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[package] qt/5.15.2: Crash under 32-bits Windows machine when loading a jpeg using QPixmap::loadFromData (under 64-bits it works well) #7596

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szigetics opened this issue Oct 8, 2021 · 3 comments
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@szigetics
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szigetics commented Oct 8, 2021

Package and Environment Details (include every applicable attribute)

  • Package Name/Version: qt/5.15.2
  • Operating System+version: Windows 10, 32-bits
  • Compiler+version: MSVC 2019 (16)
  • Conan version: conan 1.41.0
  • Python version: Python 3.10.0

Conan profile (output of conan profile show default or conan profile show <profile> if custom profile is in use)

Configuration for profile default:

[settings]
os=Windows
os_build=Windows
arch=x86
arch_build=x86
compiler=Visual Studio
compiler.version=16
build_type=Release
[options]
[conf]
[build_requires]
[env]

Steps to reproduce (Include if Applicable)

Try to load a jpeg image under Windows, 32-bits, using this snippet (make sure that you have QApplication / QGuiApplication initialized, before this code) :

        std::string encodedImageData = "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";
	auto b64Decoded = QByteArray::fromBase64(encodedImageData.data());
	QPixmap pixmap;
	pixmap.loadFromData(b64Decoded);

More details about the crash :
crash

There is a really similar bug report in the Qt bug tracking system : https://bugreports.qt.io/browse/QTBUG-75292 (Crash trying to load .jpg image via QImage) . The "resolution" of it was that the official Qt build is working fine. I suppose this also means that they think that the error is in the conan build (/ recipe).
I sent a bug report about this issue to Qt Tech Support as well. I will let you know if I get a response from them earlier than I get a response here.

Logs (Include/Attach if Applicable)

There is no relevant log entry in the Qt logs.

@szigetics szigetics added the bug Something isn't working label Oct 8, 2021
@szigetics szigetics changed the title [package] <qt>/<5.15.2>: Crash under 32-bits Windows machine when loading a jpeg using QPixmap::loadFromData (under 64-bits it works well) [package] qt/5.15.2: Crash under 32-bits Windows machine when loading a jpeg using QPixmap::loadFromData (under 64-bits it works well) Oct 8, 2021
@ericLemanissier
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Can you reproduce the bug when using "official" 32bits qt build ?

@szigetics
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Can you reproduce the bug when using "official" 32bits qt build ?

No, I cannot reproduce this bug when using "official" 32bits qt build.
Everything is working fine with that build.

@szigetics
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szigetics commented Oct 11, 2021

@ericLemanissier :
In case if I build the recipe with
-o qt:with_libjpeg=libjpeg-turbo
than everything works fine.

I think that a solution of failing the build with an error message suggesting to use -o qt:with_libjpeg=libjpeg-turbo instead in case if :

  1. the target OS is windows
  2. the target arch is x86
  3. and with_libjpeg==libjpeg

would be fine.

What do you think?

And also we could consider defaulting to -o qt:with_libjpeg=libjpeg-turbo since the official Qt package is using that as well.
The only thing : libjpeg-turbo conan recipe cannot be built for Windows arm64 without this : -e CONAN_CMAKE_SYSTEM_PROCESSOR=aarch64 .
For more info see :
conan-io/conan#8025
conan-io/conan#8026
#3392

Side note :
The official Qt package is using libjpeg-turbo as well :
https://doc.qt.io/qt-5/qtgui-index.html
=>
"LibJPEG-turbo, version 2.1.0"

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