def test_mean_average_precision_and_recall_per_class():
ds_path = BASE_PATH / 'hair_drier_toaster_bear.json'
df = cocoeval.generate_predictions(ds_path, ds_path)
class_idx_metrics = cocoeval.mean_average_precision_and_recall_per_class(df)
class_idxs = df['true_class_id'].unique()
class_idxs = class_idxs[class_idxs > 0]
print(class_idx_metrics)
assert len(class_idx_metrics) == len(class_idxs)
def test_mean_average_precision_and_recall_per_class_with_name_min_score():
ds_path = BASE_PATH / 'hair_drier_toaster_bear.json'
ds = CocoDataset(ds_path)
idx_class_name = {
idx: cat_meta['name'] for idx, cat_meta in ds.cats.items()
}
df = cocoeval.generate_predictions(ds_path, ds_path)
class_idx_metrics = cocoeval.mean_average_precision_and_recall_per_class(
df, idx_class_dict=idx_class_name, min_score=0.5)
class_idxs = df['true_class_id'].unique()
class_idxs = class_idxs[class_idxs > 0]
print(class_idx_metrics)
assert len(class_idx_metrics) == len(class_idxs)