Prediction objects, you just need to upload them to your Nucleus dataset by associating them with a model. This can be accomplished with a single call to
Dataset.upload_predictions. See example usage below.
We recommend setting
asynchronous=True to drastically speed up the upload. This will also allow you to check on the job's status in the dashboard or via the API (see our docs on Async Jobs).
import nucleus # construct various predictions box_pred_1 = nucleus.BoxPrediction(...) box_pred_2 = nucleus.BoxPrediction(...) polygon_pred = nucleus.PolygonPrediction(...) line_pred = nucleus.LinePrediction(...) cuboid_pred = nucleus.CuboidPrediction(...) segmentation_pred = nucleus.SegmentationPrediction(...) # fetch dataset and model client = nucleus.NucleusClient("YOUR_SCALE_API_KEY") dataset = client.get_dataset("YOUR_DATASET_ID") model = client.get_model("YOUR_MODEL_ID") # upload predictions to dataset job = dataset.upload_predictions( model=model, predictions=[box_pred_1, box_pred_2, polygon_pred, line_pred, cuboid_pred, segmentation_pred], update=True, asynchronous=True )
Updated about 1 year ago