Skip to content

Update ML output SDS to publish all class confidence scores #18

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
MiloradCvjetkovic merged 1 commit into from
Jul 10, 2026
Merged

Update ML output SDS to publish all class confidence scores #18

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 2 additions & 1 deletion RockPaperScissors/AppKit-E8_USB/algorithm/algorithm_config.h
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@
#define ALGORITHM_CONFIG_H_

#include "config_ml_model.h" // ML model configuration
#include "model_config.h"

// Input Data block size, in bytes
#ifndef ALGO_DATA_IN_BLOCK_SIZE
Expand All @@ -28,7 +29,7 @@

// Output Data block size, in bytes
#ifndef ALGO_DATA_OUT_BLOCK_SIZE
#define ALGO_DATA_OUT_BLOCK_SIZE (50U)
#define ALGO_DATA_OUT_BLOCK_SIZE (MODEL_NUM_CLASSES * sizeof(float))
#endif

#endif
33 changes: 30 additions & 3 deletions RockPaperScissors/AppKit-E8_USB/algorithm/arm_executor_runner.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -178,6 +178,8 @@ bool classify_object = false;

output_label_t output_label;

float class_probs[MODEL_NUM_CLASSES] = {0.0};

constexpr int H = IMAGE_HEIGHT;

constexpr int W = IMAGE_WIDTH;
Expand Down Expand Up @@ -490,6 +492,31 @@ static void FormatShortLabel(const char* label, char* short_label,
short_label[copy_len] = '\0';
}

/**
* \brief Apply softmax function to convert logits to probabilities
* \param[in] logits Pointer to logit values array
* \param[out] probs Pointer to output probability array
* \param[in] n Number of elements
*/
void softmax(const float* logits, float* probs, int n) {
float max_val = logits[0];
for (int i = 1; i < n; i++) {
if (logits[i] > max_val) {
max_val = logits[i];
}
}

float sum = 0.0f;
for (int i = 0; i < n; i++) {
probs[i] = expf(logits[i] - max_val);
sum += probs[i];
}

for (int i = 0; i < n; i++) {
probs[i] /= sum;
}
}

/**
* \brief Prepare image input tensor for SqueezeNet model
* \param[in] image Pointer to input image data (HWC RGB format)
Expand Down Expand Up @@ -846,9 +873,9 @@ void print_outputs(RunnerContext& ctx)
printf("Number of classes: %d, expected: %d\n", numel, MODEL_NUM_CLASSES);
}

static float probs[MODEL_NUM_CLASSES];
float confidence = 0.0f;
uint16_t predicted_idx = -1;
softmax(logits, class_probs, numel);
status_t postprocess_result = postprocess((float*)logits, &result);

if(postprocess_result != STATUS_OK){
Expand Down Expand Up @@ -926,8 +953,8 @@ void postprocess(RunnerContext& ctx, uint8_t* img_buf,
print_outputs(ctx);

/* Copy shortened label plus confidence into caller's output buffer */
if (out_num >= sizeof(output_label_t)) {
memcpy(out_buf, &output_label, sizeof(output_label_t));
if (out_num >= sizeof(class_probs)) {
memcpy(out_buf, class_probs, sizeof(class_probs));
}

/* Only draw if label is valid */
Expand Down