PaddlePaddle / PaddlePaddle/FastDeploy

小程序替换模型失败

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Dominant language
Python
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Merged PRs (30d)
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Description

环境

  • 【FastDeploy版本】: FastDeploy-develop
  • 【系统平台】: Linux x64(Ubuntu 16.04)
  • 【硬件】: Nvidia GPU 2080TI, CUDA 10.1 CUDNN 7.6
  • 【编译语言】:Python(3.7)
  • 【Paddle环境】:padlepaddle2.5.0,paddlelite2.7,Paddle.js-release-v2.2.3

问题日志及出现问题的操作流程

Image

    • 小程序替换识别模型后运行报错:

127.0.0.1-1743131205658.log

      • 提供复现问题的 代码+模型+错误log,供工程师快速定位问题
        1,查询了其他issue,如Web Demo替换模型失败,修改检测模型的infer_shape = [3, 960, 960]之后,检测模型可以正常跑通,但是chunk_1.dat文件有2.25MB,官网只有467KB,可能也是检测模型推理较官方慢的原因?
        2,识别模型修改infer_shape = [3, 48, 320],修改前后都无法正常推理,且自己转换的识别模型有三个chunk分片,共有10.1MB,官方模型只有一个分片3.38MB
        3,也有issue说是版本问题,使用虚拟环境分别尝试了(py3.7+paddlepaddle2.5.5+paddlelite2.7.1+paddlejsconverter1.0.7)、(py3.7+padlepaddle2.5.0,paddlelite2.7,Paddle.js-release-v2.2.3)、(py3.8+paddlepaddle2.6.0+paddlelite没有源),也都不行
        4,个人猜测,在模型转换时无法使用paddlejslite优化,或者具体的量化步骤缺失,导致上述问题,希望能给出转换模型的详细步骤(paddlepaddle、paddlejslite、paddle.js、pp-OCRV3等等)

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the examples/application/js/mini_program/ocrXcx example and compare its official model.json and chunk files with the converted recognition model. Read the attached conversion output and runtime log, then trace the model replacement path in the mini-program entry point. Done means the converted recognition model downloads and runs successfully in the example.

Written by the indexing model from the issue text.

Assessment

Tech stack
javascript, python
Domain
machine-learning, mobile-dev
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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