Update frmodules

.gitignore

@@ -99,3 +99,6 @@ ENV/
 
 # mypy
 .mypy_cache/
+
+# configure for MacOS
+*.DS_Store

fr/modules/actions/action.py

@@ -5,7 +5,7 @@ def activate(self):
         # Called when action activated
         pass
 
-    def update(self):
+    def __call__(self):
         # Called every frame while action is activated
         pass
 

fr/modules/actions/moveToFace.py

@@ -1,23 +1,26 @@
 # -*- coding: utf-8 -*-
 import cv2
 import math
-from ..analyzers.facedetector import FaceDetector
+from ..submodules.facedetector import FaceDetector
 
 class Noaction(object):
+    def __init__(self):
+        self.fd = FaceDetector()
+
     def activate(self):
         # Called when action activated
         return {}
 
-    def update(self):
+    def __call__(self):
         act = {
             "wheelleft": 0.0,
             "wheelright": 0.0
         }
         # Called every frame while action is activated
-        if str(FaceDetector.biggestFaceRect) != "None":
+        if str(self.fd.biggestFaceRect) != "None":
             # If face exists
-            x, _ = FaceDetector.biggestFaceRectPosNormalized(None)
-            size = FaceDetector.biggestFaceSizeNormalized(None)
+            x, _ = self.fd.biggestFaceRectPosNormalized(None)
+            size = self.fd.biggestFaceSizeNormalized(None)
             if abs(x) > 0.3:
                 if x > 0:
                     # Rotate to left

fr/modules/actions/noaction.py

@@ -5,7 +5,7 @@ def activate(self):
         # Called when action activated
         return {}
 
-    def update(self):
+    def __call__(self):
         # Called every frame while action is activated
         return {}
 

fr/modules/actions/raiseLeftHand.py

@@ -20,7 +20,7 @@ def activate(self):
         act["armleft"] = 1.0
         return act
 
-    def update(self):
+    def __call__(self):
         # Called every frame while action is activated
         pass
 

fr/modules/actions/raiseRightHand.py

@@ -20,7 +20,7 @@ def activate(self):
         act["armright"] = 1.0
         return act
 
-    def update(self):
+    def __call__(self):
         # Called every frame while action is activated
         pass
 

fr/modules/actions/randomMove.py

@@ -21,7 +21,7 @@ def activate(self):
         act["armright"] = 1.0
         return act
 
-    def update(self):
+    def __call__(self):
         # Called every frame while action is activated
         act = BASE_ACTION
         act["armleft"] = math.sin(time.time() * 2)

fr/modules/actions/rotateLeft.py

@@ -15,7 +15,7 @@ def activate(self):
         # Called when action activated
         return {}
 
-    def update(self):
+    def __call__(self):
         # Called every frame while action is activated
         act = BASE_ACTION
         act["wheelleft"] = -0.1

fr/modules/actions/rotateRight.py

@@ -15,7 +15,7 @@ def activate(self):
         # Called when action activated
         return {}
 
-    def update(self):
+    def __call__(self):
         # Called every frame while action is activated
         act = BASE_ACTION
         act["wheelleft"] = 0.1

fr/modules/actions/searchFaces.py

@@ -1,7 +1,7 @@
 # -*- coding: utf-8 -*-
 import time
 import math
-from ..analyzers.facedetector import FaceDetector
+from ..submodules.facedetector import FaceDetector
 
 BASE_ACTION = {
     "armleft": 0.0,
@@ -12,15 +12,15 @@
 
 class SearchFaces(object):
     def __init__(self):
-        pass
+        self.fd = FaceDetector()
 
     def activate(self):
         # Called when action activated
         return {}
 
     def update(self):
         # Called every frame while action is activated
-        facerect = FaceDetector.getFacerect(None)
+        facerect = self.fd.getFacerect(None)
         act = BASE_ACTION
         if str(facerect) != "None" and len(facerect) > 0:
             act["wheelleft"] = 0.0

fr/modules/analyzers/analyzer.py

@@ -4,6 +4,6 @@ class Analyzer(object):
     def __init__(self):
         pass
 
-    def analyze(self, observation):
+    def __call__(self, observation):
         # Return scholar (not vector or dict)
         pass

fr/modules/analyzers/faceXAxis.py

@@ -1,9 +1,11 @@
 # -*- coding: utf-8 -*-
 import cv2
-from .facedetector import FaceDetector
+from ..submodules.facedetector import FaceDetector
 
 class FaceXAxis(object):
+    def __init__(self):
+        self.fd = FaceDetector()
 
-    def analyze(self, observation):
-        x, _ = FaceDetector.biggestFaceRectPosNormalized(observation)
+    def __call__(self, observation):
+        x, _ = self.fd.biggestFaceRectPosNormalized(observation)
         return x

fr/modules/analyzers/faceYAxis.py

@@ -1,9 +1,11 @@
 # -*- coding: utf-8 -*-
 import cv2
-from .facedetector import FaceDetector
+from ..submodules.facedetector import FaceDetector
 
 class FaceYAxis(object):
+    def __init__(self):
+        self.fd = FaceDetector()
 
-    def analyze(self, observation):
-        _, y = FaceDetector.biggestFaceRectPosNormalized(observation)
+    def __call__(self, observation):
+        _, y = self.fd.biggestFaceRectPosNormalized(observation)
         return y

fr/modules/analyzers/isFaceExist.py

@@ -1,12 +1,14 @@
 # -*- coding: utf-8 -*-
 import cv2
 import time
-from .facedetector import FaceDetector
+from ..submodules.facedetector import FaceDetector
 
 class IsFaceExist(object):
+    def __init__(self):
+        self.fd = FaceDetector()
 
-    def analyze(self, observation):
-        facerect = FaceDetector.getFacerect(observation)
+    def __call__(self, observation):
+        facerect = self.fd.getFacerect(observation)
         if str(facerect) == "None": return
         if len(facerect) > 0:
             return 1.0

fr/modules/analyzers/facedetector.py → fr/modules/submodules/facedetector.py

@@ -2,19 +2,21 @@
 import cv2
 import time
 
+# Constants
 # cascade_path = "./haarcascades/haarcascade_frontalface_default.xml"
 cascade_path = "/var/opencv/haarcascades/haarcascade_frontalface_default.xml"
+# refresh rate
+refreshRate = 0.1 # sec
 
 class FaceDetector(object):
-    facerect = None
-    refreshRate = 0.1 # sec
-    lastRefreshed = 0.0 # sec
+    def __init__(self):
+        self.facerect = None
+        self.lastRefreshed = 0.0 # sec
 
-    @classmethod
     def getFacerect(self, observation):
         # Return cached data or not
-        if (time.time() - FaceDetector.lastRefreshed) < FaceDetector.refreshRate or observation == None:
-            return FaceDetector.facerect
+        if (time.time() - self.lastRefreshed) < refreshRate or observation == None:
+            return self.facerect
 
         # Engray image
         if str(observation["image"]) == "None": return
@@ -24,32 +26,29 @@ def getFacerect(self, observation):
         cascade = cv2.CascadeClassifier(cascade_path)
 
         # Get facerect
-        FaceDetector.facerect = cascade.detectMultiScale(
+        self.facerect = cascade.detectMultiScale(
             image_gray, 
             scaleFactor = 1.1,
             minNeighbors = 2,
             minSize = (30, 30)
         )
 
         # Update cache time
-        FaceDetector.lastRefreshed = time.time()
+        self.lastRefreshed = time.time()
 
-        return FaceDetector.facerect
+        return self.facerect
 
-    @classmethod
     def biggestFaceRect(self, observation):
-        facerect = self.getFacerect(observation)
-        if str(facerect) == "None": return
-        return max(facerect, key= (lambda r: r[2] * r[3]))
+        self.facerect = self.getFacerect(observation)
+        if str(self.facerect) == "None": return
+        return max(self.facerect, key= (lambda r: r[2] * r[3]))
 
-    @classmethod
     def biggestFaceSizeNormalized(self, observation):
         width, height, _ = observation["image"].shape
         biggestface = self.biggestFaceRect(observation)
         if str(biggestface) == "None": return 0.0
         return biggestface[2] * biggestface[3] / width / height
 
-    @classmethod
     def biggestFaceRectPosNormalized(self, observation):
         width, height, _ = observation["image"].shape
         biggestface = self.biggestFaceRect(observation)