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| # -*- encoding: utf-8 -*- | |
| # @Author: SWHL | |
| # @Contact: [email protected] | |
| import math | |
| import random | |
| import time | |
| from pathlib import Path | |
| import cv2 | |
| import numpy as np | |
| from PIL import Image, ImageDraw, ImageFont | |
| def draw_ocr_box_txt(image, boxes, txts, font_path, | |
| scores=None, text_score=0.5): | |
| h, w = image.height, image.width | |
| img_left = image.copy() | |
| img_right = Image.new('RGB', (w, h), (255, 255, 255)) | |
| random.seed(0) | |
| draw_left = ImageDraw.Draw(img_left) | |
| draw_right = ImageDraw.Draw(img_right) | |
| for idx, (box, txt) in enumerate(zip(boxes, txts)): | |
| if scores is not None and float(scores[idx]) < text_score: | |
| continue | |
| color = (random.randint(0, 255), | |
| random.randint(0, 255), | |
| random.randint(0, 255)) | |
| box = [tuple(v) for v in box] | |
| draw_left.polygon(box, fill=color) | |
| draw_right.polygon([box[0][0], box[0][1], | |
| box[1][0], box[1][1], | |
| box[2][0], box[2][1], | |
| box[3][0], box[3][1]], | |
| outline=color) | |
| box_height = math.sqrt((box[0][0] - box[3][0])**2 | |
| + (box[0][1] - box[3][1])**2) | |
| box_width = math.sqrt((box[0][0] - box[1][0])**2 | |
| + (box[0][1] - box[1][1])**2) | |
| if box_height > 2 * box_width: | |
| font_size = max(int(box_width * 0.9), 10) | |
| font = ImageFont.truetype(font_path, font_size, | |
| encoding="utf-8") | |
| cur_y = box[0][1] | |
| for c in txt: | |
| char_size = font.getsize(c) | |
| draw_right.text((box[0][0] + 3, cur_y), c, | |
| fill=(0, 0, 0), font=font) | |
| cur_y += char_size[1] | |
| else: | |
| font_size = max(int(box_height * 0.8), 10) | |
| font = ImageFont.truetype(font_path, font_size, 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)) | |
| return np.array(img_show) | |
| def visualize(image_path, boxes, txts, scores, | |
| font_path="./fonts/FZYTK.TTF"): | |
| image = Image.open(image_path) | |
| draw_img = draw_ocr_box_txt(image, boxes, | |
| txts, font_path, | |
| scores, | |
| text_score=0.5) | |
| draw_img_save = Path("./inference_results/") | |
| if not draw_img_save.exists(): | |
| draw_img_save.mkdir(parents=True, exist_ok=True) | |
| time_stamp = time.strftime( | |
| '%Y-%m-%d-%H-%M-%S', time.localtime(time.time())) | |
| image_save = str(draw_img_save / f'{time_stamp}_{Path(image_path).name}') | |
| cv2.imwrite(image_save, draw_img[:, :, ::-1]) | |
| return image_save | |