View/Test Models
Test the performance of your trained model with Inference Jobs
Last updated
Test the performance of your trained model with Inference Jobs
Last updated
In the model detail view, you can create "Inference Jobs" to test the model
You have to deploy the model before creating any inference task.
There are two modes of model inference: batch & real-time.
Select and open one JPG/ PNG image from your local device, the inference result will be shown automatically with the AI image viewer.
The AI viewer contains the following information of each image:
prediction results
label name & confidence score
label name & bounding boxes in dotted lines
label name & objects with white stripes
Explainability
NA
NA
Ground truth (if available)
ground truth labels
Bounding boxes in bold lines
Objects painted in solid colors
Batch inference: Select one of the dataset that you have uploaded from the drop list, enter the inference name and complete the creation process.
Prediction only: For datasets without annotation data, inference result will only provide prediction results without an inference report.
The inference detail, including training task, dataset, and annotation data will be shown here.
Inference List: You can view the inference detail about the dataset, accuracy, and status.
Inference Dataset shows all the cases that have been trained in this task.
Performance metrics
>Accuracy >ROC/PR Curve >Confusion Matrix >Evaluation Summary
>mAP >FROC/PR Curve >Evaluation Summary
>DICE scores >Evaluation Summary
Dataset Statistics
>Label Distribution
>Box Label >Box-per-Image >Box Ratio >Box Area >Label Distribution (Image-wise)
>Label Distribution >Mask-Coverage Distribution
if the batch inference dataset does not contain ground truth (annotation file not selected), there will be no performance metrics & Dataset statistics
Each image of the selected dataset will be shown in the last column, you can check the result by clicking on the image.
heat map of each label (can be toggled on of by )
