# 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()