fixed slicing function

Scripts/ai4hdr_utils.py

@@ -23,7 +23,6 @@ def sliceImage( imgArr: np.array, newSize: tuple ) -> dict:
     returns:  dictionary containing the following information
     {
         "slicedImages": [ ( xStartPos, yStartPos, slicedImgArr ) ],
-        "pixelsLost"  : int,
         "sliceCount"  : int
     }
     OR empty dictionary if slicing was unable to be completed
@@ -33,28 +32,28 @@ def sliceImage( imgArr: np.array, newSize: tuple ) -> dict:
     newWidth  = newSize[0]
     newHeight = newSize[1]
 
-    # return empty dictionary if desired slice is larger than image
+    # Return empty dictionary if desired slice is larger than image
     if newWidth > width or newHeight > height:
         return {}
 
-    # all slices will be uniform, meaning 
-    maxWidth  = ( width // newWidth ) * newWidth
-    maxHeight = ( height // newHeight ) * newHeight
-
-    # return data
-    pixelsLost    = ( width - maxWidth ) + ( height - maxHeight )
+    # Return data
     newSliceCount = 0
     imageList     = []
 
-    # process image
-    for i in range( 0, maxWidth, newWidth ):
-        for j in range( 0, maxHeight, newHeight ):
+    # Process image
+    for i in range( 0, width, newWidth ):
+        for j in range( 0, height, newHeight ):
             newSliceCount += 1
-            imageList.append( ( i, j, imgArr[i:i+newWidth, j:j+newHeight, :] ) )
+            # Create array of zeros of slice size
+            base = np.zeros( ( newWidth, newHeight, imgArr.shape[2] ) )
+            # Slice image and broadcase to base array
+            # Slice will be blacked out when outside range of original image
+            sliceArr = imgArr[i:i+newWidth, j:j+newHeight, :]
+            base[ :sliceArr.shape[0], :sliceArr.shape[1]] = sliceArr
+            imageList.append( ( i, j, base ) )
 
     return {
         "slicedImages": imageList,
-        "pixelsLost"  : pixelsLost,
         "sliceCount"  : newSliceCount
     }