feat: add detection strategies

Author: electricalgorithm

core/strategies/detectors/base_detector_strategy.py

@@ -0,0 +1,28 @@
+"""
+The base strategy for detector strategies.
+This strategy is used to define the interface for all detector strategies.
+"""
+
+from abc import abstractmethod, ABCMeta
+from dataclasses import dataclass
+
+import numpy
+
+
+@dataclass
+class DetectorResult:
+    """This class represents the result of a detector strategy."""
+    image: numpy.ndarray
+    human_found: bool
+    regions: list[tuple[int, int, int, int]] = None
+    num_detections: float = None
+
+
+class BaseDetectorStrategy(metaclass=ABCMeta):
+    """
+    The base strategy for detector strategies.
+    """
+    @staticmethod
+    @abstractmethod
+    def detect_humans(frame: numpy.ndarray) -> DetectorResult:
+        """This method detects if there are any humans in the frame."""

core/strategies/detectors/hog_descriptor_strategy.py

@@ -0,0 +1,32 @@
+"""
+The HOG descriptor strategy for detector strategies.
+"""
+import cv2
+import numpy
+from .base_detector_strategy import BaseDetectorStrategy, DetectorResult
+
+
+class HogDescriptorStrategy(BaseDetectorStrategy):
+    """
+    The HOG descriptor strategy for detector strategies.
+    """
+    @staticmethod
+    def detect_humans(frame: numpy.ndarray) -> DetectorResult:
+        """This method detects if there are any humans in the frame."""
+        # Detect humans in the frame.
+        hog_detector = cv2.HOGDescriptor()
+        hog_detector.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
+        regions, num_detections = hog_detector.detectMultiScale(
+            frame,
+            winStride=(2, 2),
+            padding=(4, 4),
+            scale=1.03,
+        )
+
+        result = DetectorResult(
+            image=frame,
+            human_found=len(num_detections) > 0,
+            regions=regions,
+            num_detections=num_detections,
+        )
+        return result