Errorcode = $err lpdnet

errorcode = $err lpdnet

must be a RFC compliant error code. text is the message to return to LPDNET Loop dev network part of addr. ANY Match any IP address. TCP/IP AX User's Manual Installing under OS/ The main error codes are: (Device not valid for session): the printer name is used for. This bash script compiles openalpr for android. You just need to provide the path to Android SDK and Android NDK in the first lines of this code and execute.

Errorcode = $err lpdnet - consider, that

& Mail -s "change tape, touch $flag" \ $email loop2: if ( -f $flag ) then if ( -s $flag ) then /bin/rm $flag echo backup done ......."

It's very weird when the eval.py is done. it still print the " ←> or <Shift><→

openvinotoolkit / training_extensionsGoto GithubPK

training_extensionsView Code? Open in Web Editor NEW1.0K51.0367.0330.85 MB

Trainable models and NN optimization tools

License: Apache License 2.0

Python 99.39%Shell 0.05%Jupyter Notebook 0.46%Makefile 0.11%openvinocomputer-visiondeep-learningtensorflowpytorchneural-networks-compressiondetectionssdsegmentationtext-detectiontext-recognitionface-recognitionsuper-resolutionquantizationsparsity

training_extensions's Introduction

pythonblackmypyopenvino

OpenVINO™ Training Extensions provide a convenient environment to train Deep Learning models and convert them using the OpenVINO™ toolkit for optimized inference.

Prerequisites

Repository components

Quick start guide

In order to get started with OpenVINO™ Training Extensions see the quick-start guide.

GitHub Repository

The project files can be found in OpenVINO™ Training Extensions. Previously developed models can be found on the misc branch.

License

Deep Learning Deployment Toolkit is licensed under Apache License Version 2.0. By contributing to the project, you agree to the license and copyright terms therein and release your contribution under these terms.

Contributing

Please read the Contribution guide before starting work on a pull request.

Known limitations

Training, export, and evaluation scripts for TensorFlow- and most PyTorch-based models from the misc branch are, currently, not production-ready. They serve exploratory purposes and are not validated.


* Other names and brands may be claimed as the property of others.

training_extensions's People

Forkers

malikaoudjifhansenchen2011zingornaiLibraryMeedmakhloufsnosov1xuyunlongshanhuyates1987tony109060581undeadinuZinovievVladimirmustafaxfeMattCurryComyuhonghong7035lnhieuvnNadeemRawtheryeknafarlanybassjijunweiCvRockerAlexanderDokuchaevlintreeskennethchngrib0ed0vDaniil-Osokinelenashtienduchoangchenqi1997daydreamer2023stefanruantintnvadimadrlovenan95AlexKoff88DmitriySidnevdruzhkov-paulikostinaIlya-Krylovhsulin0806pskiran1feolcncaichangqiPandinosaurusFinniuFlavio58itzpg1995xiaogangLixuhuaze707313rena-ganbaHust-wayneAi-is-lightanjingxanjingxingVisionZQLeo-xxxsalt-flyjayle19930918kar98kbangFengYen-Changevgeny-izutovczero69lachinovyds5817RecardoDKniexiaokunfujiehuangm-decostertongni1975mahinlmaxiaoyubingjhvics1JinYAnGHesovrasovMrYZDxzry6afeizaiadithyapremshiyuan0806maodong2056garrachFake-BBAzzzhackerLeonidBeynensonniuwenjuJEONsoyunwinnerineastbuptdbjyunhengzidiversity-aigrady1006viwoquInaaasmartwellhajungong007WaiYanNyeinNaingJeffW99tspannhwfx4758shixinlishixinlisheqi

training_extensions's Issues

Don't know how to inference

hello @[email protected]@alexey-sidnev AlexanderDokuchaev and everyone, Thank for your code. I have already trained and exported to frozen model (.pb) without optimize, errorcode = $err lpdnet. Then i use frozen model for tensorrt inference server. but I got the wrong result compared to using infer.py file (checkpoints)

I don't know if my export .pb file is incorrect or my clients code are wrong

#### MY CLIENTS CODE #####importargparseimportosimportrandomimportcv2importnumpyasnpimporttensorflowastfimporttensorflow.contrib.slimasslimfrombuiltinsimportrangefromtensorrtserver.apiimport*importtensorrtserver.api.model_config_pb2asmodel_configif__name__=='__main__': input_name='input'output_name='d_predictions'model_name='lp-recognitor'protocol=ProtocolType.from_str('http') ctx=InferContext('localhost:8000', errorcode = $err lpdnet, protocol, model_name, -1, False) img=cv2.imread("/data/tmp/plate/000111.png") img=np.float32(img) img=cv2.resize(img, (24, 94)) in_frame=img.reshape((24, 94, 3)) input_data= [] input_data.append(in_frame) results= [] results.append(ctx.run( { input_name : input_data }, { output_name : (InferContext.ResultFormat.RAW) })) errorcode = $err lpdnet print("****************results*********************", results)

Why not the eval.py print the final result instead of the " ." and the validation process is not ending.

Expected Behavior

Expected a valid result

Current Behavior

Validation process is not finishing, it is printing " errorcode = $err lpdnet

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