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+++ b/.gitignore
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 # virtual machine crash logs, see http://www.java.com/en/download/help/error_hotspot.xml
 hs_err_pid*
+.DS_Store
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diff --git a/models/UFO_object_types/README.md b/models/UFO_object_types/README.md
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+
+
+# Instructions 
+
+In order to test this model you can download a template python script that allows you to specify models and inputs.
+
+First clone the google code labs scripts and cd into the folder
+
+```shell
+git clone https://github.com/googlecodelabs/tensorflow-for-poets-2
+cd tensorflow-for-poets-2
+```
+
+Next, while your inside the tensorflow-for-poets folder you need to run the a label image script as follows
+
+```
+python -m scripts.label_image \
+    --graph={LOCAITON OF THE MODEL }  \
+    --image={LOCATION OF IMAGE TO BE CLASSIFIED} \
+    --label={LOCATION OF LABELS FOR CLASSIFICATION}
+```
+
+Here is a sample input and what kind of output to expect. 
+
+```Shell
+ python -m scripts.label_image  
+ --graph=tf_files/object_types__retrained_graph.pb     
+ --image=tf_files/training_data/flying_objects/90926_submitter_file3__Nic.UFOzoom2.jpg  
+ --labels=tf_files/object_types__retrained_labels.txt 
+ 
+ 
+Evaluation time (1-image): 0.173s
+
+flying objects 0.996902
+spheres 0.0030978536
+lights 1.9191765e-07
+glowing orbs 7.516825e-11
+```
+
+If you want to automate this process for a large batch of inputs please use the temple in the above repository or use the  above shell commands with output redirection. 
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diff --git a/models/UFO_object_types/object_types__retrained_graph.pb b/models/UFO_object_types/object_types__retrained_graph.pb
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diff --git a/models/UFO_object_types/object_types__retrained_labels.txt b/models/UFO_object_types/object_types__retrained_labels.txt
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+flying objects
+glowing orbs
+lights
+spheres