Classification

A classification pipeline returns a scalar result per class on each InferenceResult. See SimplifiedPipeline for the shared setup and Interpreting results for the result model.

Python

import denkflow

pipeline = denkflow.Pipeline.from_denkflow("path/to/model.denkflow", pat="YOUR-PAT")
simplified = denkflow.SimplifiedPipeline(pipeline)

results = simplified.run("path/to/image.jpg")

for image_result in results:
    for r in image_result.results:
        if r.scalar:
            print(f"{r.scalar.class_label.name}: {r.scalar.value:.2f}")

C#

using DenkFlow;

using var license = HubLicenseSource.FromPat("YOUR-PAT");
using var pipeline = Pipeline.FromDenkflow("path/to/model.denkflow", license);
using var simplified = new SimplifiedPipeline(pipeline);

using ImageInferenceResults results =
    simplified.Run("path/to/image.jpg");

foreach (ImageInferenceResult imageResult in results)
{
    foreach (InferenceResult result in imageResult.Results)
    {
        if (result.Scalar is Scalar scalar)
        {
            Console.WriteLine(
                $"{scalar.ClassLabel.Name}: {scalar.Value:F2}");
        }
    }
}

C / C++

DenkflowPipeline*              pipeline    = NULL;
DenkflowSimplifiedPipeline*    simplified  = NULL;
DenkflowImageInferenceResults* results     = NULL;
DenkflowHubLicenseSource*      license     = NULL;

handle_error(denkflow_hub_license_source_from_pat(&license, "YOUR-PAT", NULL, NULL),
	"denkflow_hub_license_source_from_pat");
handle_error(denkflow_pipeline_from_denkflow(&pipeline, "path/to/model.denkflow", (void*)license),
	"denkflow_pipeline_from_denkflow");
handle_error(denkflow_simplified_pipeline_new(&simplified, &pipeline),
	"denkflow_simplified_pipeline_new");
handle_error(denkflow_simplified_pipeline_run_from_file(&results, simplified, "path/to/image.jpg", 0.0f),
	"denkflow_simplified_pipeline_run_from_file");

for (size_t b = 0; b < results->image_results_length; ++b) {
	DenkflowImageInferenceResult* image_result = &results->image_results[b];
	for (size_t i = 0; i < image_result->results_length; ++i) {
		DenkflowInferenceResult* r = &image_result->results[i];
		if (r->scalar != NULL) {
			printf("%s: %f\n", r->scalar->class_label.name, r->scalar->value);
		}
	}
}

denkflow_inference_results_free(&results);
denkflow_simplified_pipeline_free(&simplified);
denkflow_free_object((void**)&license);

Draw classification scores

When annotation labels are enabled, classification scores are sorted from highest to lowest and drawn as separate class-colored chips in the top-left corner. top_classifications / TopClassifications controls how many scores are shown; 0 omits them. Keep the source image tensor so it can render the inference results, and set annotation_label_font_size / LabelFontSize to a positive value. See Drawing results for Python, C#, and C examples.