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Extraction get_rotate_crop_image

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WenmuZhou 2021-06-30 10:45:27 +08:00
parent 4a7f7c7d7b
commit fdaf1f1577
3 changed files with 49 additions and 72 deletions
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46
ppocr/data/imaug/copy_paste.py
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@ -20,40 +20,7 @@ from shapely.geometry import Polygon
from ppocr.data.imaug.iaa_augment import IaaAugment
from ppocr.data.imaug.random_crop_data import is_poly_outside_rect
def get_rotate_crop_image(img, points):
'''
img_height, img_width = img.shape[0:2]
left = int(np.min(points[:, 0]))
right = int(np.max(points[:, 0]))
top = int(np.min(points[:, 1]))
bottom = int(np.max(points[:, 1]))
img_crop = img[top:bottom, left:right, :].copy()
points[:, 0] = points[:, 0] - left
points[:, 1] = points[:, 1] - top
'''
img_crop_width = int(
max(
np.linalg.norm(points[0] - points[1]),
np.linalg.norm(points[2] - points[3])))
img_crop_height = int(
max(
np.linalg.norm(points[0] - points[3]),
np.linalg.norm(points[1] - points[2])))
pts_std = np.float32([[0, 0], [img_crop_width, 0],
[img_crop_width, img_crop_height],
[0, img_crop_height]])
M = cv2.getPerspectiveTransform(points, pts_std)
dst_img = cv2.warpPerspective(
img,
M, (img_crop_width, img_crop_height),
borderMode=cv2.BORDER_REPLICATE,
flags=cv2.INTER_CUBIC)
dst_img_height, dst_img_width = dst_img.shape[0:2]
if dst_img_height * 1.0 / dst_img_width >= 1.5:
dst_img = np.rot90(dst_img)
return dst_img
from tools.infer.utility import get_rotate_crop_image
class CopyPaste(object):
@ -164,6 +131,17 @@ def get_intersection(pD, pG):
def rotate_bbox(img, text_polys, angle, scale=1):
"""
from https://github.com/WenmuZhou/DBNet.pytorch/blob/master/data_loader/modules/augment.py
Args:
img: np.ndarray
text_polys: np.ndarray N*4*2
angle: int
scale: int
Returns:
"""
w = img.shape[1]
h = img.shape[0]

38
tools/infer/predict_system.py
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@ -31,7 +31,7 @@ import tools.infer.predict_det as predict_det
import tools.infer.predict_cls as predict_cls
from ppocr.utils.utility import get_image_file_list, check_and_read_gif
from ppocr.utils.logging import get_logger
from tools.infer.utility import draw_ocr_box_txt, get_current_memory_mb
from tools.infer.utility import draw_ocr_box_txt, get_current_memory_mb, get_rotate_crop_image
import tools.infer.benchmark_utils as benchmark_utils
logger = get_logger()
@ -45,39 +45,6 @@ class TextSystem(object):
if self.use_angle_cls:
self.text_classifier = predict_cls.TextClassifier(args)
def get_rotate_crop_image(self, img, points):
'''
img_height, img_width = img.shape[0:2]
left = int(np.min(points[:, 0]))
right = int(np.max(points[:, 0]))
top = int(np.min(points[:, 1]))
bottom = int(np.max(points[:, 1]))
img_crop = img[top:bottom, left:right, :].copy()
points[:, 0] = points[:, 0] - left
points[:, 1] = points[:, 1] - top
'''
img_crop_width = int(
max(
np.linalg.norm(points[0] - points[1]),
np.linalg.norm(points[2] - points[3])))
img_crop_height = int(
max(
np.linalg.norm(points[0] - points[3]),
np.linalg.norm(points[1] - points[2])))
pts_std = np.float32([[0, 0], [img_crop_width, 0],
[img_crop_width, img_crop_height],
[0, img_crop_height]])
M = cv2.getPerspectiveTransform(points, pts_std)
dst_img = cv2.warpPerspective(
img,
M, (img_crop_width, img_crop_height),
borderMode=cv2.BORDER_REPLICATE,
flags=cv2.INTER_CUBIC)
dst_img_height, dst_img_width = dst_img.shape[0:2]
if dst_img_height * 1.0 / dst_img_width >= 1.5:
dst_img = np.rot90(dst_img)
return dst_img
def print_draw_crop_rec_res(self, img_crop_list, rec_res):
bbox_num = len(img_crop_list)
for bno in range(bbox_num):
@ -89,7 +56,6 @@ class TextSystem(object):
dt_boxes, elapse = self.text_detector(img)
logger.info("dt_boxes num : {}, elapse : {}".format(
len(dt_boxes), elapse))
if dt_boxes is None:
return None, None
@ -99,7 +65,7 @@ class TextSystem(object):
for bno in range(len(dt_boxes)):
tmp_box = copy.deepcopy(dt_boxes[bno])
img_crop = self.get_rotate_crop_image(ori_im, tmp_box)
img_crop = get_rotate_crop_image(ori_im, tmp_box)
img_crop_list.append(img_crop)
if self.use_angle_cls and cls:
img_crop_list, angle_list, elapse = self.text_classifier(

37
tools/infer/utility.py
View File

@ -109,11 +109,10 @@ def init_args():
parser.add_argument("--use_mp", type=str2bool, default=False)
parser.add_argument("--total_process_num", type=int, default=1)
parser.add_argument("--process_id", type=int, default=0)
parser.add_argument("--benchmark", type=bool, default=False)
parser.add_argument("--save_log_path", type=str, default="./log_output/")
return parser
@ -615,5 +614,39 @@ def get_current_memory_mb(gpu_id=None):
return round(cpu_mem, 4), round(gpu_mem, 4), round(gpu_percent, 4)
def get_rotate_crop_image(img, points):
'''
img_height, img_width = img.shape[0:2]
left = int(np.min(points[:, 0]))
right = int(np.max(points[:, 0]))
top = int(np.min(points[:, 1]))
bottom = int(np.max(points[:, 1]))
img_crop = img[top:bottom, left:right, :].copy()
points[:, 0] = points[:, 0] - left
points[:, 1] = points[:, 1] - top
'''
img_crop_width = int(
max(
np.linalg.norm(points[0] - points[1]),
np.linalg.norm(points[2] - points[3])))
img_crop_height = int(
max(
np.linalg.norm(points[0] - points[3]),
np.linalg.norm(points[1] - points[2])))
pts_std = np.float32([[0, 0], [img_crop_width, 0],
[img_crop_width, img_crop_height],
[0, img_crop_height]])
M = cv2.getPerspectiveTransform(points, pts_std)
dst_img = cv2.warpPerspective(
img,
M, (img_crop_width, img_crop_height),
borderMode=cv2.BORDER_REPLICATE,
flags=cv2.INTER_CUBIC)
dst_img_height, dst_img_width = dst_img.shape[0:2]
if dst_img_height * 1.0 / dst_img_width >= 1.5:
dst_img = np.rot90(dst_img)
return dst_img
if __name__ == '__main__':
pass