Describe your question/issue here! (delete this when you post)
- Project Type: Object Detection → Multiple Bounding Boxes → Single Label Class Model → Detections Classes Replacement
- Operating System & Browser: WSL, Local Inference, or Serverless Hosted API V2
- Project Universe Link or Workspace/Project ID: Custom Workflow, but can be tested easily
I am trying to do a simple workflow (or at least I thought it would be simple.).
Since I can apparently only upload ONE image, here’s the text of the error from the Detections Classes Replacement block :
Data fed into step `detections_classes_replacement` property `classification_predictions` has actual dimensionality 1, when expected was 2
Blocks with errors:
1.
detections_classes_replacement
Error in property: classification_predictions. Expected dimensionality 2, but received dimensionality 1.
Is there an example or better way of doing this? The goal would be to have an output of the original input image, with all the bounding boxes detected in the Obj Detection Model, but with the class names inserted into those bounding boxes from the single label classification model.
Would greatly appreciate help. Have spent hours on this, going in circles with the AI Agent and reading documentation. I am not sure how to format the data in the expected format with the workflow editor. I am confident that doing it manually via Python wouldn’t be difficult, but for this exercise, I need to map this out for my customers to be able to do it in this workflow editor.
–Andrew