--- a/yolo.xml	Wed Oct 18 13:31:46 2017 -0400
+++ b/yolo.xml	Thu Oct 19 10:01:49 2017 -0400
@@ -8,32 +8,62 @@
 mkdir input_dir &&
 mkdir output_png_dir &&
 cp -R /home/greg/_conda/envs/__darknet@1.0/bin/* .
-#for $i in $input:
-    #set input_filename = $i.file_name
-    #set full_name = $i.name
+#set input $input_type_cond.input
+#if str($input_type_cond.input_type) == 'image':
+    #set input_filename = $input.file_name
+    #set full_name = $input.name
     #set head = $full_name.split('.')[0]
     #set output_filename_png = '%s_predictions.png' % $head
     #set output_filename_shape_confidence = '%s_shape_detection_confidence.tabular' % $head
     && ln -s $input_filename input_dir/$full_name
     && darknet detect cfg/yolo.cfg yolo.weights 'input_dir/$full_name' -thresh $thresh > output_shape_confidence_dir/$output_filename_shape_confidence
     && mv ./predictions.png output_png_dir/$output_filename_png
-#end for
+#else:
+    #for $i in $input:
+        #set input_filename = $i.file_name
+        #set full_name = $i.name
+        #set head = $full_name.split('.')[0]
+        #set output_filename_png = '%s_predictions.png' % $head
+        #set output_filename_shape_confidence = '%s_shape_detection_confidence.tabular' % $head
+        && ln -s $input_filename input_dir/$full_name
+        && darknet detect cfg/yolo.cfg yolo.weights 'input_dir/$full_name' -thresh $thresh > output_shape_confidence_dir/$output_filename_shape_confidence
+        && mv ./predictions.png output_png_dir/$output_filename_png
+    #end for
+#end if
     ]]></command>
     <inputs>
-        <param name="input" format="jpg" type="data_collection" collection_type="list" label="Collection of image files" />
-        <param name="thresh" type="float" value="0.25" label="Object detection threshold" />
+        <conditional name="input_type_cond">
+            <param name="input_type" type="select" label="Select">
+                <option value="image" selected="true">a single image</option>
+                <option value="images">a collection of images</option>
+            </param>
+            <when value="image">
+                <param name="input" format="jpg" type="data" label="Image"/>
+            </when>
+            <when value="images">
+                <param name="input" format="jpg" type="data_collection" collection_type="list" label="Collection of image files"/>
+            </when>
+        </conditional>
+        <param name="thresh" type="float" value="0.25" label="Object detection threshold"/>
         <param name="output_shape_confidence" type="select" display="radio" label="Output shape detection confidence levels?">
             <option value="yes" selected="true">Yes</option>
             <option value="no">No</option>
         </param>
     </inputs>
     <outputs>
-        <collection name="output_shape_confidence" type="list" label="${tool.name} (shape detection confidence) on ${on_string}">
+        <data name="output_shape_confidence" format="tabular" label="${tool.name} (shape detection confidence) on ${on_string}">
+            <filter>input_type_cond['input_type'] == 'image' and output_shape_confidence == 'yes'</filter>
+        </data>
+        <data name="output_shape" format="png" label="${tool.name} (shapes) on ${on_string}">
+            <filter>input_type_cond['input_type'] == 'image'</filter>
+        </data>
+        <collection name="output_shape_confidences" type="list" label="${tool.name} (shape detection confidence) on ${on_string}">
             <discover_datasets pattern="__name__" directory="output_shape_confidence_dir" format="tabular" />
-            <filter>output_shape_confidence == 'yes'</filter>
+            <filter>input_type_cond['input_type'] == 'images' and output_shape_confidence == 'yes'</filter>
         </collection>
-        <collection name="output_shape" type="list" label="${tool.name} (shapes) on ${on_string}">
+        <collection name="output_shapes" type="list" label="${tool.name} (shapes) on ${on_string}">
             <discover_datasets pattern="__name__" directory="output_png_dir" format="png" />
+            <filter>input_type_cond['input_type'] == 'images'</filter>
         </collection>
     </outputs>
     <tests>