Unable to Loop the Inference of a Model That Has 2 Outputs

Unable to handle a model that has 2 outputs when using the function code below:

 for i, detection in enumerate(detections):
        #_, image_id, confidence, xmin, ymin, xmax, ymax = detection
        xmin, ymin, xmax, ymax, confidence = detection
        if confidence > 0.2:
            xmin = int(max((xmin * image.shape[1]), 10))
            ymin = int(max((ymin * image.shape[0]), 10))
            xmax = int(min((xmax * image.shape[1]), image.shape[1] - 10))
            ymax = int(min((ymax * image.shape[0]), image.shape[0] - 10))

To enable the looping of 2 model outputs, take both outputs into account because output2 may contain a background class.

Reuse the part of the code as below: 

# output1, output2 = model()

for i, (detection, label) in enumerate(zip(output1, output2)): 
         #_, image_id, confidence, xmin, ymin, xmax, ymax = detection
         xmin, ymin, xmax, ymax, confidence = detection
         if confidence > 0.2 and label == 1: 
             # reuse the code from the example