created separate prog to run meanshift from terminal, added to readme the results of meanshift

README.md

@@ -5,30 +5,52 @@ Slices an image into even sized tiles.
 Note: if the slice size doesn't fit evenly into the size of 
       the original image, pixels will be lost.
 
-## Command line arguments
- - arg1: name of image file used for slicing
- - arg2: file name used as base for all slices
- - arg3: width of new slices
- - arg4: height of new slices
- - arg5: directory to save slices 
-
-## Example run
+## Command line arguments:
+- arg1: name of image file used for slicing
+- arg2: file name used as base for all slices
+- arg3: width of new slices
+- arg4: height of new slices
+- arg5: directory to save slices 
+
+## Example run:
 ```bash
-python sliceImage.py ./sliceImage_ex/GeoEye_After011310.jpg GeoEye_Slice 512 512 ./sliceImage_ex/
+python sliceImage.py ./sliceImageResults/GeoEye_Original.jpg GeoEye_Slice 512 512 ./sliceImageResults/
 ```
 
-## Example run result
+## Example run result:
 ## Original Image: 1180x1180
-![](sliceImage_ex/GeoEye_After011310.jpg)
+![](sliceImageResults/GeoEye_Original.jpg)
 
 ## Slice 1: 512x512
-![](sliceImage_ex/GeoEye_Slice-0-0.jpg)
+![](sliceImageResults/GeoEye_Slice-0-0.jpg)
 
 ## Slice 2: 512x512
-![](sliceImage_ex/GeoEye_Slice-0-512.jpg)
+![](sliceImageResults/GeoEye_Slice-0-512.jpg)
 
 ## Slice 3: 512x512
-![](sliceImage_ex/GeoEye_Slice-512-0.jpg)
+![](sliceImageResults/GeoEye_Slice-512-0.jpg)
 
 ## Slice 4: 512x512
-![](sliceImage_ex/GeoEye_Slice-512-512.jpg)
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+![](sliceImageResults/GeoEye_Slice-512-512.jpg)
+
+## "meanShift.py" program:
+Uses the mean shift algorithm to create a segmentation mask for an image.
+
+## Command line arguments:
+ - arg1: image file used for segmentation
+ - arg2: file name to save segmentation
+
+ ## Example run:
+ ```bash
+python meanShift.py meanShiftResults/GeoEye_MS_Original.jpg meanShiftResults/GeoEye_MS_Segmented
+```
+
+ ## Example run result:
+ ## Original Image:
+ ![](meanShiftResults/GeoEye_MS_Original.jpg)
+
+ ## Segmentation Image:
+ ![](meanShiftResults/GeoEye_MS_Segmented.jpg)
+
+ ## Program run time:
+ This program takes roughly 20 seconds to run, tested on an AMD FX(tm)-4300 Quad-Core Processor
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ai4hdr_utils.py

@@ -65,7 +65,7 @@ def sliceImage( imagePath: str, newFileBase: str, newSize: tuple, newPath: str )
     }
 
 
-def meanshiftSegmentation( imagePath: str, outPath: str, classColors: list=None, quantile=0.2, samples=500 ) -> dict:
+def meanshiftSegmentation( imagePath: str, outPath: str, quantile=0.2, samples=500, classColors: list=None ) -> dict:
     '''
     SOURCE: https://www.efavdb.com/mean-shift
 
@@ -75,10 +75,10 @@ def meanshiftSegmentation( imagePath: str, outPath: str, classColors: list=None,
     Parameters:
         - imagePath   : path to image used
         - outPath     : path to save segmented image ( image type extension automatically added )
-        - classColors : custom list of colors to use for classes, default: [ "darkgreen", "indigo", "gold" ]
-                        Note: list index = class label
         - quantile    : used for estimate_bandwidth function, should be between [0, 1], default: 0.2
         - samples     : used for estimate_bandwidth function, number of samples to use, defualt: 500
+        - classColors : custom list of colors to use for classes, default: [ "darkgreen", "indigo", "gold" ]
+                        Note: list index = class label
 
     Returns: a dictionary mapping the class integer to a tuple containing a color name and rgb value
     {
@@ -140,11 +140,4 @@ def meanshiftSegmentation( imagePath: str, outPath: str, classColors: list=None,
         1: ( classColors[1], color2 ),
         2: ( classColors[2], color3 )
     }
-    
-
-if __name__ == "__main__":
-    cwd       =  pathlib.Path.cwd()
-    imagePath = cwd.joinpath( "meanShiftSeg_ex/GeoEye_MS_Original.jpg" )
-    outPath   = cwd.joinpath( "meanShiftSeg_ex/GeoEye_MS_Segmented" )
-
-    result = meanshiftSegmentation( str( imagePath ), str( outPath ) )
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+    
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meanShift.py

+import sys
+from ai4hdr_utils import meanshiftSegmentation
+
+if __name__ == "__main__":
+    '''
+    Required arguments:
+    - arg1: image file used for segmentation
+    - arg2: file name to save segmentation
+    '''
+    
+    if len( sys.argv ) == 3:
+        imagePath = sys.argv[1]
+        outPath   = sys.argv[2]
+        '''
+        TO DO: Need customization of following parameters?
+        For now, using same defaults as the function
+        '''
+        quantile    = 0.2
+        samples     = 500
+        classColors = [ "darkgreen", "indigo", "gold" ]
+
+        result = meanshiftSegmentation( imagePath=imagePath,
+                                        outPath=outPath,
+                                        quantile=quantile,
+                                        samples=samples,
+                                        classColors=classColors )
+
+    else:
+        print( "Invalid arg count" )
+
+    
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