44

im_dim = original_img_dim[0], original_img_dim[1]
im_dim = torch.FloatTensor(im_dim).repeat(1,2)

#If there's a GPU availible, put the model on GPU
if CUDA:
    im_dim = im_dim_list.cuda()
    model.cuda()

#Set the model in evaluation mode
model.eval()
with torch.no_grad():
      prediction = model(processed_image)


output = final_detection(prediction, confidence_threshold=0.5, num_classes=80, nms_conf = nms_thesh)