View/Test Models

Test the performance of your trained model with Inference Jobs

Create Inference Job

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.

Real-time inference

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:

Type
Image classification
Object detection
Object Segmentation

prediction results

label name & confidence score

label name & bounding boxes in dotted lines

label name & objects with white stripes

Explainability

heat map of each label (can be toggled on of by )

NA

NA

Ground truth (if available)

ground truth labels

Bounding boxes in bold lines

Objects painted in solid colors

Image Classification: prediction & ground truth
Image classification: heat map on

Batch inference

  • 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.

View Inference Detail

Annotation Data (with ground truth/label)

  • 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.

Inference Detail for different types:

Type
Image Classification
Object Detection
Object Segmentation

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

Inference Detail: Image Classification

Prediction only

  • 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.

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