add legend to UnivariatePlot

README.md

@@ -7,7 +7,8 @@ image files or frames that were extracted from moving image files.
 ToDo
 ====
 
-[] `MultivariatePlot` muss noch auf die selbe Simplizität wie `UnivariatePlot`
-   umgestellt werden
-[] Bisher funktioniert nur der LightDark Contrast, andere Kontraste
-   implementieren
+[]  `MultivariatePlot` muss noch auf die selbe Simplizität wie `UnivariatePlot`
+    umgestellt werden
+[]  gettter und setter für Frames.start setzen und das Rekursionsproblem lösen
+[x] Bisher funktioniert nur der LightDark Contrast, andere Kontraste
+    implementieren

itten/contrasts.py

@@ -3,11 +3,16 @@ import cv2 as cv
 
 # TODO create generic class
 
+class Contrast(object):
+    """Base class for color contrasts"""
+    def __init__(self, img):
+        self._img = img
+        
 
-class LightDark(object):
+class LightDark(Contrast):
     """docstring for LightDark"""
     def __init__(self, img, method='luminance'):
-        self._img = img
+        super(LightDark, self).__init__(img)
 
         meth = getattr(LightDark, method)
         self.ctrst = meth(self)
@@ -43,3 +48,41 @@ class LightDark(object):
         lightness = img[:, :, 1].copy()
 
         return lightness
+
+
+class Saturation(Contrast):
+    """docstring for Saturation"""
+    def __init__(self, img, method='saturation'):
+        super(Saturation, self).__init__(img)
+
+        meth = getattr(Saturation, method)
+        self.ctrst = meth(self)
+
+    def saturation(self):
+        """docstring for saturation"""
+        img = cv.cvtColor(self._img, cv.COLOR_BGR2HSV)
+        saturations = img[:, :, 1].copy()
+
+        return saturations
+
+    def chroma(self):
+        """docstring for chroma"""
+        pass
+
+
+class Hue(Contrast):
+    """docstring for Saturation"""
+    def __init__(self, img, method='hue'):
+        super(Hue, self).__init__(img)
+
+        meth = getattr(Hue, method)
+        self.ctrst = meth(self)
+
+    def hue(self):
+        """docstring for hue"""
+        
+        img = cv.cvtColor(self._img, cv.COLOR_BGR2HSV)
+        hues = img[:, :, 0].copy()
+
+        return hues
+

itten/movie.py

@@ -33,6 +33,10 @@ class Frames(object):
         self.end = end
         self.frm_cnt = 0
 
+    # TODO start als property erzeugt bisher eine Endlosschleife wei
+    # count_frames sart und end brauchen und so gegenseitig sart und end nicht
+    # gesetzt wird
+
     @property
     def end(self):
         return self.__end
@@ -41,16 +45,16 @@ class Frames(object):
     def end(self, nr):
         if nr == 0:
             self.__end = self.frm_length
-            self.frm_cnt = self.count_frames
+            self.frm_cnt = self.count_frames()
         elif nr > self.frm_length:
             self.__end = self.frm_length - 1
-            self.frm_cnt = self.count_frames
+            self.frm_cnt = self.count_frames()
         elif nr < self.start:
             self.__end = self.start + 1
-            self.frm_cnt = self.count_frames
+            self.frm_cnt = self.count_frames()
         else:
             self.__end = nr
-            self.frm_cnt = self.count_frames
+            self.frm_cnt = self.count_frames()
 
     @property
     def frm_cnt(self):

itten/views.py

@@ -327,15 +327,18 @@ class UnivariateSequence(View):
         """
 
         obj = View.__new__(cls, frames, input_array=input_array)
+        obj.feature = None
         return obj
 
     def __array_finalize__(self, obj):
         if obj is None: return
+        self._threshold = getattr(obj, 'feature', None)
         View.__array_finalize__(self, obj)
 
     # TODO später ersetzen durch numpy mean/deviation in Kombination mit anderen Möglichkeiten
     @staticmethod
     def meanmad(values):
+
         values = values.flatten()
         length = values.size
         points = np.sum(values)
@@ -360,6 +363,7 @@ class UnivariateSequence(View):
            save: save plot also to disk
         """
         # set class properties
+        self.feature = 'mean'
         self._contrast = ctrst
         self._method = method
         self._frame_step = frm_stp
@@ -413,6 +417,7 @@ class UnivariateSequence(View):
            save: save plot also to disk
         """
         # set class properties
+        self.feature = 'absolute_deviation'
         self._contrast = ctrst
         self._method = method
         self._frame_step = frm_stp

itten/visuals.py

@@ -124,6 +124,7 @@ class UnivariatePlot(SequencePlot):
 
         # Interpolation mit savitzky_golay funktioniert nicht
         # contrast_points = savitzky_golay(np.array(contrast_points), 51, 7)
-        self._axt.plot(self._x, view)
+        self._axt.plot(self._x, view, label=view.feature)
+        self._axt.legend()
 
         return self.fig

testing/bootstrap.py

@@ -2,12 +2,14 @@ from itten.movie import Movie
 from itten.views import UnivariateSequence
 from itten.visuals import UnivariatePlot
 
-movie = Movie(prefix='rec_', folder='../DHd-2017/Data/Frames/Rec/', end=1100)
-cont = UnivariateSequence(movie._frames)
-cont.seqmean(frm_stp=2)
+movie = Movie(prefix='rec_', folder='../DHd-2017/Data/Frames/Rec/')
+# movie._frames.start = 367
+# movie._frames.end = 784
+cont = UnivariateSequence(movie._frames,)
+cont.seqmean(frm_stp=3, ctrst='saturation')
 viz = UnivariatePlot(cont)
-viz.plot(cont)
-cont.seqmad(frm_stp=2)
+# viz.plot(cont)
+cont.seqmad(frm_stp=3, ctrst='saturation')
 viz.plot(cont)
 viz.saveplt()