50 lines
1.3 KiB
Python
50 lines
1.3 KiB
Python
import numpy as np
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from paddleocr import TextRecognition
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import cv2
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class OCRProcessor:
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def __init__(self):
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self.model = TextRecognition(model_name="PP-OCRv5_server_rec")
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print("OCR模型初始化完成（占位）")
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def predict(self, image_array):
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# 保持原有模型调用方式
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output = self.model.predict(input=image_array)
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# 结构化输出结果
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results = output[0]["rec_text"]
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placeholder_result = results.split(',')
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return placeholder_result
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# 保留原有函数接口
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_processor = OCRProcessor()
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def LPRNinitialize_model():
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return _processor
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def LPRNmodel_predict(image_array):
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# 获取原始预测结果
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raw_result = _processor.predict(image_array)
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# 将结果合并为字符串（如果是列表的话）
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if isinstance(raw_result, list):
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result_str = ''.join(raw_result)
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else:
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result_str = str(raw_result)
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# 过滤掉'·'字符
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filtered_str = result_str.replace('·', '')
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# 转换为字符列表
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char_list = list(filtered_str)
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# 确保返回长度为7的列表
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if len(char_list) >= 7:
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# 如果长度大于等于7，取前7个字符
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return char_list[:7]
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else:
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# 如果长度小于7，用空字符串补齐到7位
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return char_list + [''] * (7 - len(char_list))
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