fix

backend/src/NPMean.py

@@ -6,20 +6,31 @@ class NPMeanSequential:
     def __init__(self):
         self.i0 = None
         self.i1 = None
-    def forward(self, img1): #forward method calculates out mean of new img, and saves current img as old
+    def sceneDetect(self, img1):
         if self.i0 is None:
             self.i0 = img1
             self.image0mean = np.mean(self.i0)
             return
         self.i1 = img1
-        self.img1mean = np.mean(self.i1)
-
-    def isSceneChange(self):
-        if self.image0mean > self.img1mean + 20 or self.image0mean < self.img1mean - 20:
-            self.image0mean = self.img1mean
+        img1mean = np.mean(self.i1)
+        if self.image0mean > img1mean + 20 or self.image0mean < img1mean - 20:
+            self.image0mean = img1mean
             return True
-        self.image0mean = self.img1mean
+        self.image0mean = img1mean
         return False
 
-    def isMeanEqual(self):
-        return self.image0mean == self.img1mean
+    def isEqualImages(self,img1):
+        if self.i0 is None:
+            self.i0 = img1
+            self.image0mean = np.mean(self.i0)
+            return
+        self.i1 = img1
+        img1mean = np.mean(self.i1)
+        if (self.i0==self.i1).all():
+            self.image0mean = img1mean
+            self.i0 = self.i1
+            return True
+        self.i0 = self.i1
+        self.image0mean = img1mean
+        return False
+

backend/src/SceneDetect.py

@@ -97,8 +97,7 @@ def getMeanTransitions(self):
         detector = NPMeanSequential()
         for frame_num in tqdm(range(self.totalInputFrames - 1)):
             frame = bytesTo100x100img(self.readQueue.get())
-            detector.forward(frame)
-            if detector.isSceneChange():
+            if detector.sceneDetect(frame):
                 sceneChangeQueue.put(frame_num-1)
         return sceneChangeQueue