File size: 2,575 Bytes
83b2527 5823579 83b2527 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
from paddleocr import PaddleOCR
import json
from PIL import Image
import gradio as gr
import numpy as np
import cv2
# 获取随机的颜色
def get_random_color():
c = tuple(np.random.randint(0 ,256 ,3).tolist())
return c
# 绘制ocr识别结果
def draw_ocr_bbox( image ,boxes ,colors ):
print(colors)
box_num = len(boxes)
for i in range(box_num):
box = np.reshape(np.array(boxes[i]) ,[-1 ,1 ,2]).astype(np.int64)
image = cv2.polylines(np.array(image) ,[box] ,True ,colors[i] ,2)
return image
# torch.hub.download_url_to_file('https://i.imgur.com/aqMBT0i.jpg', 'example.jpg')
def inference( img: Image.Image ,lang ,confidence ):
ocr = PaddleOCR(use_angle_cls = True ,lang = lang ,use_gpu = False)
# img_path = img.name
img2np = np.array(img)
result = ocr.ocr(img2np ,cls = True)[0]
# rgb
image = img.convert('RGB')
boxes = [line[0] for line in result]
txts = [line[1][0] for line in result]
scores = [line[1][1] for line in result]
# 识别结果
final_result = [dict(boxes = box ,txt = txt ,score = score ,_c = get_random_color()) for box ,txt ,score in
zip(boxes ,txts ,scores)]
# 过滤 score < 0.5 的
final_result = [item for item in final_result if item['score'] > confidence]
im_show = draw_ocr_bbox(image ,[item['boxes'] for item in final_result] ,[item['_c'] for item in final_result])
im_show = Image.fromarray(im_show)
data = [[json.dumps(item['boxes']) ,round(item['score'] ,3) ,item['txt']] for item in final_result]
return im_show ,data
title = 'PaddleOCR'
description = 'Gradio demo for PaddleOCR.'
examples = [
# ['example_imgs/example.jpg' ,'en' ,0.5] ,
# ['example_imgs/ch.jpg' ,'ch' ,0.7] ,
# ['example_imgs/img_12.jpg' ,'en' ,0.7] ,
]
css = ".output_image, .input_image {height: 40rem !important; width: 100% !important;}"
if __name__ == '__main__':
demo = gr.Interface(
inference ,
[gr.Image(type = 'pil' ,label = 'Input') ,
gr.Dropdown(choices = ['ch' ,'en' ,'fr' ,'german' ,'korean' ,'japan'] ,value = 'ch' ,label = 'language') ,
gr.Slider(0.1 ,1 ,0.5 ,step = 0.1 ,label = 'confidence_threshold')
] ,
# 输出
[gr.Image(type = 'pil' ,label = 'Output') ,
gr.Dataframe(headers = ['bbox' ,'score' ,'text'] ,label = 'Result')] ,
title = title ,
description = description ,
examples = examples ,
css = css ,
)
demo.queue(max_size = 10)
demo.launch(debug = True ,server_name = "0.0.0.0") |