We have data with annotated bounding boxes (‘sick’) and data that has no bounding boxes at all (‘healthy’).
Our objective is to train the algorithm with both as the ‘healthy’ data would allow for a more robust model.
We have followed the convention provided in mxnet’s documentation, an example of healthy and sick in our list currently looks like this:
2 2 0 whole/healthy/R40IMG30.jpeg
3 2 5 0 0.0004060000000000036 0.097402 0.22037400000000001 0.22849000000000003 whole/sick/R117IMG245.jpeg
Whereby the first line represents a healthy example with no bounding boxes and the second an example with a bounding box around the sick area.
In the first line the length of label is 0 (we tried 5 as well), while in the second line the label length is 5.
We’re getting this error when starting the training instance: “Not enough annotation packed in the list file or the RecordIO file. Each object requires at least five numbers [label_id, xmin, ymin, ymax] for annotation.”
We understand what the error means, and are wondering how we’d go about inserting data with no annotations via RecordIO format.