Evaluating a Sequence of Images

This is a modification of the classification example to highlight how to evaluate a sequence of images.

Python

import denkflow

pat = "YOUR-PAT"

denkflow_path = "path/to/model/file.denkflow"
image_paths = ["path/to/image_1.JPG", "path/to/image_2.JPG", "path/to/image_3.JPG"]

input_topic = "camera/image"
output_topic = "classification_node/output"

pipeline = denkflow.Pipeline.from_denkflow(
    denkflow_path,
    pat=pat,
)

pipeline.initialize()

results_receiver = pipeline.subscribe(output_topic)

for path in image_paths:
    image_tensor = denkflow.ImageTensor.from_file(path)

    pipeline.publish_image_tensor(input_topic, image_tensor)

    pipeline.run()

    tensor = results_receiver.receive_scalar_tensor()

    results_per_batch = tensor.to_objects()

    print(f"Classification Results for {path}:")
    for results_per_class_label in results_per_batch:
        for result_for_class_label in results_per_class_label:
            print(f"{result_for_class_label.class_label}: {result_for_class_label.value:.2f}")

C

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include "denkflow.h"

void handle_error(enum DenkflowResult error_code, const char* function_name) {
	printf("%s: %d", function_name, (int32_t)error_code);
	if (error_code != DenkflowResult_Ok) {
		char error_buffer[ERROR_BUFFER_SIZE];
		memset(error_buffer, 0, ERROR_BUFFER_SIZE);
		get_last_error(error_buffer);
		printf(" (%s)\n", error_buffer);
		exit(EXIT_FAILURE);
	}
	printf("\n");
}

int main() {
	Pipeline*            pipeline             = NULL;
	InitializedPipeline* initialized_pipeline = NULL;
	ImageTensor*         image_tensor         = NULL;
	Receiver_Tensor*     receiver             = NULL;
	ScalarTensor*        tensor               = NULL;
	ScalarResults*       results              = NULL;
	HubLicenseSource*    hub_license_source   = NULL;

	enum DenkflowResult r;

	const uint64_t timeout_ms = 8000;

	const char* pat           = "YOUR-PAT";

	const char* denkflow_path = "path/to/model/file.denkflow";
	const char* image_path    = "path/to/an/image.jpg";

	const char* input_topic   = "camera/image";
	const char* output_topic  = "classification_node/output";

	r = hub_license_source_from_pat(&hub_license_source, pat, NULL_BYTE, NULL_BYTE);

	handle_error(r, "hub_license_source_from_pat");

	r = pipeline_from_denkflow(&pipeline, denkflow_path, (void*)hub_license_source);
	handle_error(r, "pipeline_from_denkflow");

	r = initialize_pipeline(&initialized_pipeline, &pipeline);
	handle_error(r, "initialize_pipeline");

	r = initialized_pipeline_subscribe(&receiver, initialized_pipeline, output_topic);
	handle_error(r, "initialized_pipeline_subscribe");

	// This example just evaluates the same image three times.
	for (int i = 0; i < 3; i++) {
		r = image_tensor_from_file(&image_tensor, image_path);
		handle_error(r, "image_tensor_from_file");

		r = initialized_pipeline_publish_image_tensor(initialized_pipeline, input_topic, &image_tensor);
		handle_error(r, "initialized_pipeline_publish_image_tensor");

		r = initialized_pipeline_run(initialized_pipeline, timeout_ms);
		handle_error(r, "initialized_pipeline_run");

		r = receiver_receive_scalar_tensor(&tensor, receiver);
		handle_error(r, "receiver_receive_scalar_tensor");

		r = scalar_tensor_to_objects(&results, tensor);
		handle_error(r, "scalar_tensor_to_objects");

		if (r == DenkflowResult_Ok) {
			for (int b = 0; b < results->scalar_batch_elements_length; b++) {
				printf("Image %d\n", b);
				for (int c = 0; c < results->scalar_batch_elements[b].scalars_length; c++) {
					printf("  %s: %f\n",
						results->scalar_batch_elements[b].scalars[c].class_label.name,
						results->scalar_batch_elements[b].scalars[c].value
					);
				}
			}
		}

		// These are the objects that need to be freed per run.
		r = free_object((void**)&tensor);
		handle_error(r, "free_object");
		r = free_object((void**)&results);
		handle_error(r, "free_object");
	}

	r = free_object((void**)&hub_license_source);
	handle_error(r, "free_object");
	r = free_object((void**)&initialized_pipeline);
	handle_error(r, "free_object");
	r = free_object((void**)&receiver);
	handle_error(r, "free_object");

	return 0;
}