cleaning up readme

Scripts/ai4hdr_utils.py

@@ -179,37 +179,39 @@ def importAndProcess( imgPath: str, dbPath: str, newImgName: str ):
         os.mkdir( imgSlicedSizePath )
         os.mkdir( imgMSSizePath )
 
-        # Step 4: Slice 
-        sliceResults = sliceImage( imgArr, ( size, size ) )
-
-        # Step 5: Save slices
-        for res in sliceResults["slicedImages"]:
-            i = res[0]
-            j = res[1]
-            slicedImg = res[2]
-            finalFileName = "{}-{}-{}".format( newImgName, i, j )
-            sliceSizePath = imgSlicedSizePath.joinpath( "{}.{}".format( finalFileName, fileExt ) ) 
-            print( "SAVING IMAGE:", sliceSizePath )
-            cv2.imwrite( str( sliceSizePath ), slicedImg )
-
-            # Step 6: Mean Shift
-            ( segmentedImage, labelsImage, numberRegions ) = meanShiftSegmentation( slicedImg )
-
-            # Step 7: Save MS results
-            segColorPath = imgMSSizePath.joinpath( "{}-color-seg.{}".format( finalFileName, fileExt ) )
-            labelImgPath = imgMSSizePath.joinpath( "{}-labels-image.{}".format( finalFileName, fileExt ) )
-
-            print( "SAVING IMAGE:", segColorPath )
-            print( "SAVING IMAGE:", labelImgPath )
-
-            # scale labelsImage to [0,255]
-            labelsImage = labelsImage.astype( float )
-            labelsImage /= labelsImage.max()
-            labelsImage *= 255
-
-            # save results to image files
-            cv2.imwrite( str( segColorPath ), segmentedImage )
-            cv2.imwrite( str( labelImgPath ), labelsImage )
+        if imgArr.shape[0] >= size and imgArr.shape[1] >= size:
+
+            # Step 4: Slice 
+            sliceResults = sliceImage( imgArr, ( size, size ) )
+
+            # Step 5: Save slices
+            for res in sliceResults["slicedImages"]:
+                i = res[0]
+                j = res[1]
+                slicedImg = res[2]
+                finalFileName = "{}-{}-{}".format( newImgName, i, j )
+                sliceSizePath = imgSlicedSizePath.joinpath( "{}.{}".format( finalFileName, fileExt ) ) 
+                print( "SAVING IMAGE:", sliceSizePath )
+                cv2.imwrite( str( sliceSizePath ), slicedImg )
+
+                # Step 6: Mean Shift
+                ( segmentedImage, labelsImage, numberRegions ) = meanShiftSegmentation( slicedImg )
+
+                # Step 7: Save MS results
+                segColorPath = imgMSSizePath.joinpath( "{}-color-seg.{}".format( finalFileName, fileExt ) )
+                labelImgPath = imgMSSizePath.joinpath( "{}-labels-image.{}".format( finalFileName, fileExt ) )
+
+                print( "SAVING IMAGE:", segColorPath )
+                print( "SAVING IMAGE:", labelImgPath )
+
+                # scale labelsImage to [0,255]
+                labelsImage = labelsImage.astype( float )
+                labelsImage /= labelsImage.max()
+                labelsImage *= 255
+
+                # save results to image files
+                cv2.imwrite( str( segColorPath ), segmentedImage )
+                cv2.imwrite( str( labelImgPath ), labelsImage )