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[Fix] fix hmean iou

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liukuikun 2022-06-01 02:56:30 +00:00 committed by gaotongxiao
parent 71d1a445c9
commit 2a852f23b5
2 changed files with 8 additions and 7 deletions
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10
mmocr/metrics/hmean_iou_metric.py
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@ -171,15 +171,15 @@ class HmeanIOUMetric(BaseMetric):
dataset_pred_num[i] += np.sum(~pred_ignore_flags) dataset_pred_num[i] += np.sum(~pred_ignore_flags)
for i, pred_score_thr in enumerate(self.pred_score_thrs): for i, pred_score_thr in enumerate(self.pred_score_thrs):
precision, recall, hmean = compute_hmean( recall, precision, hmean = compute_hmean(
int(dataset_hit_num[i]), int(dataset_hit_num[i]), int(dataset_hit_num[i]), int(dataset_hit_num[i]),
int(dataset_gt_num), int(dataset_pred_num[i])) int(dataset_gt_num), int(dataset_pred_num[i]))
eval_results = dict( eval_results = dict(
precision=precision, recall=recall, hmean=hmean) precision=precision, recall=recall, hmean=hmean)
logger.info(f'prediction score threshold: {pred_score_thr}, ' logger.info(f'prediction score threshold: {pred_score_thr:.2f}, '
f'recall: {eval_results["recall"]:.3f}, ' f'recall: {eval_results["recall"]:.4f}, '
f'precision: {eval_results["precision"]:.3f}, ' f'precision: {eval_results["precision"]:.4f}, '
f'hmean: {eval_results["hmean"]:.3f}\n') f'hmean: {eval_results["hmean"]:.4f}\n')
if eval_results['hmean'] > best_eval_results['hmean']: if eval_results['hmean'] > best_eval_results['hmean']:
best_eval_results = eval_results best_eval_results = eval_results
return best_eval_results return best_eval_results

5
tests/test_metrics/test_hmean_iou.py
View File

@ -68,9 +68,10 @@ class TestHmeanIOU(unittest.TestCase):
pred_data_sample = TextDetDataSample() pred_data_sample = TextDetDataSample()
pred_data_sample.pred_instances = InstanceData() pred_data_sample.pred_instances = InstanceData()
pred_data_sample.pred_instances.polygons = [ pred_data_sample.pred_instances.polygons = [
torch.FloatTensor([0, 0, 1, 0, 1, 1, 0, 1]),
torch.FloatTensor([0, 0, 1, 0, 1, 1, 0, 1]) torch.FloatTensor([0, 0, 1, 0, 1, 1, 0, 1])
] ]
pred_data_sample.pred_instances.scores = torch.FloatTensor([0.8]) pred_data_sample.pred_instances.scores = torch.FloatTensor([1, 0.95])
predictions.append(pred_data_sample.to_dict()) predictions.append(pred_data_sample.to_dict())
self.predictions = predictions self.predictions = predictions
@ -81,7 +82,7 @@ class TestHmeanIOU(unittest.TestCase):
metric.process(self.gt, self.predictions) metric.process(self.gt, self.predictions)
eval_results = metric.evaluate(size=2) eval_results = metric.evaluate(size=2)
precision = 3 / 4 precision = 3 / 5
recall = 3 / 4 recall = 3 / 4
hmean = 2 * precision * recall / (precision + recall) hmean = 2 * precision * recall / (precision + recall)
target_result = { target_result = {