Utility sample_images does not sample from image snapshots only
**Describe the bug**
The `sample_images` method in `plantcv-utils.py` when working with "Phenofront" data (datasets with a `SnapshotInfo.csv` file) does not differentiate between snapshots (rows in the spreadsheet) that have images and those that do not (e.g. watering events). Because there can be many more watering events than imaging events, any given random sample can be light on actual image data. We can update the function slightly to randomly subset from only image data.


diff --git a/plantcv/utils/sample_images.py b/plantcv/utils/sample_images.py
index 1de23a1f..783fc226 100644
--- a/plantcv/utils/sample_images.py
+++ b/plantcv/utils/sample_images.py
@@ -23,8 +23,10 @@ def sample_images(source_path, dest_path, num=100):
         input_csv = open(os.path.join(source_path, 'SnapshotInfo.csv'))
         header = input_csv.readline()
         for line in input_csv:
+            line = line.rstrip("\\n")
             element_arr = line.split(',')
-            line_array.append(element_arr)
+            if element_arr[-1]:
+                line_array.append(element_arr)
         input_csv.close()
 
         # Check to make sure number of imgs to select is less than number of images found
['plantcv/utils/sample_images.py']