multi-class detection task evaluation

2022_11_25_detection_eval.py

results = dataset.evaluate_detections(
    "predictions",
    gt_field="ground_truth",
    eval_key="eval",
    compute_mAP=True,
)

# Get the 10 most common classes in the dataset
counts = dataset.count_values("ground_truth.detections.label")
classes_top10 = sorted(counts, key=counts.get, reverse=True)[:10]

# Print a classification report for the top-10 classes
results.print_report(classes=classes_top10)