* lower python version for google colab
* faces working with colab
* text for colab
* fix dict update bug
* final edits for colab
* update readme with links
* load text models on demand
* update test
* fix typo; more description in readme
* remove optional keys
* update notebook
* comments
* add jupyterlab
* add text analysis capability
* add bool in tests
* add dependencies and spelling test
* add test sentiment
* update black pre-commit dependency for native nb support
* update black version, find better sentiment test
* test analyse_image
There has been a backwards-incompatible change to shields.io badges for Github Actions. They now identify workflows by their filename instead of their name field.
* start with translate
* translate and clean - notebook
* spacy model in requirements
* translate in module
* clean in module
* upload coverage only for ubuntu
* update ubuntu version on runner
* update dependencies
* start tests for text
* skip gcv test
* fix age
* more text tests
* more text tests
* add comment
* test translation
* fix numpy version; add reference data for trans
* use utf-8 for windows
* Apply thresholding to restrict the scope of facial expression recognition
* fix test dict faces
* remove approx
* do not ignore data in subdirs
* where does test_display come from
* remove face analysis duplication
* imageai sneaked into ci
Co-authored-by: Inga Ulusoy <inga.ulusoy@uni-heidelberg.de>
* Create ci.yml
* include pytest
* Update pyproject.toml
* include pytest-cov
* use approx in pytest
* Update test_faces.py
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* add coverage yaml
* reduce passing grade
* use copy instead of symlink on windows
* crude attempt at calculating deviations
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Create ci.yml
* include pytest
* Update pyproject.toml
* include pytest-cov
* use approx in pytest
* Update test_faces.py
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* add coverage yaml
* reduce passing grade
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* colors expression by KMean algorithm
* object detection by imageai
* object detection by cvlib
* add encapsulation of object detection
* remove encapsulation of objdetect v0
* objects expression to dict
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* added imageai to requirements
* add objects to dictionary
* update for AnalysisMethod baseline
* add objects dection support explore_analysis display
* extend python version of misinf to allow imageai
* account for older python
* use global functionality for dict to csv convert
* update for docker build
* docker will build now but ipywidgets still not working
* test code
* include test data folder in repo
* add some sample images
* load cvs labels to dict
* add test data
* retrigger checks
* add map to human coding
* get orders from dict, missing dep
* add module to test accuracy
* retrigger checks
* retrigger checks
* now removing imageai
* removed imageai
* move labelmanager to analyse
* multiple faces in mydict
* fix pre-commit issues
* map mydict
* hide imageai
* objects default using cvlib, isolate and disable imageai
* correct python version
* refactor faces tests
* refactor objects tests
* sonarcloud issues
* refactor utils tests
* address code smells
* update readme
* update notebook without imageai
Co-authored-by: Ma Xianghe <825074348@qq.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: iulusoy <inga.ulusoy@uni-heidelberg.de>
* convert into dict output
* faces class
* return cleaned dict
* empty methods that are required
* with dict updates
* with dominant emotion confidence as tuple
* multiple images
* update notebook
* read image into nb
* test
* added keras-ocr and google vision
* google cloud vision by far the best
* setting up docker for text 1
* move widgets and analysis to display module
* move widgets and analysis to display module - 2
* text on image through widgets
* Fix installation into Docker image
* Install C++ compiler, not only C
* Automatically install requirements.txt stuff
* Write pytesseract into requirements file
Co-authored-by: iulusoy <inga.ulusoy@uni-heidelberg.de>
* read image into nb
* test
* added keras-ocr and google vision
* google cloud vision by far the best
* setting up docker for text 1
* move widgets and analysis to display module
* move widgets and analysis to display module - 2
* text on image through widgets
