mirror of
https://github.com/RapidAI/RapidOCR.git
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100 lines
3.6 KiB
Python
100 lines
3.6 KiB
Python
# -*- encoding: utf-8 -*-
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# @Author: SWHL
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# @Contact: liekkaskono@163.com
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import math
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import random
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from pathlib import Path
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import cv2
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import numpy as np
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from PIL import Image, ImageDraw, ImageFont
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# from rapidocr_onnxruntime import TextSystem
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from rapidocr_openvino import TextSystem
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def draw_ocr_box_txt(image, boxes, txts, font_path,
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scores=None, text_score=0.5):
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if not Path(font_path).exists():
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raise FileNotFoundError(f'The {font_path} does not exists! \n'
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f'Please download the file in the https://drive.google.com/drive/folders/1x_a9KpCo_1blxH1xFOfgKVkw1HYRVywY')
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h, w = image.height, image.width
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img_left = image.copy()
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img_right = Image.new('RGB', (w, h), (255, 255, 255))
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random.seed(0)
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draw_left = ImageDraw.Draw(img_left)
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draw_right = ImageDraw.Draw(img_right)
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for idx, (box, txt) in enumerate(zip(boxes, txts)):
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if scores is not None and scores[idx] < text_score:
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continue
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color = (random.randint(0, 255),
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random.randint(0, 255),
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random.randint(0, 255))
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draw_left.polygon(box, fill=color)
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draw_right.polygon([box[0][0], box[0][1],
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box[1][0], box[1][1],
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box[2][0], box[2][1],
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box[3][0], box[3][1]],
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outline=color)
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box_height = math.sqrt((box[0][0] - box[3][0])**2
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+ (box[0][1] - box[3][1])**2)
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box_width = math.sqrt((box[0][0] - box[1][0])**2
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+ (box[0][1] - box[1][1])**2)
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if box_height > 2 * box_width:
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font_size = max(int(box_width * 0.9), 10)
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font = ImageFont.truetype(font_path, font_size,
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encoding="utf-8")
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cur_y = box[0][1]
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for c in txt:
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char_size = font.getsize(c)
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draw_right.text((box[0][0] + 3, cur_y), c,
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fill=(0, 0, 0), font=font)
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cur_y += char_size[1]
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else:
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font_size = max(int(box_height * 0.8), 10)
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font = ImageFont.truetype(font_path, font_size, encoding="utf-8")
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draw_right.text([box[0][0], box[0][1]], txt,
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fill=(0, 0, 0), font=font)
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img_left = Image.blend(image, img_left, 0.5)
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img_show = Image.new('RGB', (w * 2, h), (255, 255, 255))
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img_show.paste(img_left, (0, 0, w, h))
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img_show.paste(img_right, (w, 0, w * 2, h))
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return np.array(img_show)
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def visualize(image_path, boxes, rec_res, font_path="fonts/msyh.ttc"):
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image = Image.open(image_path)
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txts = [rec_res[i][0] for i in range(len(rec_res))]
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scores = [rec_res[i][1] for i in range(len(rec_res))]
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draw_img = draw_ocr_box_txt(image, boxes,
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txts, font_path,
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scores,
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text_score=0.5)
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draw_img_save = Path("./inference_results/")
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if not draw_img_save.exists():
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draw_img_save.mkdir(parents=True, exist_ok=True)
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image_save = str(draw_img_save / f'infer_{Path(image_path).name}')
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cv2.imwrite(image_save, draw_img[:, :, ::-1])
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print(f'The infer result has saved in {image_save}')
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if __name__ == '__main__':
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config_path = 'config.yaml'
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text_sys = TextSystem(config_path)
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image_path = r'test_images/det_images/ch_en_num.jpg'
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img = cv2.imread(image_path)
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dt_boxes, rec_res = text_sys(img)
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visualize(image_path, dt_boxes, rec_res,
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font_path='resources/fonts/msyh.ttc') |