PaddleOCR
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PaddlePaddle
打包后提示识别错误could not create a primitive
请提供下述完整信息以便快速定位问题/Please provide the following information to quickly locate the problem
- 系统环境/System Environment：
- win10 64
- 版本号/Version：
- Paddle： 2.6.1
- PaddleOCR： 2.7.5
- 问题相关组件/Related components：
- tools\infer\predict_det.py self.predictor.run() 无法启动
- 运行指令/Command Code：
ocr = PaddleOCR(use_angle_cls=False, use_gpu=False, show_log=False) text = ocr.ocr(file_path, cls=True)
- 完整报错/Complete Error Message：
Traceback (most recent call last): File "main.py", line 96, in <module> File "app.py", line 36, in App File "module\img_to_pdf.py", line 23, in ConvertToPdf File "module\img_to_pdf.py", line 128, in __model_2 File "module\img_to_pdf.py", line 228, in InvoiceOcr File "paddleocr.py", line 682, in ocr File "tools\infer\predict_system.py", line 76, in __call__ dt_boxes, elapse = self.text_detector(img) ^^^^^^^^^^^^^^^^^^^^^^^ File "tools\infer\predict_det.py", line 254, in __call__ self.predictor.run() RuntimeError: could not create a primitive
打包后在cmd窗口运行能执行识别成功，但是大概过了一会就提示错误无法进行下去
是指打包成wheel包之后识别报错吗
是的，我也按照 #34492 关闭mkldnn加速，也没有效果. 系统环境： 64bit、AMD64 spec 如下： `# -- mode: python ; coding: utf-8 -- import sys ; sys.setrecursionlimit(sys.getrecursionlimit() * 5)
block_cipher = None a = Analysis(['main.py'], pathex=['E:\PyEnviroment\Lib\site-packages\paddleocr', 'E:\PyEnviroment\Lib\site-packages\paddle\libs'], binaries=[('E:\PyEnviroment\Lib\site-packages\paddle\libs', '.')], datas=[], hiddenimports=['framework_pb2','scipy.special.cython_special','skimage','skimage.feature._orb_descriptor_positions','skimage.filters.edges', 'skimage.data._fetchers'], hookspath=['.'], runtime_hooks=[], excludes=['matplotlib'], win_no_prefer_redirects=False, win_private_assemblies=False, cipher=block_cipher, noarchive=False) pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher) exe = EXE(pyz, a.scripts, [], exclude_binaries=True, name='main', debug=False, bootloader_ignore_signals=False, strip=False, upx=True, console=True) coll = COLLECT(exe, a.binaries, a.zipfiles, a.datas, strip=False, upx=True, upx_exclude=[], name='mam_it')`
