[BUG]: cannot unpack non-iterable VisImage object

[KatherineJames]

Description of the bug

Running with use_ros=False

Images with no detected berries (eg. sample_184.png) results in this error.

Steps To Reproduce

non_ros_params:

datasets:
  train_dataset_name: 'aoc_train_dataset'
  test_dataset_name: 'aoc_test_dataset'
  validation_dataset_name: 'aoc_validation_dataset'
  dataset_train_annotation_url: 'https://lncn.ac/aocanntrain' 
  dataset_train_images_url: 'https://lncn.ac/aocdatatrain'
  dataset_test_annotation_url: 'https://lncn.ac/aocanntest' 
  dataset_test_images_url: 'https://lncn.ac/aocdatatest'
files:
  # pretrained model used as a training base model, if set as empty, the config file will use imagenet trained model as base.
  pretrained_model_file: ''
  # model_file: './model/aoc_tomato_ripeness_151_40k.pth'
  model_file: './model/aoc_strawberry_class_fruit.pth' #'./model/aoc_model.pth'
  config_file: 'COCO-InstanceSegmentation/mask_rcnn_R_101_FPN_3x.yaml'
  test_metadata_catalog_file: './data/dataset_catalogs/test_metadata_catalog.pkl'
  train_dataset_catalog_file: './data/dataset_catalogs/tom_train_dataset_catalog.pkl'
  train_annotation_file: './data/strawberry_dataset/train/annotations/ripeness_class_annotations.json'
  test_annotation_file: './data/strawberry_dataset/test/annotations/test_annotations.json'
  validation_annotation_file: './data/strawberry_dataset/val/annotations/ripeness_class_annotations.json'
  model_url: 'https://lncn.ac/aocmodel'
  meta_catalog_url: 'https://lncn.ac/aocmeta'
  train_catalog_url: 'https://lncn.ac/aoccat'
directories:
  train_image_dir: './data/strawberry_dataset/train/'
  test_image_dir: './data/strawberry_dataset/test/' #'./data/strawberry_dataset/test/'
  validation_image_dir: './data/strawberry_dataset/val/'
  training_output_dir: './data/training_output/'
  prediction_output_dir: './data/prediction_output/test_images/'
  prediction_json_dir: './data/annotations/predicted/' 
training:
  epochs: 40000
  number_of_classes: 1
  optimizer: 'SGD'
  learning_rate: 0.0025
settings:
  download_assets: false # if assets such as model and datasets should be downloaded
  rename_pred_images: false #rename the predicted images in img_000001.png like format
  segm_masks: true
  bbox: true
  show_orientation: false
  fruit_type: 'strawberry' # currently supported for "strawberry" or "tomato"
  validation_period: 500 # Smaller validation will increase training time. The value is set to have 100 validation during training

Additional Information

No response

[KatherineJames]

@usmanzahidi - would you mind taking a look at this to see if there is a quick fix?