Update Pixel project handling

docs/source/api_reference/api_metadata.rst

@@ -18,7 +18,7 @@ Project metadata example:
      "creator_id": "admin@superannotate.com",
      "updatedAt": "2020-08-31T05:43:43.118Z",
      "createdAt": "2020-08-31T05:43:43.118Z"
-     "type": "Vector", # Pixel, Video, Multimodal
+     "type": "Vector", # Video, Multimodal
      "attachment_name": None,
      "attachment_path": None,
      "entropy_status": 1,

docs/source/cli_client.rst

@@ -42,7 +42,7 @@ To create a new project:
 
 .. code-block:: bash
 
-   superannotatecli create-project --name <project_name> --description <project_description> --type <project_type Vector or Pixel>
+   superannotatecli create-project --name <project_name> --description <project_description> --type <project_type Vector>
 
 ----------
 

docs/source/userguide/setup_project.rst

@@ -249,9 +249,7 @@ you are uploading to should contain annotation class with that name.
 
 
 This will try uploading to the project all the JSON files in the folder that have :file:`"<image_name>.json"` postfix.
-For pixel projects JSON files should be named :file:`"<image_name>___pixel.json"` and also for
-each JSON a mask image file should be present with the name
-:file:`"<image_name>___save.png"`. Image with :file:`<image_name>` should
+Image with :file:`<image_name>` should
 already be present in the project for the upload to work.
 
 

docs/source/userguide/utilities.rst

@@ -40,7 +40,7 @@ You can find more information annotation format conversion :ref:`here <ref_conve
     export_annotation(
        "tests/converter_test/COCO/input/fromSuperAnnotate/cats_dogs_panoptic_segm",
        "tests/converter_test/COCO/output/panoptic",
-       "COCO", "panoptic_test", "Pixel","panoptic_segmentation"
+       "COCO", "panoptic_test","panoptic_segmentation"
     )
 
     # From COCO keypoints detection format to SA annotation format
@@ -54,7 +54,7 @@ You can find more information annotation format conversion :ref:`here <ref_conve
     import_annotation(
        "tests/converter_test/VOC/input/fromPascalVOCToSuperAnnotate/VOC2012",
        "tests/converter_test/VOC/output/instances",
-       "VOC", "instances_test", "Pixel", "instance_segmentation"
+       "VOC", "instances_test", "instance_segmentation"
     )
 
     # YOLO annotation format to SA annotation format

pytest.ini

@@ -3,4 +3,4 @@ minversion = 3.7
 log_cli=true
 python_files = test_*.py
 ;pytest_plugins = ['pytest_profiling']
-;addopts = -n 6 --dist loadscope
+addopts = -n 6 --dist loadscope

src/superannotate/__init__.py

@@ -3,7 +3,7 @@
 import sys
 
 
-__version__ = "4.5.1"
+__version__ = "4.5.2dev1"
 
 
 os.environ.update({"sa_version": __version__})
@@ -17,7 +17,6 @@
 from lib.core import PACKAGE_VERSION_MAJOR_UPGRADE
 from lib.core.exceptions import AppException
 from lib.core.exceptions import FileChangedError
-from superannotate.lib.app.input_converters import convert_project_type
 from superannotate.lib.app.input_converters import export_annotation
 from superannotate.lib.app.input_converters import import_annotation
 from superannotate.lib.app.interface.sdk_interface import SAClient
@@ -37,7 +36,6 @@
     "FileChangedError",
     "import_annotation",
     "export_annotation",
-    "convert_project_type",
 ]
 
 __author__ = "Superannotate"

src/superannotate/lib/app/analytics/aggregators.py

@@ -9,7 +9,6 @@
 
 import lib.core as constances
 import pandas as pd
-from lib.core import PIXEL_ANNOTATION_POSTFIX
 from lib.core import VECTOR_ANNOTATION_POSTFIX
 from lib.core.exceptions import AppException
 
@@ -162,8 +161,6 @@ def _set_annotation_suffix(self, path):
             self._annotation_suffix = ".json"
         elif VECTOR_ANNOTATION_POSTFIX in fname.name:
             self._annotation_suffix = VECTOR_ANNOTATION_POSTFIX
-        elif PIXEL_ANNOTATION_POSTFIX in fname.name:
-            self._annotation_suffix = PIXEL_ANNOTATION_POSTFIX
         else:
             self._annotation_suffix = ".json"
 
@@ -205,10 +202,7 @@ def aggregate_annotations_as_df(self):
         self.check_classes_path()
         annotation_paths = self.get_annotation_paths()
 
-        if self.project_type in (
-            constances.ProjectType.VECTOR,
-            constances.ProjectType.PIXEL,
-        ):
+        if self.project_type is constances.ProjectType.VECTOR:
             return self.aggregate_image_annotations_as_df(annotation_paths)
         if self.project_type is constances.ProjectType.VIDEO:
             return self.aggregate_video_annotations_as_df(annotation_paths)

src/superannotate/lib/app/analytics/common.py

@@ -173,8 +173,6 @@ def __get_user_metadata(annotation):
 
     if "___objects.json" in annotations_paths[0].name:
         type_postfix = "___objects.json"
-    elif "___pixel.json" in annotations_paths[0].name:
-        type_postfix = "___pixel.json"
     else:
         type_postfix = ".json"
 

src/superannotate/lib/app/helpers.py

@@ -9,7 +9,6 @@
 import numpy as np
 import pandas as pd
 from lib.core import ATTACHED_VIDEO_ANNOTATION_POSTFIX
-from lib.core import PIXEL_ANNOTATION_POSTFIX
 from lib.core import VECTOR_ANNOTATION_POSTFIX
 from lib.core.exceptions import AppException
 
@@ -36,7 +35,6 @@ def get_local_annotation_paths(
             if i.name.endswith(
                 (
                     VECTOR_ANNOTATION_POSTFIX,
-                    PIXEL_ANNOTATION_POSTFIX,
                     ATTACHED_VIDEO_ANNOTATION_POSTFIX,
                 )
             )
@@ -66,10 +64,8 @@ def get_s3_annotation_paths(folder_path, s3_bucket, annotation_paths, recursive)
     for data in paginator.paginate(Bucket=s3_bucket, Prefix=folder_path):
         for annotation in data.get("Contents", []):
             key = annotation["Key"]
-            if (
-                key.endswith(VECTOR_ANNOTATION_POSTFIX)
-                or key.endswith(PIXEL_ANNOTATION_POSTFIX)
-                or key.endswith(ATTACHED_VIDEO_ANNOTATION_POSTFIX)
+            if key.endswith(VECTOR_ANNOTATION_POSTFIX) or key.endswith(
+                ATTACHED_VIDEO_ANNOTATION_POSTFIX
             ):
                 if not recursive and "/" in key[len(folder_path) + 1 :]:
                     continue

src/superannotate/lib/app/input_converters/__init__.py

@@ -1,10 +1,8 @@
-from lib.app.input_converters.conversion import convert_project_type
 from lib.app.input_converters.conversion import export_annotation
 from lib.app.input_converters.conversion import import_annotation
 
 
 __all__ = [
-    "convert_project_type",
     "export_annotation",
     "import_annotation",
 ]

src/superannotate/lib/app/input_converters/conversion.py

@@ -6,17 +6,14 @@
 import tempfile
 from argparse import Namespace
 from pathlib import Path
-from typing import Union
 
 from lib.app.interface.base_interface import Tracker
 from lib.core import LIMITED_FUNCTIONS
 from lib.core.enums import ProjectType
 from lib.core.exceptions import AppException
-from typing_extensions import Literal
 
 from .export_from_sa_conversions import export_from_sa
 from .import_to_sa_conversions import import_to_sa
-from .sa_conversion import sa_convert_project_type
 
 
 ALLOWED_TASK_TYPES = [
@@ -27,26 +24,22 @@
     "vector_annotation",
 ]
 
-ALLOWED_PROJECT_TYPES = ["Pixel", "Vector"]
+ALLOWED_PROJECT_TYPES = ["Vector"]
 
 ALLOWED_ANNOTATION_IMPORT_FORMATS = {
     "COCO": [
-        ("Pixel", "panoptic_segmentation"),
-        ("Pixel", "instance_segmentation"),
         ("Vector", "keypoint_detection"),
         ("Vector", "instance_segmentation"),
         ("Vector", "object_detection"),
     ],
     "VOC": [
         ("Vector", "object_detection"),
         ("Vector", "instance_segmentation"),
-        ("Pixel", "instance_segmentation"),
     ],
     "LabelBox": [
         ("Vector", "object_detection"),
         ("Vector", "instance_segmentation"),
         ("Vector", "vector_annotation"),
-        ("Pixel", "instance_segmentation"),
     ],
     "DataLoop": [
         ("Vector", "object_detection"),
@@ -57,15 +50,14 @@
         ("Vector", "vector_annotation"),
         ("Vector", "object_detection"),
         ("Vector", "instance_segmentation"),
-        ("Pixel", "instance_segmentation"),
         ("Vector", "keypoint_detection"),
     ],
     "VoTT": [
         ("Vector", "object_detection"),
         ("Vector", "instance_segmentation"),
         ("Vector", "vector_annotation"),
     ],
-    "SageMaker": [("Pixel", "instance_segmentation"), ("Vector", "object_detection")],
+    "SageMaker": [("Vector", "object_detection")],
     "VGG": [
         ("Vector", "object_detection"),
         ("Vector", "instance_segmentation"),
@@ -77,8 +69,6 @@
 
 ALLOWED_ANNOTATION_EXPORT_FORMATS = {
     "COCO": [
-        ("Pixel", "panoptic_segmentation"),
-        ("Pixel", "instance_segmentation"),
         ("Vector", "instance_segmentation"),
         ("Vector", "keypoint_detection"),
         ("Vector", "object_detection"),
@@ -166,8 +156,6 @@ def export_annotation(
     --------------------------------------
      project_type           task
     ==============  ======================
-    Pixel           panoptic_segmentation
-    Pixel           instance_segmentation
     Vector          instance_segmentation
     Vector          object_detection
     Vector          keypoint_detection
@@ -181,15 +169,13 @@ def export_annotation(
     :type dataset_format: str
     :param dataset_name: Will be used to create json file in the output_dir.
     :type dataset_name: str
-    :param project_type: SuperAnnotate project type is either 'Vector' or 'Pixel' (Default: 'Vector')
+    :param project_type: SuperAnnotate project type is 'Vector'
                          'Vector' project creates <image_name>___objects.json for each image.
-                         'Pixel' project creates <image_name>___pixel.jsons and <image_name>___save.png annotation mask for each image.
     :type project_type: str
     :param task: Task can be one of the following: ['panoptic_segmentation', 'instance_segmentation',
                  'keypoint_detection', 'object_detection']. (Default: "object_detection").
                  'keypoint_detection' can be used to converts keypoints from/to available annotation format.
                  'panoptic_segmentation' will use panoptic mask for each image to generate bluemask for SuperAnnotate annotation format and use bluemask to generate panoptic mask for invert conversion. Panoptic masks should be in the input folder.
-                 'instance_segmentation' 'Pixel' project_type converts instance masks and 'Vector' project_type generates bounding boxes and polygons from instance masks. Masks should be in the input folder if it is 'Pixel' project_type.
                  'object_detection' converts objects from/to available annotation format
     :type task: str
     """
@@ -223,8 +209,6 @@ def export_annotation(
     _passes_value_sanity(values_info)
     if project_type == "Vector":
         extension = "___objects.json"
-    elif project_type == "Pixel":
-        extension = "___pixel.json"
     else:
         extension = ".json"
     with tempfile.TemporaryDirectory() as tmp_dir:
@@ -264,8 +248,6 @@ def import_annotation(
     --------------------------------------
      project_type           task
     ==============  ======================
-    Pixel           panoptic_segmentation
-    Pixel           instance_segmentation
     Vector          instance_segmentation
     Vector          object_detection
     Vector          keypoint_detection
@@ -276,7 +258,6 @@ def import_annotation(
     --------------------------------------
      project_type           task
     ==============  ======================
-    Pixel           instance_segmentation
     Vector          instance_segmentation
     Vector          object_detection
     ==============  ======================
@@ -289,7 +270,6 @@ def import_annotation(
     Vector          object_detection
     Vector          instance_segmentation
     Vector          vector_annotation
-    Pixel           instance_segmentation
     ==============  ======================
 
     ==============  ======================
@@ -311,7 +291,6 @@ def import_annotation(
     Vector          keypoint_detection
     Vector          vector_annotation
     Vector          instance_segmentation
-    Pixel           instance_segmentation
     ==============  ======================
 
     ==============  ======================
@@ -329,7 +308,6 @@ def import_annotation(
     --------------------------------------
      project_type           task
     ==============  ======================
-    Pixel           instance_segmentation
     Vector          objcet_detection
     ==============  ======================
 
@@ -368,15 +346,13 @@ def import_annotation(
     :type dataset_format: str
     :param dataset_name: Name of the json file in the input_dir, which should be converted.
     :type dataset_name: str
-    :param project_type: SuperAnnotate project type is either 'Vector' or 'Pixel' (Default: 'Vector')
+    :param project_type: SuperAnnotate project type is 'Vector'
                          'Vector' project creates <image_name>___objects.json for each image.
-                         'Pixel' project creates <image_name>___pixel.jsons and <image_name>___save.png annotation mask for each image.
     :type project_type: str
     :param task: Task can be one of the following: ['panoptic_segmentation', 'instance_segmentation',
                  'keypoint_detection', 'object_detection', 'vector_annotation']. (Default: "object_detection").
                  'keypoint_detection' can be used to converts keypoints from/to available annotation format.
                  'panoptic_segmentation' will use panoptic mask for each image to generate bluemask for SuperAnnotate annotation format and use bluemask to generate panoptic mask for invert conversion. Panoptic masks should be in the input folder.
-                 'instance_segmentation' 'Pixel' project_type converts instance masks and 'Vector' project_type generates bounding boxes and polygons from instance masks. Masks should be in the input folder if it is 'Pixel' project_type.
                  'object_detection' converts objects from/to available annotation format
                  'vector_annotation' can be used to convert all annotations (point, ellipse, circule, cuboid and etc) to SuperAnnotate vector project.
     :param images_root: Additonal path to images directory in input_dir
@@ -427,29 +403,3 @@ def import_annotation(
     _passes_converter_sanity(args, "import")
 
     import_to_sa(args)
-
-
-@Tracker
-def convert_project_type(
-    input_dir: Union[str, Path],
-    output_dir: Union[str, Path],
-    convert_to: Literal["Vector", "Pixel"],
-):
-    """Converts SuperAnnotate 'Vector' project type to 'Pixel' or reverse.
-
-    :param input_dir: Path to the dataset folder that you want to convert.
-    :type input_dir: Pathlike(str or Path)
-    :param output_dir: Path to the folder where you want to have converted files.
-    :type output_dir: Pathlike(str or Path)
-    :param convert_to: the project type to which the current project should be converted.
-    :type convert_to: str
-    """
-    params_info = [
-        (input_dir, "input_dir", (str, Path)),
-        (output_dir, "output_dir", (str, Path)),
-    ]
-    _passes_type_sanity(params_info)
-
-    input_dir, output_dir = _change_type(input_dir, output_dir)
-
-    sa_convert_project_type(input_dir, output_dir, convert_to)