[DAR-4931][External] Fixed regression affecting converting complex polygons to coco

darwin/exporter/formats/coco.py

@@ -6,6 +6,7 @@
 
 import numpy as np
 import orjson as json
+from upolygon import draw_polygon, rle_encode
 
 import darwin.datatypes as dt
 from darwin.utils import convert_polygons_to_sequences
@@ -175,35 +176,64 @@ def _build_annotation(
 ) -> Optional[Dict[str, Any]]:
     annotation_type = annotation.annotation_class.annotation_type
     if annotation_type == "polygon":
-        sequences = convert_polygons_to_sequences(
-            annotation.data["paths"], rounding=False
-        )
-        x_coords = [s[0::2] for s in sequences]
-        y_coords = [s[1::2] for s in sequences]
-        min_x = np.min([np.min(x_coord) for x_coord in x_coords])
-        min_y = np.min([np.min(y_coord) for y_coord in y_coords])
-        max_x = np.max([np.max(x_coord) for x_coord in x_coords])
-        max_y = np.max([np.max(y_coord) for y_coord in y_coords])
-        w = max_x - min_x
-        h = max_y - min_y
-        # Compute the area of the polygon
-        poly_area = np.sum(
-            [
-                _polygon_area(x_coord, y_coord)
-                for x_coord, y_coord in zip(x_coords, y_coords)
-            ]
-        )
+        if len(annotation.data["paths"]) == 1:
+            sequences = convert_polygons_to_sequences(
+                annotation.data["paths"], rounding=False
+            )
+            x_coords = [s[0::2] for s in sequences]
+            y_coords = [s[1::2] for s in sequences]
+            min_x = np.min([np.min(x_coord) for x_coord in x_coords])
+            min_y = np.min([np.min(y_coord) for y_coord in y_coords])
+            max_x = np.max([np.max(x_coord) for x_coord in x_coords])
+            max_y = np.max([np.max(y_coord) for y_coord in y_coords])
+            w = max_x - min_x
+            h = max_y - min_y
+            # Compute the area of the polygon
+            poly_area = np.sum(
+                [
+                    _polygon_area(x_coord, y_coord)
+                    for x_coord, y_coord in zip(x_coords, y_coords)
+                ]
+            )
 
-        return {
-            "id": annotation_id,
-            "image_id": _build_image_id(annotation_file),
-            "category_id": categories[annotation.annotation_class.name],
-            "segmentation": sequences,
-            "area": poly_area,
-            "bbox": [min_x, min_y, w, h],
-            "iscrowd": 0,
-            "extra": _build_extra(annotation),
-        }
+            return {
+                "id": annotation_id,
+                "image_id": _build_image_id(annotation_file),
+                "category_id": categories[annotation.annotation_class.name],
+                "segmentation": sequences,
+                "area": poly_area,
+                "bbox": [min_x, min_y, w, h],
+                "iscrowd": 0,
+                "extra": _build_extra(annotation),
+            }
+        elif len(annotation.data["paths"]) > 1:
+            mask = np.zeros((annotation_file.image_height, annotation_file.image_width))
+            sequences = convert_polygons_to_sequences(annotation.data["paths"])
+            draw_polygon(mask, sequences, 1)
+            counts = rle_encode(mask)
+
+            x_coords = [s[0::2] for s in sequences]
+            y_coords = [s[1::2] for s in sequences]
+            min_x = np.min([np.min(x_coord) for x_coord in x_coords])
+            min_y = np.min([np.min(y_coord) for y_coord in y_coords])
+            max_x = np.max([np.max(x_coord) for x_coord in x_coords])
+            max_y = np.max([np.max(y_coord) for y_coord in y_coords])
+            w = max_x - min_x + 1
+            h = max_y - min_y + 1
+
+            return {
+                "id": annotation_id,
+                "image_id": _build_image_id(annotation_file),
+                "category_id": categories[annotation.annotation_class.name],
+                "segmentation": {
+                    "counts": counts,
+                    "size": [annotation_file.image_height, annotation_file.image_width],
+                },
+                "area": 0,
+                "bbox": [min_x, min_y, w, h],
+                "iscrowd": 1,
+                "extra": _build_extra(annotation),
+            }
     elif annotation_type == "tag":
         pass
     elif annotation_type == "bounding_box":

e2e_tests/data/convert/coco/from/base_annotation.json

@@ -3,7 +3,15 @@
   "schema_ref": "https://darwin-public.s3.eu-west-1.amazonaws.com/darwin_json/2.0/schema.json",
   "item": {
     "name": "",
-    "path": "/"
+    "path": "/",
+    "slots": [
+      {
+        "type": "image",
+        "slot_name": "0",
+        "width": 1080,
+        "height": 1920
+      }
+    ]
   },
   "annotations": [
     {
@@ -59,6 +67,24 @@
               "x": 0.0,
               "y": 1.0
             }
+          ],
+          [
+            {
+              "x": 1.0,
+              "y": 0.0
+            },
+            {
+              "x": 1.0,
+              "y": 1.0
+            },
+            {
+              "x": 0.0,
+              "y": 1.0
+            },
+            {
+              "x": 0.0,
+              "y": 0.0
+            }
           ]
         ]
       }

e2e_tests/data/convert/coco/to/output.json

@@ -19,8 +19,8 @@
       "license": 0,
       "file_name": "",
       "coco_url": "n/a",
-      "height": null,
-      "width": null,
+      "height": 1920,
+      "width": 1080,
       "date_captured": "",
       "flickr_url": "n/a",
       "darwin_url": null,
@@ -60,26 +60,27 @@
       "id": 3,
       "image_id": 2043925204,
       "category_id": 3961009249,
-      "segmentation": [
-        [
-          0.0,
-          0.0,
-          1.0,
-          0.0,
-          1.0,
-          1.0,
-          0.0,
-          1.0
+      "segmentation": {
+        "counts": [
+          0,
+          2,
+          1918,
+          2,
+          2071678
+        ],
+        "size": [
+          1920,
+          1080
         ]
-      ],
-      "area": 1.0,
+      },
+      "area": 0,
       "bbox": [
-        0.0,
-        0.0,
-        1.0,
-        1.0
+        0,
+        0,
+        2,
+        2
       ],
-      "iscrowd": 0,
+      "iscrowd": 1,
       "extra": {}
     }
   ],

tests/darwin/exporter/formats/export_coco_test.py

@@ -14,12 +14,14 @@ def annotation_file(self) -> dt.AnnotationFile:
             filename="test.json",
             annotation_classes=set(),
             annotations=[],
+            image_height=1920,
+            image_width=1080,
         )
 
     def test_polygon_include_extras(self, annotation_file: dt.AnnotationFile):
         polygon = dt.Annotation(
             dt.AnnotationClass("polygon_class", "polygon"),
-            {"paths": [{"x": 1, "y": 1}, {"x": 2, "y": 2}, {"x": 1, "y": 2}]},
+            {"paths": [[{"x": 1, "y": 1}, {"x": 2, "y": 2}, {"x": 1, "y": 2}]]},
             [dt.make_instance_id(1)],
         )
 
@@ -29,6 +31,34 @@ def test_polygon_include_extras(self, annotation_file: dt.AnnotationFile):
             "extra"
         ] == {"instance_id": 1}
 
+    def test_complex_polygon(self, annotation_file: dt.AnnotationFile):
+        polygon = dt.Annotation(
+            dt.AnnotationClass("polygon_class", "polygon"),
+            {
+                "paths": [
+                    [{"x": 1, "y": 1}, {"x": 2, "y": 2}, {"x": 1, "y": 2}],
+                    [{"x": 3, "y": 3}, {"x": 4, "y": 4}, {"x": 3, "y": 4}],
+                ]
+            },
+            [],
+        )
+
+        categories = {"polygon_class": 1}
+
+        annotations = coco._build_annotation(annotation_file, 1, polygon, categories)
+        assert annotations["segmentation"]["counts"] == [
+            1921,
+            2,
+            1919,
+            1,
+            1920,
+            2,
+            1919,
+            1,
+            2065915,
+        ]
+        assert annotations["segmentation"]["size"] == [1920, 1080]
+
     def test_bounding_boxes_include_extras(self, annotation_file: dt.AnnotationFile):
         bbox = dt.Annotation(
             dt.AnnotationClass("bbox_class", "bounding_box"),