环境安装:PaddleHub一键OCR中文识别:https://aistudio.baidu.com/aistudio/projectdetail/512888
开源代码:https://github.com/PaddlePaddle/PaddleHub
cd paddlehub
python 1.py
新建test:测试图片 新建out:保存图片 新建test.txt 测试图片名列表
1.py:
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import os
import paddlehub as hub
import cv2
save_path='out'
with open('test.txt', 'r') as f:
test_img_path=[]
for line in f:
test_img_path.append(line.strip())
print(test_img_path)
#path_list = [args['dataset'] + '/' + path for path in os.listdir(args['dataset'])]
# 加载移动端预训练模型
ocr = hub.Module(name="chinese_ocr_db_crnn_mobile")
np_images =[cv2.imread(image_path) for image_path in test_img_path] #读取测试文件夹test.txt中的照片路径
results = ocr.recognize_text(
images=np_images, # 图片数据,ndarray.shape 为 [H, W, C],BGR格式;
use_gpu=False, # 是否使用 GPU;若使用GPU,请先设置CUDA_VISIBLE_DEVICES环境变量
output_dir='out', # 图片的保存路径,默认设为 ocr_result;
visualization=True, # 是否将识别结果保存为图片文件;
box_thresh=0.5, # 检测文本框置信度的阈值;
text_thresh=0.5) # 识别中文文本置信度的阈值;
for result in results:
data = result['data']
save_path = result['save_path']
for infomation in data:
print('text: ', infomation['text'], '\nconfidence: ', infomation['confidence'], '\ntext_box_position: ', infomation['text_box_position'])