Display of Annotation Type #1192
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First of all please fix codacy and build (probably you forgot to add migrations). Please check that the patch works in case of undo/redo, propagation, ... When you ready please remove WIP from the patch and we will review and provide feedback. |
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@azhavoro , could you please review and give your opinion. |
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Thanks for the contribution.
I have question:
What do you think about support of this field for export/import annotations functionality (CVAT format only). For now if I dump and upload anno again I will completely lose auto/manual field for all objects, right?
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@Priya4607 , we have a conflict. Could you please resolve it?
@azhavoro , could you please summarise all your comments into a check list? Thus it will be easy to understand where we are with the PR.
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@Priya4607 thank you for the update
Could you please fix the build and squash all migrations into one file? |
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@Priya4607 , what is your plans regarding the PR? |
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@nmanovic |
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I'm ok with the back-end changes (2 minor comments above). |
*added field type for tracks
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@Priya4607 , could you please look at #1767. Do you think you can adapt your changes to the PR? It looks like I will merge it before your PR. I hope that together we can merge your PR till middle of July. Really appreciate your time and efforts! |
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@azhavoro , please work with @Priya4607 to accept the PR. What should be done for that? Could you please preview it again and provide your comments? |
| migrations.AlterField( | ||
| model_name='labeledshape', | ||
| name='type', | ||
| field=models.CharField(choices=[('rectangle', 'RECTANGLE'), ('polygon', 'POLYGON'), ('polyline', 'POLYLINE'), ('points', 'POINTS'), ('cuboid', 'CUBOID')], max_length=16), |
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Why do we have the migration for "type" field here?
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Had a migration conflict. So I merged migrations to resolve it.
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@Priya4607 , we should have the old migration file and plus new one with only your changes.
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When I create a new migration, I get the labeledshape model changes added. I'm not sure how to include my changes alone. Could you provide some suggestions on how to proceed?
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@Priya4607 , it was a problem with develp branch. It missed some migrations. I have fixed that. Could you please update and create a new migration?
cvat/apps/tf_annotation/views.py
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| @@ -174,6 +174,7 @@ def convert_to_cvat_format(data): | |||
| "group": None, | |||
| "occluded": False, | |||
| "attributes": [], | |||
| "annotation_type": "Auto", | |||
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@Priya4607 , can we rename "annotation_type" into "source". Also I will vote for "auto", "manual" (fist letter should be lower case). In the future we can store in the field even username (or its id).
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Okay, should it be applied to both frontend and backend to maintain uniformity?
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@Priya4607 , we are ready to merge the PR. Let's do the final minor refactoring, update CHANGELOG.md and I will merge. Thanks for the great idea and contribution. |
@zhiltsov-max Updated test cases |
CHANGELOG.md
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| @@ -61,6 +61,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 | |||
| - [Datumaro] Added `convert` command to convert datasets directly (<https://github.com/opencv/cvat/pull/1837>) | |||
| - [Datumaro] Added an option to specify image extension when exporting datasets (<https://github.com/opencv/cvat/pull/1799>) | |||
| - [Datumaro] Added image copying when exporting datasets, if possible (<https://github.com/opencv/cvat/pull/1799>) | |||
| - Source type support for tags, shapes and tracks (<https://github.com/opencv/cvat/pull/1192>) | |||
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Wrong place. Could you please move these lines into the section for next release?
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@Priya4607 , I'm fine with the PR. Need to fix CHANGELOG.md and I will merge. Thanks! |
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Complexity increasing per file
==============================
- cvat/apps/engine/migrations/0027_auto_20200719_1552.py 1
- cvat-core/src/annotations-objects.js 1
Clones removed
==============
+ cvat-core/src/annotations-saver.js -1
See the complete overview on Codacy |
CHANGELOG.md
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| @@ -467,6 +468,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0 | |||
| ### Added | |||
| - Initial version | |||
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| ## [0.6.1] - 2020-04-14 | |||
| ### Added | |||
| - Annotation type to determine whether a drawn shape is auto annotated using Tensorflow Object detection API or manually annotated by the user | |||
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@Priya4607 , some problems with merge. These lines are wrong.
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Removed those lines.
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@Priya4607 , thanks again for the PR. If you can add the information into statistics about the task (aka info), it will be awesome. Thus we can understand number of manual, interpolated and automatic annotated objects. |
This PR adds a feature which can help the user distinguish which of the boxes are auto-annotated. When a user annotates an image it is marked as
(MANUAL)in each of the boxes created and in case of auto-annotation it is marked as(AUTO). When the user edits a auto-generated box it is changed from(AUTO)to(MANUAL).