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import tempfile | |
import os | |
import gradio as gr | |
import paddlehub as hub | |
from PIL import Image | |
pp_ocrv3 = hub.Module(name="ch_pp-ocrv3") | |
def inference(img): | |
""" | |
[{'save_path': '', 'data': [{'text': '飞桨“大航海”计划', 'confidence': 0.9351316094398499, 'text_box_position': [[246, 16], [384, 14], [384, 33], [246, 35]]}, {'text': '产业智船化升圾', 'confidence': 0.8330735564231873, 'text_box_position': [[433, 109], [487, 109], [487, 119], [433, 119]]}]}] | |
""" | |
results = pp_ocrv3.recognize_text(paths=[img],use_gpu=False,visualization=False) | |
print(results) | |
res = [] | |
data = results[0]['data'] | |
for item in data: | |
if item['confidence'] > 0.75 and len(item['text']) > 0: | |
res.append(item['text']) | |
return res | |
title="ch_PP-OCRv3" | |
description="ch_PP-OCRv3 is a practical ultra-lightweight OCR system developed by PaddleOCR." | |
examples=[['test.png']] | |
gr.Interface(inference,gr.inputs.Image(type="filepath"), | |
outputs=[gr.Textbox(label="Output Message")], | |
title=title, | |
description=description, | |
examples=examples).launch(enable_queue=True) |