Merge branch 'develop' into CTX-4070

* develop:
  CTX-4079: Redesigned terminate condition for experiment worker process - Added log file output for experiment worker process for debugging purposes
  CTX-4251: Update "model-queue/custom" to "run" endpoint
  Version bump
  CTX-4219: Make root not private to make it available outside the class - Name starts with an underscore to mark it as internally used don't touch
  CTX-4083: Moved heartbeat to the metrics worker process - Renamed metrics worker process to experiment worker
  Version bump
  CTX-4102: Fix terminating metrics process on experiment process kill
  CTX-4166: Implemented Sequence sample import
  CTX-3890: Changed division to //
  CTX-3890: Converted wider code to be compatible with int based bounding boxes
  CTX-3890: Changed width and height variables from float to int
  Update README.md

README.md

@@ -44,7 +44,7 @@ if __name__ == "__main__":
     initializeProject(main)
 ```
 
-(Read the documentation and learn how you can migrate your project to the Coretex platform -> [Migrate your project to Coretex](https://app.gitbook.com/o/6QxmEiF5ygi67vFH3kV1/s/YoN0XCeop3vrJ0hyRKxx/getting-started/demo-experiments/migrate-your-project-to-coretex))
+Read the documentation and learn how you can migrate your project to the Coretex platform -> [Migrate your project to Coretex](https://app.gitbook.com/o/6QxmEiF5ygi67vFH3kV1/s/YoN0XCeop3vrJ0hyRKxx/getting-started/demo-experiments/migrate-your-project-to-coretex)
 
 ## Key Features
 

coretex/coretex/annotation/image/bbox.py

@@ -28,49 +28,49 @@ class BBox(Codable):
 
         Properties
         ----------
-        minX : float
+        minX : int
             top left x coordinate
-        minY : float
+        minY : int
             top left y coordinate
-        width : float
+        width : int
             width of the bounding box
-        height : float
+        height : int
             height of the bounding box
     """
 
-    def __init__(self, minX: float = 0, minY: float = 0, width: float = 0, height: float = 0) -> None:
+    def __init__(self, minX: int = 0, minY: int = 0, width: int = 0, height: int = 0) -> None:
         self.minX: Final = minX
         self.minY: Final = minY
 
         self.width: Final = width
         self.height: Final = height
 
     @property
-    def maxX(self) -> float:
+    def maxX(self) -> int:
         """
             Returns
             -------
-            float -> bottom right x coordinate
+            int -> bottom right x coordinate
         """
 
         return self.minX + self.width
 
     @property
-    def maxY(self) -> float:
+    def maxY(self) -> int:
         """
             Returns
             -------
-            float -> bottom right y coordinate
+            int -> bottom right y coordinate
         """
 
         return self.minY + self.height
 
     @property
-    def polygon(self) -> List[float]:
+    def polygon(self) -> List[int]:
         """
             Returns
             -------
-            List[float] -> Bounding box represented as a polygon (x, y) values
+            List[int] -> Bounding box represented as a polygon (x, y) values
         """
 
         return [
@@ -91,20 +91,20 @@ def _keyDescriptors(cls) -> Dict[str, KeyDescriptor]:
         return descriptors
 
     @classmethod
-    def create(cls, minX: float, minY: float, maxX: float, maxY: float) -> Self:
+    def create(cls, minX: int, minY: int, maxX: int, maxY: int) -> Self:
         """
             Utility constructor which has maxX and maxY as parameters instead
             of width and height
 
             Parameters
             ----------
-            minX : float
+            minX : int
                 top left x coordinate
-            minY : float
+            minY : int
                 top left y coordinate
-            maxX : float
+            maxX : int
                 bottom right x coordinate
-            maxY : float
+            maxY : int
                 bottom right y coordinate
 
             Returns
@@ -115,15 +115,15 @@ def create(cls, minX: float, minY: float, maxX: float, maxY: float) -> Self:
         return cls(minX, minY, maxX - minX, maxY - minY)
 
     @classmethod
-    def fromPoly(cls, polygon: List[float]) -> Self:
+    def fromPoly(cls, polygon: List[int]) -> Self:
         """
             Creates bounding box from a polygon, by finding
             the minimum x and y coordinates and calculating
             width and height of the polygon
 
             Parameters
             ----------
-            polygon : List[float]
+            polygon : List[int]
                 list of x, y points - length must be even
 
             Returns
@@ -140,8 +140,8 @@ def fromPoly(cls, polygon: List[float]) -> Self:
             "minX: 0, minY: 0, width: 4, height: 3"
         """
 
-        x: List[float] = []
-        y: List[float] = []
+        x: List[int] = []
+        y: List[int] = []
 
         for index, value in enumerate(polygon):
             if index % 2 == 0:

coretex/coretex/annotation/image/coretex_format.py

@@ -29,11 +29,11 @@
 from ....codable import Codable, KeyDescriptor
 
 
-SegmentationType = List[float]
+SegmentationType = List[int]
 
 
-def toPoly(segmentation: List[float]) -> List[Tuple[float, float]]:
-    points: List[Tuple[float, float]] = []
+def toPoly(segmentation: List[int]) -> List[Tuple[int, int]]:
+    points: List[Tuple[int, int]] = []
 
     for index in range(0, len(segmentation) - 1, 2):
         points.append((segmentation[index], segmentation[index + 1]))
@@ -145,42 +145,42 @@ def extractBinaryMask(self, width: int, height: int) -> np.ndarray:
 
         return binaryMask
 
-    def centroid(self) -> Tuple[float, float]:
+    def centroid(self) -> Tuple[int, int]:
         """
             Calculates centroid of segmentations
 
             Returns
             -------
-            Tuple[float, float] -> x, y coordinates of centroid
+            Tuple[int, int] -> x, y coordinates of centroid
         """
 
         flattenedSegmentations = [element for sublist in self.segmentations for element in sublist]
 
         listCX = [value for index, value in enumerate(flattenedSegmentations) if index % 2 == 0]
-        centerX = fsum(listCX) / len(listCX)
+        centerX = sum(listCX) // len(listCX)
 
         listCY = [value for index, value in enumerate(flattenedSegmentations) if index % 2 != 0]
-        centerY = fsum(listCY) / len(listCY)
+        centerY = sum(listCY) // len(listCY)
 
         return centerX, centerY
 
-    def centerSegmentations(self, newCentroid: Tuple[float, float]) -> None:
+    def centerSegmentations(self, newCentroid: Tuple[int, int]) -> None:
         """
             Centers segmentations to the specified center point
 
             Parameters
             ----------
-            newCentroid : Tuple[float, float]
+            newCentroid : Tuple[int, int]
                 x, y coordinates of centroid
             """
 
         newCenterX, newCenterY = newCentroid
         oldCenterX, oldCenterY = self.centroid()
 
-        modifiedSegmentations: List[List[float]] = []
+        modifiedSegmentations: List[List[int]] = []
 
         for segmentation in self.segmentations:
-            modifiedSegmentation: List[float] = []
+            modifiedSegmentation: List[int] = []
 
             for i in range(0, len(segmentation), 2):
                 x = segmentation[i] + (newCenterX - oldCenterX)
@@ -203,7 +203,7 @@ def rotateSegmentations(self, degrees: int) -> None:
                 degree of rotation
         """
 
-        rotatedSegmentations: List[List[float]] = []
+        rotatedSegmentations: List[List[int]] = []
         centerX, centerY = self.centroid()
 
         # because rotations with image and segmentations doesn't go in same direction
@@ -212,14 +212,14 @@ def rotateSegmentations(self, degrees: int) -> None:
         cosang, sinang = cos(theta), sin(theta)
 
         for segmentation in self.segmentations:
-            rotatedSegmentation: List[float] = []
+            rotatedSegmentation: List[int] = []
 
             for i in range(0, len(segmentation), 2):
                 x = segmentation[i] - centerX
                 y = segmentation[i + 1] - centerY
 
-                newX = (x * cosang - y * sinang) + centerX
-                newY = (x * sinang + y * cosang) + centerY
+                newX = int(x * cosang - y * sinang) + centerX
+                newY = int(x * sinang + y * cosang) + centerY
 
                 rotatedSegmentation.append(newX)
                 rotatedSegmentation.append(newY)
@@ -238,17 +238,17 @@ class CoretexImageAnnotation(Codable):
         ----------
         name : str
             name of annotation class
-        width : float
+        width : int
             width of annotation
-        height : float
+        height : int
             height of annotation
         instances : List[CoretexSegmentationInstance]
             list of SegmentationInstance objects
     """
 
     name: str
-    width: float
-    height: float
+    width: int
+    height: int
     instances: List[CoretexSegmentationInstance]
 
     @classmethod
@@ -262,8 +262,8 @@ def _keyDescriptors(cls) -> Dict[str, KeyDescriptor]:
     def create(
         cls,
         name: str,
-        width: float,
-        height: float,
+        width: int,
+        height: int,
         instances: List[CoretexSegmentationInstance]
     ) -> Self:
         """
@@ -273,9 +273,9 @@ def create(
             ----------
             name : str
                 name of annotation class
-            width : float
+            width : int
                 width of annotation
-            height : float
+            height : int
                 height of annotation
             instances : List[CoretexSegmentationInstance]
                 list of SegmentationInstance objects

coretex/coretex/conversion/converters/create_ml_converter.py

@@ -53,10 +53,10 @@ def _extractLabels(self) -> Set[str]:
 
         return labels
 
-    def __extractBBox(self, bbox: Dict[str, float]) -> BBox:
+    def __extractBBox(self, bbox: Dict[str, int]) -> BBox:
         return BBox(
-            bbox["x"] - bbox["width"] / 2,
-            bbox["y"] - bbox["height"] / 2,
+            bbox["x"] - bbox["width"] // 2,
+            bbox["y"] - bbox["height"] // 2,
             bbox["width"],
             bbox["height"]
         )

coretex/coretex/conversion/converters/human_segmentation_converter.py

@@ -65,7 +65,7 @@ def _dataSource(self) -> List[str]:
     def _extractLabels(self) -> Set[str]:
         return set(["background", "human"])
 
-    def __extractPolygons(self, annotationPath: str, imageWidth: int, imageHeight: int) -> List[List[float]]:
+    def __extractPolygons(self, annotationPath: str, imageWidth: int, imageHeight: int) -> List[List[int]]:
         maskImage = Image.open(annotationPath)
         if maskImage is None:
             return []
@@ -81,7 +81,7 @@ def __extractPolygons(self, annotationPath: str, imageWidth: int, imageHeight: i
 
         contours = skimage.measure.find_contours(subMaskArray, 0.5)
 
-        segmentations: List[List[float]] = []
+        segmentations: List[List[int]] = []
         for contour in contours:
             for i in range(len(contour)):
                 row, col = contour[i]

coretex/coretex/conversion/converters/label_me_converter.py

@@ -62,7 +62,7 @@ def __extractInstance(self, shape: Dict[str, Any]) -> Optional[CoretexSegmentati
             logging.getLogger("coretexpylib").info(f">> [Coretex] Class: ({label}) is not a part of dataset")
             return None
 
-        points: List[float] = np.array(shape["points"]).flatten().tolist()
+        points: List[int] = np.array(shape["points"]).flatten().tolist()
         bbox = BBox.fromPoly(points)
 
         return CoretexSegmentationInstance.create(coretexClass.classIds[0], bbox, [points])

coretex/coretex/conversion/converters/pascal/instance_extractor.py

@@ -31,7 +31,7 @@
 from ....dataset import ImageDataset
 
 
-ContourPoints = List[List[float]]
+ContourPoints = List[List[int]]
 SegmentationPolygon = List[ContourPoints]
 
 

coretex/coretex/conversion/converters/pascal/pascal_2012_converter.py

@@ -21,7 +21,7 @@
 import glob
 import xml.etree.ElementTree as ET
 
-from .shared import getTag, toFloat
+from .shared import getTag, toInt
 from .instance_extractor import InstanceExtractor
 from ...base_converter import BaseConverter
 from .....coretex import CoretexImageAnnotation
@@ -84,7 +84,7 @@ def __extractImageAnnotation(self, root: ET.Element) -> None:
         if size is None:
             return
 
-        width, height = toFloat(size, "width", "height")
+        width, height = toInt(size, "width", "height")
         if width is None or height is None:
             return
 

coretex/coretex/conversion/converters/pascal/shared.py

@@ -38,6 +38,16 @@ def toFloat(rootEl: ET.Element, firstEl: str, secondEl: str) -> Tuple[Optional[f
     return (float(firstVal), float(secondVal))
 
 
+def toInt(rootEl: ET.Element, firstEl: str, secondEl: str) -> Tuple[Optional[int], Optional[int]]:
+    firstVal = getTag(rootEl, firstEl)
+    secondVal = getTag(rootEl, secondEl)
+
+    if firstVal is None or secondVal is None:
+        return (None, None)
+
+    return (int(firstVal), int(secondVal))
+
+
 def getBoxes(bndbox: ET.Element) -> Optional[Dict[str, float]]:
     xmin, ymin = toFloat(bndbox, "xmin", "ymin")
     xmax, ymax = toFloat(bndbox, "xmax", "ymax")

coretex/coretex/conversion/converters/voc_converter.py

@@ -22,7 +22,7 @@
 import glob
 import xml.etree.ElementTree as ET
 
-from .pascal.shared import getTag, getBoxes, toFloat
+from .pascal.shared import getTag, getBoxes, toInt
 from ..base_converter import BaseConverter
 from ...annotation import CoretexImageAnnotation, CoretexSegmentationInstance, BBox
 
@@ -91,7 +91,7 @@ def _extractImageAnnotation(self, root: ET.Element) -> None:
         if size is None:
             return
 
-        width, height = toFloat(size, "width", "height")
+        width, height = toInt(size, "width", "height")
         if width is None or height is None:
             return
 

coretex/coretex/conversion/converters/yolo_converter.py

@@ -67,10 +67,10 @@ def __extractBBox(self, rawInstance: List[str], width: int, height: int) -> BBox
         wYolo = float(rawInstance[3])
         hYolo = float(rawInstance[4])
 
-        boxWidth = wYolo * width
-        boxHeight = hYolo * height
-        xMin = float(xYolo * width - (boxWidth / 2))
-        yMin = float(yYolo * height - (boxHeight / 2))
+        boxWidth = int(wYolo * width)
+        boxHeight = int(hYolo * height)
+        xMin = int(xYolo * width - (boxWidth / 2))
+        yMin = int(yYolo * height - (boxHeight / 2))
 
         return BBox(xMin, yMin, boxWidth, boxHeight)
 

coretex/coretex/dataset/__init__.py

@@ -23,3 +23,4 @@
 from .local_dataset import LocalDataset
 from .network_dataset import NetworkDataset
 from .utils import downloadDataset
+from .sequence_dataset import SequenceDataset, LocalSequenceDataset