# Copyright (c) OpenMMLab. All rights reserved. import numpy as np import pytest import torch from mmocr.models.textdet.postprocess import (DBPostprocessor, FCEPostprocessor, TextSnakePostprocessor) from mmocr.models.textdet.postprocess.utils import comps2boundaries, poly_nms def test_db_boxes_from_bitmaps(): """Test the boxes_from_bitmaps function in db_decoder.""" pred = np.array([[[0.8, 0.8, 0.8, 0.8, 0], [0.8, 0.8, 0.8, 0.8, 0], [0.8, 0.8, 0.8, 0.8, 0], [0.8, 0.8, 0.8, 0.8, 0], [0.8, 0.8, 0.8, 0.8, 0]]]) preds = torch.FloatTensor(pred).requires_grad_(True) db_decode = DBPostprocessor(text_repr_type='quad', min_text_width=0) boxes = db_decode(preds) assert len(boxes) == 1 def test_fcenet_decode(): k = 1 preds = [] preds.append(torch.ones(1, 4, 10, 10)) preds.append(torch.ones(1, 4 * k + 2, 10, 10)) fcenet_decode = FCEPostprocessor( fourier_degree=k, num_reconstr_points=50, nms_thr=0.01) boundaries = fcenet_decode(preds=preds, scale=1) assert isinstance(boundaries, list) def test_poly_nms(): threshold = 0 polygons = [] polygons.append([10, 10, 10, 30, 30, 30, 30, 10, 0.95]) polygons.append([15, 15, 15, 25, 25, 25, 25, 15, 0.9]) polygons.append([40, 40, 40, 50, 50, 50, 50, 40, 0.85]) polygons.append([5, 5, 5, 15, 15, 15, 15, 5, 0.7]) keep_poly = poly_nms(polygons, threshold) assert isinstance(keep_poly, list) def test_comps2boundaries(): # test comps2boundaries x1 = np.arange(2, 18, 2) x2 = x1 + 2 y1 = np.ones(8) * 2 y2 = y1 + 2 comp_scores = np.ones(8, dtype=np.float32) * 0.9 text_comps = np.stack([x1, y1, x2, y1, x2, y2, x1, y2, comp_scores]).transpose() comp_labels = np.array([1, 1, 1, 1, 1, 3, 5, 5]) shuffle = [3, 2, 5, 7, 6, 0, 4, 1] boundaries = comps2boundaries(text_comps[shuffle], comp_labels[shuffle]) assert len(boundaries) == 3 # test comps2boundaries with blank inputs boundaries = comps2boundaries(text_comps[[]], comp_labels[[]]) assert len(boundaries) == 0 def test_textsnake_decode(): maps = torch.zeros((1, 6, 224, 224), dtype=torch.float) maps[:, 0:2, :, :] = -10. maps[:, 0, 60:100, 50:170] = 10. maps[:, 1, 75:85, 60:160] = 10. maps[:, 2, 75:85, 60:160] = 0. maps[:, 3, 75:85, 60:160] = 1. maps[:, 4, 75:85, 60:160] = 10. # test decoding with text center region of small area maps[:, 0:2, 150:152, 5:7] = 10. textsnake_decode = TextSnakePostprocessor() results = textsnake_decode(torch.squeeze(maps)) assert len(results) == 1 # test decoding with small radius maps.fill_(0.) maps[:, 0:2, :, :] = -10. maps[:, 0, 120:140, 20:40] = 10. maps[:, 1, 120:140, 20:40] = 10. maps[:, 2, 120:140, 20:40] = 0. maps[:, 3, 120:140, 20:40] = 1. maps[:, 4, 120:140, 20:40] = 0.5 results = textsnake_decode(torch.squeeze(maps)) assert len(results) == 0 def test_db_decode(): pred = torch.zeros((1, 8, 8)) pred[0, 2:7, 2:7] = 0.8 expect_result_quad = [[ 1.0, 8.0, 1.0, 1.0, 8.0, 1.0, 8.0, 8.0, 0.800000011920929 ]] expect_result_poly = [[ 8, 2, 8, 6, 6, 8, 2, 8, 1, 6, 1, 2, 2, 1, 6, 1, 0.800000011920929 ]] with pytest.raises(AssertionError): DBPostprocessor(text_repr_type='dummpy') db_decode = DBPostprocessor(text_repr_type='quad', min_text_width=1) result_quad = db_decode(preds=pred) db_decode = DBPostprocessor(text_repr_type='poly', min_text_width=1) result_poly = db_decode(preds=pred) assert result_quad == expect_result_quad assert result_poly == expect_result_poly