Merge to main

fastlabel/__init__.py

@@ -1142,24 +1142,39 @@ def __export_index_color_image(self, task: list, output_dir: str, pallete: List[
         image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
 
         index = 1
+        # In case segmentation, to avoid hollowed points overwrite other segmentation in them, segmentation rendering process is different from other annotation type
+        seg_mask_images = []
         for annotation in task["annotations"]:
             color = index if is_instance_segmentation else classes.index(
                 annotation["value"]) + 1
             if annotation["type"] == AnnotationType.segmentation.value:
+                # Create each annotation's masks and merge them finally
+                seg_mask_ground = Image.new(
+                    "RGB", (task["width"], task["height"]), 0)
+                seg_mask_image = np.array(seg_mask_ground)
+                seg_mask_image = cv2.cvtColor(seg_mask_image, cv2.COLOR_BGR2GRAY)
+
                 for region in annotation["points"]:
                     count = 0
                     for points in region:
                         if count == 0:
-                            cv_draw_points = self.__get_cv_draw_points(points)
+                            cv_draw_points = []
+                            if utils.is_clockwise(points):
+                                cv_draw_points = self.__get_cv_draw_points(
+                                    points)
+                            else:
+                                cv_draw_points = self.__get_cv_draw_points(
+                                    utils.reverse_points(points))
                             cv2.fillPoly(
-                                image, [cv_draw_points], color, lineType=cv2.LINE_8, shift=0)
+                                seg_mask_image, [cv_draw_points], color, lineType=cv2.LINE_8, shift=0)
                         else:
                             # Reverse hollow points for opencv because this points are counter clockwise
                             cv_draw_points = self.__get_cv_draw_points(
                                 utils.reverse_points(points))
                             cv2.fillPoly(
-                                image, [cv_draw_points], 0, lineType=cv2.LINE_8, shift=0)
+                                seg_mask_image, [cv_draw_points], 0, lineType=cv2.LINE_8, shift=0)
                         count += 1
+                seg_mask_images.append(seg_mask_image)
             elif annotation["type"] == AnnotationType.polygon.value:
                 cv_draw_points = self.__get_cv_draw_points(
                     annotation["points"])
@@ -1174,6 +1189,10 @@ def __export_index_color_image(self, task: list, output_dir: str, pallete: List[
                 continue
             index += 1
 
+        # For segmentation, merge each mask images
+        for seg_mask_image in seg_mask_images:
+            image = image | seg_mask_image
+
         image_path = os.path.join(
             output_dir, utils.get_basename(task["name"]) + ".png")
         os.makedirs(os.path.dirname(image_path), exist_ok=True)

fastlabel/utils.py

@@ -1,5 +1,7 @@
 import os
 import base64
+import numpy as np
+import geojson
 from typing import List
 
 
@@ -41,3 +43,26 @@ def reverse_points(points: List[int]) -> List[int]:
             reversed_points.insert(
                 0, points[index])
     return reversed_points
+
+def is_clockwise(points: list) -> bool:
+    """
+    points: [x1, y1, x2, y2, x3, y3, ... xn, yn]
+    Sum over the edges, (x2 − x1)(y2 + y1). 
+    If the result is positive the curve is clockwise, if it's negative the curve is counter-clockwise.
+
+    The above is assumes a normal Cartesian coordinate system. 
+    HTML5 canvas, use an inverted Y-axis.
+    Therefore If the area is negative, the curve is clockwise.
+    """
+    points_splitted = [points[idx:idx + 2]
+                                    for idx in range(0, len(points), 2)]
+    polygon_geo = geojson.Polygon(points_splitted)
+    coords = np.array(list(geojson.utils.coords(polygon_geo)))
+    xs, ys = map(list, zip(*coords))
+    xs.append(xs[0])
+    ys.append(ys[0])
+    sum_edges = sum((xs[i] - xs[i - 1]) * (ys[i] + ys[i - 1]) for i in range(1, len(points_splitted))) / 2.0
+
+    if sum_edges < 0:
+        return True
+    return False 

setup.py

@@ -8,7 +8,7 @@
 
 setuptools.setup(
     name="fastlabel",
-    version="0.11.8",
+    version="0.11.9",
     author="eisuke-ueta",
     author_email="eisuke.ueta@fastlabel.ai",
     description="The official Python SDK for FastLabel API, the Data Platform for AI",