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updated readme
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README.md
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README.md
@ -163,14 +163,14 @@ Underneath the output interfaces, there is a button marked "Flag". When a user t
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For example, with the calculator interface shown above, we would have the flagged data stored in the flagged directory shown below:
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```
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```directory
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+-- calculator.py
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+-- flagged/
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| +-- logs.csv
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```
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*flagged/logs.csv*
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```
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```csv
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num1,operation,num2,Output
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5,add,7,12
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6,subtract,1.5,4.5
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@ -178,7 +178,7 @@ num1,operation,num2,Output
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With the sepia interface shown above, we would have the flagged data stored in the flagged directory shown below:
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```
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```directory
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+-- sepia.py
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+-- flagged/
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| +-- logs.csv
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@ -190,8 +190,8 @@ With the sepia interface shown above, we would have the flagged data stored in t
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| | +-- 1.png
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```
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*flagged/logs.csv*:
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```
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*flagged/logs.csv*
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```csv
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im,Output
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im/0.png,Output/0.png
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im/1.png,Output/1.png
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@ -88,17 +88,22 @@ Underneath the output interfaces, there is a button marked "Flag". When a user t
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For example, with the calculator interface shown above, we would have the flagged data stored in the flagged directory shown below:
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```directory
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+-- calculator.py
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+-- flagged/
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| +-- logs.csv
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```
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*flagged/logs.csv*
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```csv
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num1,operation,num2,Output
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5,add,7,12
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6,subtract,1.5,4.5
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```
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With the sepia interface shown above, we would have the flagged data stored in the flagged directory shown below:
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```directory
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+-- sepia.py
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+-- flagged/
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| +-- logs.csv
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@ -108,11 +113,14 @@ With the sepia interface shown above, we would have the flagged data stored in t
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| +-- Output/
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| | +-- 0.png
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| | +-- 1.png
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```
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*flagged/logs.csv*
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```csv
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im,Output
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im/0.png,Output/0.png
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im/1.png,Output/1.png
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```
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You can review these flagged inputs by manually exploring the flagging directory, or load them into the examples of the Gradio interface by pointing the `examples=` argument to the flagged directory. If you wish for the user to provide a reason for flagging, you can pass a list of strings to the `flagging_options` argument of Interface. Users will have to select one of the strings when flagging, which will be saved as an additional column to the CSV.
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