Crate yscv_eval 

Evaluation and benchmarking utilities for yscv.

Structs

BenchmarkViolation

CameraDiagnosticsCapture

CameraDiagnosticsDevice

CameraDiagnosticsFirstFrame

CameraDiagnosticsReport

CameraDiagnosticsRequested

CameraDiagnosticsThresholds

CameraDiagnosticsTiming

CameraDiagnosticsViolation

CocoMetrics

CountingMetrics

DetectionDatasetFrame

DetectionEvalConfig

DetectionFrame

DetectionMetrics

GroundTruthTrack

LabeledBox

PipelineBenchmarkReport

PipelineBenchmarkThresholds

PipelineDurations

StageThresholds

TimingStats

TrackingDatasetFrame

TrackingEvalConfig

TrackingFrame

TrackingMetrics

Enums

EvalError

F1Average

Averaging strategy for multi-class F1 score.

Constants

CRATE_ID

Functions

accuracy

Compute classification accuracy as the fraction of correct predictions.

auc

Area under the curve using the trapezoidal rule.

average_precision

Compute average precision (area under the precision-recall curve) using the trapezoidal rule.

classification_report

Generate a human-readable classification report (similar to scikit-learn’s classification_report).

cohens_kappa

Cohen’s kappa coefficient measuring inter-annotator agreement.

confusion_matrix

Compute a confusion matrix for num_classes classes.

detection_frames_as_view

dice_score

Per-class Dice coefficient: 2 * |pred ∩ target| / (|pred| + |target|).

evaluate_counts

evaluate_detections

evaluate_detections_coco

Evaluate detections using COCO-style multi-threshold metrics.

evaluate_detections_from_dataset

evaluate_tracking

evaluate_tracking_from_dataset

f1_score

Compute F1 score with the specified averaging strategy.

hota

Higher Order Tracking Accuracy.

idf1

Identity F1 score: measures how well predicted IDs match GT IDs across frames.

load_camera_diagnostics_report_json_file

load_detection_dataset_coco_files

load_detection_dataset_jsonl_file

load_detection_dataset_kitti_label_dirs

load_detection_dataset_openimages_csv_files

load_detection_dataset_voc_xml_dirs

load_detection_dataset_widerface_files

load_detection_dataset_yolo_label_dirs

load_tracking_dataset_jsonl_file

load_tracking_dataset_mot_txt_files

mae

Mean absolute error.

mape

Mean absolute percentage error, skipping pairs where the target is zero.

mean_iou

Mean Intersection over Union for semantic segmentation.

parse_camera_diagnostics_report_json

parse_detection_dataset_coco

parse_detection_dataset_jsonl

parse_detection_dataset_openimages_csv

parse_detection_dataset_widerface

parse_pipeline_benchmark_thresholds

parse_tracking_dataset_jsonl

parse_tracking_dataset_mot

per_class_iou

Per-class Intersection over Union: |pred ∩ target| / |pred ∪ target|.

per_class_precision_recall

Compute per-class precision and recall from a confusion matrix.

precision_recall_curve

Compute precision-recall curve from binary classification scores and labels.

psnr

Peak Signal-to-Noise Ratio between two images.

r2_score

Coefficient of determination: 1 - SS_res / SS_tot.

rmse

Root mean squared error.

roc_curve

Compute ROC curve from binary classification scores and labels.

ssim

Structural Similarity Index (SSIM) between two grayscale images.

summarize_durations

summarize_pipeline_durations

top_k_accuracy

Top-k accuracy: fraction of samples where the correct label is in the top-k predictions.

tracking_frames_as_view

validate_camera_diagnostics_report

validate_pipeline_benchmark_thresholds