[Utils] Migrate models/textdet/postprocessors/utils.py

.dev_scripts/covignore.cfg

@@ -23,6 +23,11 @@ mmocr/models/textdet/detectors/single_stage_text_detector.py
 # It will be removed after all utils are moved to mmocr.utils
 mmocr/core/evaluation/utils.py
 mmocr/models/textdet/postprocessors/utils.py
+utils/postprocessor_utils.py
+
+# It will be removed after all models have been refactored
+mmocr/utils/ocr.py
+mmocr/models/textdet/modules/proposal_local_graph.py
 mmocr/utils/bbox_utils.py
 mmocr/datasets/pipelines/crop.py
 

mmocr/models/textdet/modules/proposal_local_graph.py

@@ -5,7 +5,7 @@ import torch
 from lanms import merge_quadrangle_n9 as la_nms
 from mmcv.ops import RoIAlignRotated
 
-from mmocr.models.textdet.postprocessors.utils import fill_hole
+from mmocr.utils import fill_hole
 from .utils import (euclidean_distance_matrix, feature_embedding,
                     normalize_adjacent_matrix)
 

mmocr/models/textdet/postprocessors/fce_postprocessor.py

@@ -9,8 +9,8 @@ from numpy.fft import ifft
 
 from mmocr.core import TextDetDataSample
 from mmocr.registry import MODELS
+from mmocr.utils import fill_hole
 from .base_postprocessor import BaseTextDetPostProcessor
-from .utils import fill_hole
 
 
 @MODELS.register_module()

mmocr/models/textdet/postprocessors/textsnake_postprocessor.py

@@ -11,8 +11,8 @@ from skimage.morphology import skeletonize
 
 from mmocr.core import TextDetDataSample
 from mmocr.registry import MODELS
+from mmocr.utils import fill_hole
 from .base_postprocessor import BaseTextDetPostProcessor
-from .utils import fill_hole
 
 
 @MODELS.register_module()

mmocr/models/textdet/postprocessors/utils.py

@@ -4,50 +4,7 @@ import operator
 
 import cv2
 import numpy as np
-import pyclipper
 from numpy.linalg import norm
-from shapely.geometry import Polygon
-
-
-def filter_instance(area, confidence, min_area, min_confidence):
-    return bool(area < min_area or confidence < min_confidence)
-
-
-def box_score_fast(bitmap, _box):
-    h, w = bitmap.shape[:2]
-    box = _box.copy()
-    xmin = np.clip(np.floor(box[:, 0].min()).astype(np.int32), 0, w - 1)
-    xmax = np.clip(np.ceil(box[:, 0].max()).astype(np.int32), 0, w - 1)
-    ymin = np.clip(np.floor(box[:, 1].min()).astype(np.int32), 0, h - 1)
-    ymax = np.clip(np.ceil(box[:, 1].max()).astype(np.int32), 0, h - 1)
-
-    mask = np.zeros((ymax - ymin + 1, xmax - xmin + 1), dtype=np.uint8)
-    box[:, 0] = box[:, 0] - xmin
-    box[:, 1] = box[:, 1] - ymin
-    cv2.fillPoly(mask, box.reshape(1, -1, 2).astype(np.int32), 1)
-    return cv2.mean(bitmap[ymin:ymax + 1, xmin:xmax + 1], mask)[0]
-
-
-def unclip(box, unclip_ratio=1.5):
-    poly = Polygon(box)
-    distance = poly.area * unclip_ratio / poly.length
-    offset = pyclipper.PyclipperOffset()
-    offset.AddPath(box, pyclipper.JT_ROUND, pyclipper.ET_CLOSEDPOLYGON)
-    expanded = np.array(offset.Execute(distance))
-    return expanded
-
-
-def fill_hole(input_mask):
-    h, w = input_mask.shape
-    canvas = np.zeros((h + 2, w + 2), np.uint8)
-    canvas[1:h + 1, 1:w + 1] = input_mask.copy()
-
-    mask = np.zeros((h + 4, w + 4), np.uint8)
-
-    cv2.floodFill(canvas, mask, (0, 0), 1)
-    canvas = canvas[1:h + 1, 1:w + 1].astype(np.bool)
-
-    return ~canvas | input_mask
 
 
 class Node:

mmocr/utils/__init__.py

@@ -23,6 +23,7 @@ from .polygon_utils import (boundary_iou, crop_polygon, is_poly_inside_rect,
                             poly_intersection, poly_iou, poly_make_valid,
                             poly_union, polys2shapely, rescale_polygon,
                             rescale_polygons)
+from .postprocessor_utils import fill_hole
 from .setup_env import register_all_modules
 from .string_util import StringStrip
 
@@ -40,5 +41,5 @@ __all__ = [
     'disable_text_recog_aug_test', 'box_center_distance', 'box_diag',
     'compute_hmean', 'filter_2dlist_result', 'many2one_match_ic13',
     'one2one_match_ic13', 'select_top_boundary', 'boundary_iou',
-    'point_distance', 'points_center'
+    'point_distance', 'points_center', 'fill_hole'
 ]

mmocr/utils/postprocessor_utils.py

@@ -0,0 +1,17 @@
+# Copyright (c) OpenMMLab. All rights reserved.
+import cv2
+import numpy as np
+
+
+def fill_hole(input_mask):
+    # TODO typehints & test & docstring
+    h, w = input_mask.shape
+    canvas = np.zeros((h + 2, w + 2), np.uint8)
+    canvas[1:h + 1, 1:w + 1] = input_mask.copy()
+
+    mask = np.zeros((h + 4, w + 4), np.uint8)
+
+    cv2.floodFill(canvas, mask, (0, 0), 1)
+    canvas = canvas[1:h + 1, 1:w + 1].astype(np.bool)
+
+    return ~canvas | input_mask