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Have I written custom code (as opposed to using a stock example script provided in MediaPipe)
No
OS Platform and Distribution
iOS 18.1.1
Mobile device if the issue happens on mobile device
iPhone 15
Browser and version if the issue happens on browser
No response
Programming Language and version
Swift
MediaPipe version
0.10.20
Bazel version
No response
Solution
Object Detection (any)
Android Studio, NDK, SDK versions (if issue is related to building in Android environment)
No response
Xcode & Tulsi version (if issue is related to building for iOS)
16.1
Describe the actual behavior
Runtime error: "objc[1064]: Class TFLBufferConvert is implemented in both /private/var/containers/Bundle/Application/D3732F45-70C8-458D-8BD7-3A8E99C8BB47/ObjectDetector.app/ObjectDetector.debug.dylib (0x106250610) and /private/var/containers/Bundle/Application/D3732F45-70C8-458D-8BD7-3A8E99C8BB47/ObjectDetector.app/ObjectDetector.debug.dylib (0x1062526e0). One of the two will be used. Which one is undefined."
Describe the expected behaviour
I should be able to use "pod 'TensorFlowLiteSwift', '~> 0.0.1-nightly', :subspecs => ['Metal']"
Standalone code/steps you may have used to try to get what you need
Use this Podfile
target 'ObjectDetector' do
use_frameworks!
pod 'MediaPipeTasksVision', '0.10.20'
pod 'TensorFlowLiteSwift', '~> 0.0.1-nightly', :subspecs => ['Metal']
# Pods for ObjectDetector
end
pod install
Build & run iOS app
Other info / Complete Logs
Most developers considering using Mediapipe in iOS apps will have separate TFLite models executed using TensorFlowLiteSwift directly. However, once the Mediapipe pod (eg MediaPipeTasksVision) is added to your podfile, existing usage of TensorFlowLiteSwift + Metal delegate will cause runtime errors. They both link to the same Obj-C code.
The Mediapipe iOS Pod should support a configuration that does not collide with TensorFlowLiteSwift Pod + Metal to allow greater iOS adoption with apps already using TFLite.
objc[1064]: Class TFLBufferConvert is implemented in both /private/var/containers/Bundle/Application/D3732F45-70C8-458D-8BD7-3A8E99C8BB47/ObjectDetector.app/ObjectDetector.debug.dylib (0x106250610) and /private/var/containers/Bundle/Application/D3732F45-70C8-458D-8BD7-3A8E99C8BB47/ObjectDetector.app/ObjectDetector.debug.dylib (0x1062526e0). One of the two will be used. Which one is undefined.
WARNING: All log messages before absl::InitializeLog() is called are written to STDERR
I0000 00:00:1734382404.659640 236024 gl_context.cc:369] GL version: 3.0 (OpenGL ES 3.0 Metal - 101), renderer: Apple A16 GPU
The text was updated successfully, but these errors were encountered:
Have I written custom code (as opposed to using a stock example script provided in MediaPipe)
No
OS Platform and Distribution
iOS 18.1.1
Mobile device if the issue happens on mobile device
iPhone 15
Browser and version if the issue happens on browser
No response
Programming Language and version
Swift
MediaPipe version
0.10.20
Bazel version
No response
Solution
Object Detection (any)
Android Studio, NDK, SDK versions (if issue is related to building in Android environment)
No response
Xcode & Tulsi version (if issue is related to building for iOS)
16.1
Describe the actual behavior
Describe the expected behaviour
I should be able to use "pod 'TensorFlowLiteSwift', '~> 0.0.1-nightly', :subspecs => ['Metal']"
Standalone code/steps you may have used to try to get what you need
Use this Podfile
pod install
Build & run iOS app
Other info / Complete Logs
Most developers considering using Mediapipe in iOS apps will have separate TFLite models executed using
TensorFlowLiteSwift
directly. However, once the Mediapipe pod (egMediaPipeTasksVision
) is added to your podfile, existing usage ofTensorFlowLiteSwift
+ Metal delegate will cause runtime errors. They both link to the same Obj-C code.The Mediapipe iOS Pod should support a configuration that does not collide with
TensorFlowLiteSwift
Pod + Metal to allow greater iOS adoption with apps already using TFLite.The text was updated successfully, but these errors were encountered: