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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
import os
import sys
__dir__ = os.path.dirname(os.path.abspath(__file__))
sys.path.append(__dir__)
sys.path.insert(0, os.path.abspath(os.path.join(__dir__, '..')))
os.environ["FLAGS_allocator_strategy"] = 'auto_growth'
import cv2
import json
import paddle
from ppocr.data import create_operators, transform
from ppocr.modeling.architectures import build_model
from ppocr.postprocess import build_post_process
from ppocr.utils.save_load import load_model
from ppocr.utils.utility import get_image_file_list
import tools.program as program
from PIL import Image, ImageDraw, ImageFont
import math
def draw_e2e_res_for_chinese(image,
boxes,
txts,
config,
img_name,
font_path="./doc/simfang.ttf"):
h, w = image.height, image.width
img_left = image.copy()
img_right = Image.new('RGB', (w, h), (255, 255, 255))
import random
random.seed(0)
draw_left = ImageDraw.Draw(img_left)
draw_right = ImageDraw.Draw(img_right)
for idx, (box, txt) in enumerate(zip(boxes, txts)):
box = np.array(box)
box = [tuple(x) for x in box]
color = (random.randint(0, 255), random.randint(0, 255),
random.randint(0, 255))
draw_left.polygon(box, fill=color)
draw_right.polygon(box, outline=color)
font = ImageFont.truetype(font_path, 15, encoding="utf-8")
draw_right.text([box[0][0], box[0][1]], txt, fill=(0, 0, 0), font=font)
img_left = Image.blend(image, img_left, 0.5)
img_show = Image.new('RGB', (w * 2, h), (255, 255, 255))
img_show.paste(img_left, (0, 0, w, h))
img_show.paste(img_right, (w, 0, w * 2, h))
save_e2e_path = os.path.dirname(config['Global'][
'save_res_path']) + "/e2e_results/"
if not os.path.exists(save_e2e_path):
os.makedirs(save_e2e_path)
save_path = os.path.join(save_e2e_path, os.path.basename(img_name))
cv2.imwrite(save_path, np.array(img_show)[:, :, ::-1])
logger.info("The e2e Image saved in {}".format(save_path))
def draw_e2e_res(dt_boxes, strs, config, img, img_name):
if len(dt_boxes) > 0:
src_im = img
for box, str in zip(dt_boxes, strs):
box = box.astype(np.int32).reshape((-1, 1, 2))
cv2.polylines(src_im, [box], True, color=(255, 255, 0), thickness=2)
cv2.putText(
src_im,
str,
org=(int(box[0, 0, 0]), int(box[0, 0, 1])),
fontFace=cv2.FONT_HERSHEY_COMPLEX,
fontScale=0.7,
color=(0, 255, 0),
thickness=1)
save_det_path = os.path.dirname(config['Global'][
'save_res_path']) + "/e2e_results/"
if not os.path.exists(save_det_path):
os.makedirs(save_det_path)
save_path = os.path.join(save_det_path, os.path.basename(img_name))
cv2.imwrite(save_path, src_im)
logger.info("The e2e Image saved in {}".format(save_path))
def main():
global_config = config['Global']
# build model
model = build_model(config['Architecture'])
load_model(config, model)
# build post process
post_process_class = build_post_process(config['PostProcess'],
global_config)
# create data ops
transforms = []
for op in config['Eval']['dataset']['transforms']:
op_name = list(op)[0]
if 'Label' in op_name:
continue
elif op_name == 'KeepKeys':
op[op_name]['keep_keys'] = ['image', 'shape']
transforms.append(op)
ops = create_operators(transforms, global_config)
save_res_path = config['Global']['save_res_path']
if not os.path.exists(os.path.dirname(save_res_path)):
os.makedirs(os.path.dirname(save_res_path))
model.eval()
with open(save_res_path, "wb") as fout:
for file in get_image_file_list(config['Global']['infer_img']):
logger.info("infer_img: {}".format(file))
with open(file, 'rb') as f:
img = f.read()
data = {'image': img}
batch = transform(data, ops)
images = np.expand_dims(batch[0], axis=0)
shape_list = np.expand_dims(batch[1], axis=0)
images = paddle.to_tensor(images)
preds = model(images)
post_result = post_process_class(preds, shape_list)
points, strs = post_result['points'], post_result['texts']
# write result
dt_boxes_json = []
for poly, str in zip(points, strs):
tmp_json = {"transcription": str}
tmp_json['points'] = poly.tolist()
dt_boxes_json.append(tmp_json)
otstr = file + "\t" + json.dumps(dt_boxes_json) + "\n"
fout.write(otstr.encode())
src_img = cv2.imread(file)
if global_config['infer_visual_type'] == 'EN':
draw_e2e_res(points, strs, config, src_img, file)
elif global_config['infer_visual_type'] == 'CN':
src_img = Image.fromarray(
cv2.cvtColor(src_img, cv2.COLOR_BGR2RGB))
draw_e2e_res_for_chinese(
src_img,
points,
strs,
config,
file,
font_path="./doc/fonts/simfang.ttf")
logger.info("success!")
if __name__ == '__main__':
config, device, logger, vdl_writer = program.preprocess()
main()
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