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from clevrml import

Image_Model

import os

key = os.environ[ "API-KEY" ]

model = Image_Model( )

model.predict(

   api_key=key,

   image_file_name=

   model_name=

)

<Pending Input>,

"null"

Our model correctly predicted the image. With only 3 examples of each class, our model can generalize well within the context of our demo.
If you want to continue with the rest of the test data, click the Continue Testing button, otherwise click the Next Button
Image Selected: 
loading.gif
No Image Selected
Now click the "Run" button above to get a prediction for the image you selected.

Output

Prediction: 

Details:

-------------------------------------

Model Name: 

Prediction: 

Status: Success

Cost: $0.025

------------------------------------

JSON: 

{

   Model_Name: 

   Prediction:

   Status: "Success",

   Cost: 0.025

}

"null"

mark

mark

"null"

mark

Now that we've built our model, let's test it by giving it images to make predictions. 
First, let's select an image. From the "Test Images" box below, select any of the images. 
When you are ready to move on, click the "Continue" button.

Test Images (Select One)

stop_test1.jpg
stop_sign1.jpg
Scenic Bike Ride
bicycle2.jpg
bikey.jpg
bicycle1.jpg
red_lights.jpg
traffic_light2.jpg
red.jpg
traffic_light1.jpg
bicycle.jpg
bicycle3.jpg
stop_test9.jpg
stop_sign2.jpg
red_light.jpg
traffic_light3.jpg