* Changed teams target version to 1.4
* Added october and november blog posts
* fixed emojis
* testing font weights for emoji
* removed bold from emojis as not required to render
* added blogs posts
* fixed video titles
* updated roadmap links
* removed repeated sentence
Co-authored-by: Canhua Li <licanhua@live.com>
* Updated Maintainer Info
* Pylint and Black format Check Fix (#16)
pylint fixes, due to version upgrade.
* Removed github workflows for pic2card
Co-authored-by: Vivek Kozhisseri <vivek@Viveks-MBP.bbrouter>
Co-authored-by: aravindhshn <46240940+aravindhshn@users.noreply.github.com>
* Initial proposals
* Add details about current state, motivation
* Organize into order of work, and add estimates
* Add epic for UI testing infra
* Strikeout completed tasks, document current list of pipelines, and add to release checklist
* Added app center links
Co-authored-by: Jonathan Miller <1761798+jonmill@users.noreply.github.com>
- Migrated from flake8 to pylint for stricter linting checks
- Black python code formatted to apply uniform formatting standard across all python files.
Co-authored-by: Haridas N <haridas.n@imaginea.com>
* Updating Issue Templates and PR Template for added clarity
* Updating from PR feedback
* Fixing more PR feedback
* Updating rendering bug report text from PR feedback
* Fixing last PR feedback
* Nov Community Call blog [draft]
* Update Community-Call-November.md
Content review updates.
* Update Community-Call-November.md
* Update GIF
* Delete pic2card.gif
* New pic2card.gif
* Update Community-Call-November.md
* Update Community-Call-November.md
* Delete pic2card.gif
* gif again with correct aspect ratio
* Add files via upload
* Resized image maxwidth 600pix
* Add files via upload
* Column length fix and author and youtube video
* Renamed the asset folder for blog.
* Minor edits
* feature_image addition
* pic2card blog post edits
* post edits
* blog tweaks
Co-authored-by: Haridas N <haridas.n@imaginea.com>
Co-authored-by: Haridas N <haridas.nss@gmail.com>
Co-authored-by: Vasanthakumar <vasanth.s@imaginea.com>
- Normalised the api response for template / non-template apis
- Dockerfile for both detr and rcnn models
- Reduced the docker image size close to 1.1GB ( Before it used to be > 2G )
- Removed the need for tf_object_detection library, which was adding lot of unnecessary dependencies for lesser gain.
- Added github actions to publish the backend to github container registry ( ghrc.io )
- Tesseract fixes to avoid mdfile false triggering special characters.
* Detr model first level results are out.
- Looking good, but duplicate values are there, have to find way to remove
it.
- Measure the mAP score against the benchmark dataset.
* Voc2coco data convertor.
* xml_to_csv and generate_tfrecords commands updated.
- image label has to be synced so that tfrecords are in correct format.
- xml_to_csv command is now more generic.
- Notebook update specific for the dataset experiments.
* Correctly set the category_ids of objects.
* Faster-RCNN updated hparams
This has been resulted into better validation and test accuracy.
Mainly the tuning has been done with aspect ratios of the image.
* Added model registry and realted pipelines.
- Abstract class for the object detection classes
- We can add multiple implementations and select on for the main
pipeline
- Classes are structured with compossibility in mind
* Inference using libtorch for detr model.
Speed enhancments at inference time.
Helps to reduce the dependency of all python torch library stack.
* Columns grouping and image size labels
* columns grouping and image size to labels
* image size to labels logic
* removed the check of exact match of number of objects predicted
* resolved review comments
* updated the predict json test elements count
* Standardizing the object detection model pipeline.
- Helps to switch different object detection models without changing the
pic2card pipeline.
* Both Detr and RCNN models are workig with pic2cad.
* Fixed test cases, to support multiple models.
* Latest Faster RCNN model frozen dump.
* Debug api with new bbox draw method.
Model switching are tested using env variable, and test cases are all
passing.
* Lint fixes and pep8 standardization.
Now only C901 (too complex implementation ) only exempted.
* Fail build if lint test has problems.
Co-authored-by: Keerthana Manoharan <43063410+Keerthana786@users.noreply.github.com>
Co-authored-by: Keerthana Manoharan <43063410+Keerthana786@users.noreply.github.com>
* Updated version
* [ReactNative][Templating] Integrate with AEL in ReactNative Renderer (#4162)
* Migrated to AdaptiveCards Templating with AEL Support
* Updated README with AEL related changes
* updated version details
* [ReactNative][Github actions] Github action setup for CI (#4209)
* Added simple test case
* added basic github actions workflow for testing
* Try 1 - fixed path issue
* Added proper github actions and included badge in readme
* [ReactNative] Changed github action trigger
Co-authored-by: Vivek Kozhisseri <vivekvijayakrishnan@gmail.com>
* Measure the quality of the object detection.
- Using mAP metric
- Evaluating image label vs custom image pipeline, metrics shows model
does good job.
- Tried pytorch implementations, have to do more iterations to improve.
- Some cleanups
* Fixed the test failure issue.
- Separated the tf and pytorch dependencies, we don't need to install
one if not required.
- Only the stable pipeline will be enabled as default, other one will be
used at dev stage only.
- Migrated the requirements and docker files under a folder.
* Reverted the separate folder for requirements.
As the actions in the uptream need a change to make it work.
* pandas version fix.
## Description
Following along the lines of the [typescript repo](https://github.com/microsoft/TypeScript/issues/new/choose) adding a question template that redirects the community to StackOverflow for questions.
For now, allowing for blank issues as a catch-all but eventually goal is to only enable issues that fit our allowed templates for better project management/tracking.
Attempt at trying to standardize PR descriptions - both for maintainability/documentation purposes and also ensure consistency for some of the fabric bot policies that kick in for PRs specifically.
- Follows the newer template workflow which allows for separate templates for bugs and tasks
- Allows for automatically labeling the issues as "Bugs" to kick off the internal fabric bot github workflow to get this visible on our project boards
* Add a GitHub issue template
* Add some more questions to issue template
* Updates to CONTRIBUTING.md
- Don't tell people to use the Schema label since non-contributors can't use labels
- Eliminate some early preview wording
- Fix some links
* Direct questions to StackOverflow
msftbot[bot]
J.P. Roca
Jonathan Miller
Vivek Kozhisseri
Risheek Rajolu
Jonathan Miller
Rahul Amlekar
aravindhshn
Matt Hidinger
Keerthana Manoharan
Haridas N
Rebecca Muraira
Shalini Joshi-MSFT
Pragadeesh Kanagavel
Haridas N
Paul Campbell
Andrew Bares