the pipfile to match the version installed on your machine
- run pipenv install in the project root directory
- run pipenv shell to spawn a shell in the virtual env of the project; to exit it run ctrl+d
- run python3 [Any].py
ANOTHER APPROACH - instead of spwaning a pipenv shell, you can run pipenv run + some script from the pipfile. The pipfile includes commands that run the video simulation or the singelton image simulation.
SPV Architecture

- The configuration variables could be set in the simConfig.py file
- The video simulation file is videoSim.py and the phosphene simulation file (singleton image simulation) is phosphenesSim.py
- The enhancement modules are the following:
- caricaturing (found in caricaturing/ directory)
- emotion recognition (found in emotion_recognition/ directory)
- talking detection (found in talking_detection/ directory)
- face recognition (found in face_recognition/ directory; this module was dropped in the study)
- face specific histogram equalization (found in bboxes.py file as a function heq())
- The experiment/ directory contains the videos used in the computer screen simulation
Owner
- Name: Hesham Moneer
- Login: HeshamMoneer
- Kind: user
- Repositories: 4
- Profile: https://github.com/HeshamMoneer
GitHub Events
Total
Last Year
Dependencies
Pipfile
pypi
- cmake *
- dlib *
- opencv-contrib-python *
- opencv-python *
- scikit-image *
- scipy *
- sklearn *
- tensorflow *
Pipfile.lock
pypi
- absl-py ==1.0.0
- astunparse ==1.6.3
- cachetools ==5.0.0
- certifi ==2021.10.8
- charset-normalizer ==2.0.12
- cmake ==3.22.4
- dlib ==19.23.1
- flatbuffers ==2.0
- gast ==0.5.3
- google-auth ==2.6.6
- google-auth-oauthlib ==0.4.6
- google-pasta ==0.2.0
- grpcio ==1.44.0
- h5py ==3.6.0
- idna ==3.3
- imageio ==2.17.0
- importlib-metadata ==4.11.3
- joblib ==1.1.0
- keras ==2.8.0
- keras-preprocessing ==1.1.2
- libclang ==14.0.1
- markdown ==3.3.6
- networkx ==2.8
- numpy ==1.22.3
- oauthlib ==3.2.0
- opencv-contrib-python ==4.5.5.64
- opencv-python ==4.5.5.64
- opt-einsum ==3.3.0
- packaging ==21.3
- pillow ==9.1.0
- protobuf ==3.20.1
- pyasn1 ==0.4.8
- pyasn1-modules ==0.2.8
- pyparsing ==3.0.8
- pywavelets ==1.3.0
- requests ==2.27.1
- requests-oauthlib ==1.3.1
- rsa ==4.8
- scikit-image ==0.19.2
- scikit-learn ==1.0.2
- scipy ==1.8.0
- setuptools ==62.1.0
- six ==1.16.0
- sklearn ==0.0
- tensorboard ==2.8.0
- tensorboard-data-server ==0.6.1
- tensorboard-plugin-wit ==1.8.1
- tensorflow ==2.8.0
- tensorflow-io-gcs-filesystem ==0.25.0
- termcolor ==1.1.0
- tf-estimator-nightly ==2.8.0.dev2021122109
- threadpoolctl ==3.1.0
- tifffile ==2022.4.22
- typing-extensions ==4.2.0
- urllib3 ==1.26.9
- werkzeug ==2.1.1
- wheel ==0.37.1
- wrapt ==1.14.0
- zipp ==3.8.0