Mergeback releases/1.6.0 to develop (#1428)

.github/dependabot.yml

@@ -24,8 +24,3 @@ updates:
     directory: /tests
     schedule:
       interval: daily
-
-  - package-ecosystem: pip
-    directory: /gui
-    schedule:
-      interval: daily

.github/workflows/code_scan.yml

@@ -30,8 +30,6 @@ jobs:
           pip-compile -o .ci/dev/docker/segment-anything/requirements.txt docker/segment-anything/requirements.txt
           mkdir -p .ci/base/docs
           pip-compile -o .ci/base/docs/requirements.txt docs/requirements.txt
-          mkdir -p .ci/base/gui
-          pip-compile -o .ci/base/gui/requirements.txt gui/requirements.txt
       - name: Run Trivy Scan (full, csv)
         uses: aquasecurity/trivy-action@d710430a6722f083d3b36b8339ff66b32f22ee55 # 0.19.0
         with:

3rd-party.txt

@@ -7311,288 +7311,6 @@ The above copyright notice and this permission notice shall be included in all c
 
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docs/source/docs/get-started/quick-start-guide/usage.rst

@@ -46,41 +46,3 @@ formats and providing high performance operations:
 
     # export the resulting dataset in COCO format
     dataset.export('dst/dir', 'coco', save_images=True)
-
-DatumaroApp module
--------------
-
-Datumaro also provides a solution to users via GUI, which is DatumaroApp. This visually represents the features
-necessary for performing complex tasks such as data processing, allowing users to easily
-understand and interact with them, thereby enhancing user experience and enabling tasks to be
-performed more intuitively. Additionally, it allows users with limited coding or programming
-experience to use the solution. This enables users to immediately use the solution without the
-need for separate development or setup processes, allowing them to start using the solution and
-performing necessary tasks immediately.
-
-.. code-block::
-
-    cd gui
-    streamlit run streamlit_app.py
-
-Following the above steps, the DatumaroApp page will appear.
-
-.. image:: ../../../../images/gui/intro.png
-
-Datumaro provides solutions not only for individual datasets but also for multiple datasets.
-You can utilize these functionalities through the GUI. Simply select the desired dataset format
-from the sidebar. Please click on **Single Dataset** on sidebar to proceed.
-
-.. image:: ../../../../images/gui/select_file.png
-
-Enter the location where the desired dataset is located in the *Select a path to import data* field below, and then select
-the dataset from among the options available.
-Select the desired dataset from among those available in the *Select a file*. Whether your dataset is in a zip
-file or a regular folder, both are importable.
-
-.. image:: ../../../../images/gui/single_info.png
-
-You can review information about the selected dataset below. You can view Dataset Information, Subset Info,
-Category Info, and a sample of the dataset. For other functionalities, you can proceed through different tabs.
-
-If you want to learn more about DatumaroApp in detail, please check `here <../../datumaroapp-reference/overview.rst>`_.

docs/source/docs/release_notes.rst

@@ -3,7 +3,7 @@ Release Notes
 
 .. toctree::
    :maxdepth: 1
-v2.0.0 (2024.04)
+v1.6.0 (2024.04)
 ----------------
 
 New features
@@ -17,7 +17,6 @@ New features
 - Add `__getitem__()` for random accessing with O(1) time complexity
 - Add Data-aware Anchor Generator
 - Support bounding box import within Kaggle extractors and add `KaggleCocoBase`
-- Implement Datumaroapp GUI for datumaro
 
 Enhancements
 ^^^^^^^^^^^^

src/datumaro/version.py

@@ -1 +1 @@
-__version__ = "2.0.0"
+__version__ = "1.7.0rc0"

tests/requirements.txt

@@ -7,9 +7,3 @@ pytest-stress
 pytest-html
 coverage
 pytest-csv
-
-# DatumaroApp
-streamlit==1.32.2
-streamlit_antd_components
-streamlit_elements
-streamlit-aggrid