Commit d6330d80 authored by Josef Brandt's avatar Josef Brandt
Browse files

Bugfix plus additional checkbox for inverting threshold.

parent 6d428c36

.gitignore

0 → 100644
+8 −0
Original line number Diff line number Diff line 


__pycache__/



*.c



*.pyd



gepard\.cfg

segmentation.py

+11 −5
Original line number Diff line number Diff line
@@ -52,6 +52,7 @@ class Segmentation(object): 
                                'lowThresh': 0.2,

                                'activateUpThresh': False,

                                'upThresh': 0.5,

                                'invertThresh': False,

                                'maxholebrightness': 0.5,

#                                'erodeconvexdefects': 0,

                                'minparticlearea': 20,
@@ -73,9 +74,10 @@ class Segmentation(object): 
        parlist = [Parameter("contrastCurve", np.ndarray, self.detectParams['contrastCurve'], helptext="Curve contrast"),

                   Parameter("activateContrastCurve", np.bool, self.detectParams['activateContrastCurve'], helptext="activate Contrast curve", show=True, linkedParameter='contrastCurve'),

                   Parameter("blurRadius", int, self.detectParams['blurRadius'], 3, 99, 1, 2, helptext="Blur radius", show=True),

                   Parameter("activateLowThresh", np.bool, self.detectParams['activateThresh2'], helptext="activate lower threshold", show=False, linkedParameter='lowThresh'),

                   Parameter("invertThresh", np.bool, self.detectParams['invertThresh'], helptext="Invert the current threshold", show=False),

                   Parameter("activateLowThresh", np.bool, self.detectParams['activateLowThresh'], helptext="activate lower threshold", show=False, linkedParameter='lowThresh'),

                   Parameter("lowThresh", float, self.detectParams['lowThresh'], .01, .9, 2, .02, helptext="Lower threshold", show=True),

                   Parameter("activateUpThresh", np.bool, self.detectParams['activateThresh2'], helptext="activate upper threshold", show=False, linkedParameter='upThresh'),

                   Parameter("activateUpThresh", np.bool, self.detectParams['activateUpThresh'], helptext="activate upper threshold", show=False, linkedParameter='upThresh'),

                   Parameter("upThresh", float, self.detectParams['upThresh'], .01, 1.0, 2, .02, helptext="Upper threshold", show=True),

                   Parameter("maxholebrightness", float, self.detectParams['maxholebrightness'], 0, 1, 2, 0.02, helptext="Close holes brighter than..", show = True),

#                   Parameter("erodeconvexdefects", int, self.detectParams['erodeconvexdefects'], 0, 20, helptext="Erode convex defects", show=True),     #TODO: Consider removing it entirely. It is usually not used...
@@ -320,6 +322,8 @@ class Segmentation(object): 
        # thresholding

        if self.activateLowThresh and not self.activateUpThresh:

            thresh = cv2.threshold(blur, int(255*self.lowThresh), 255, cv2.THRESH_BINARY)[1]

            if self.invertThresh:

                thresh = 255-thresh

            if return_step=="lowThresh": return thresh, 0

            print("lower threshold")

            if self.cancelcomputation:
@@ -329,7 +333,8 @@ class Segmentation(object): 
            lowerLimit, upperLimit = np.round(self.lowThresh*255), np.round(self.upThresh*255)

            thresh = np.zeros_like(blur)

            thresh[np.where(np.logical_and(blur >= lowerLimit, blur <= upperLimit))] = 255

            

            if self.invertThresh:

                thresh = 255-thresh

            if return_step=="lowThresh" or return_step=="upThresh": return thresh, 0

            print("between threshold")

            if self.cancelcomputation:
@@ -338,6 +343,8 @@ class Segmentation(object): 
        elif not self.activateLowThresh and self.activateUpThresh:

            thresh = np.zeros_like(blur)

            thresh[np.where(blur <= np.round(self.upThresh*255))] = 255

            if self.invertThresh:

                thresh = 255-thresh

            if return_step=="upThresh": return thresh, 0

            print("upper threshold")

            if self.cancelcomputation:
@@ -346,8 +353,7 @@ class Segmentation(object): 
            if self.parent is not None:

                self.parent.raiseWarning('No thresholding method selected!\nAborted detection..')

            print('NO THRESHOLDING SELECTED!')

            return None, None, None

            

            return blur, 0

        

        #close holes darkter than self.max_brightness

        self.closeBrightHoles(thresh, blur, self.maxholebrightness)