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I am trying to run face_effect demo which renders the face paint and glasses. It is not included in the examples so I am making a binary using the provided library 'face_effect_gpu_deps'

My build file is at /mediapipe/examples/desktop/face_effect/BUILD similar to other provided examples

cc_binary(
    name = "face_effect_gpu",
    deps = [
        "//mediapipe/examples/desktop:demo_run_graph_main_gpu",
        "//mediapipe/graphs/face_effect:face_effect_gpu_deps",
    ],
)

On executing this binary, I get this error: collection.h:417 Check failed: id < EndId() (1 vs. 1)

I have been able to run all the other examples successfully on both CPU and GPU. Could you please let me know what is going wrong or provide an example to run face effects?

Build command: bazel build -c opt --copt -DMESA_EGL_NO_X11_HEADERS --copt -DEGL_NO_X11 mediapipe/examples/desktop/face_effect:face_effect_gpu

Run command (using the face_effect_gpu.pbtxt): GLOG_logtostderr=1 bazel-bin/mediapipe/examples/desktop/face_effect/face_effect_gpu --calculator_graph_config_file=mediapipe/graphs/face_effect/face_effect_gpu.pbtxt

System information (Please provide as much relevant information as possible)

• Have I written custom code (as opposed to using a stock example script provided in Mediapipe): Modified stock example
• OS Platform and Distribution (e.g., Linux Ubuntu 16.04, Android 11, iOS 14.4): Ubuntu 20.04.3 LTS
• MediaPipe version: 0.8.9.1
• Bazel version: 4.2.1
• Solution (e.g. FaceMesh, Pose, Holistic): FaceMesh
• Programming Language and version ( e.g. C++, Python, Java): C++

Describe the expected behavior: The face_effect module runs

Other info / Complete Logs : I20220206 22:37:01.470067 158366 demo_run_graph_main_gpu.cc:58] Initialize the calculator graph. I20220206 22:37:01.475389 158366 demo_run_graph_main_gpu.cc:62] Initialize the GPU. I20220206 22:37:01.482228 158366 gl_context_egl.cc:162] Successfully initialized EGL. Major : 1 Minor: 5 I20220206 22:37:01.529899 158383 gl_context.cc:334] GL version: 3.2 (OpenGL ES 3.2 NVIDIA 460.91.03) I20220206 22:37:01.530066 158366 demo_run_graph_main_gpu.cc:68] Initialize the camera or load the video. I20220206 22:37:01.701638 158366 demo_run_graph_main_gpu.cc:89] Start running the calculator graph. I20220206 22:37:01.705971 158366 demo_run_graph_main_gpu.cc:94] Start grabbing and processing frames. F20220206 22:37:01.706034 158369 collection.h:417] Check failed: id < EndId() (1 vs. 1) *** Check failure stack trace: *** @ 0x56281e95b0ab google::LogMessage::SendToLog() @ 0x56281e95705d google::LogMessage::Flush() @ 0x56281e9574cd google::LogMessageFatal::~LogMessageFatal() @ 0x56281e885864 mediapipe::internal::Collection<>::Get() @ 0x56281e8ae1a8 mediapipe::InputSidePacketHandler::SetInternal() @ 0x56281e8ae9c7 mediapipe::InputSidePacketHandler::Set() @ 0x56281e8ad16e mediapipe::OutputSidePacketImpl::SetInternal() @ 0x56281e8ad3b5 mediapipe::OutputSidePacketImpl::Set() @ 0x56281e85f1f4 mediapipe::(anonymous namespace)::EnvGeneratorCalculator::Open() @ 0x56281e8a243c mediapipe::CalculatorNode::OpenNode() @ 0x56281e88cebe mediapipe::internal::SchedulerQueue::OpenCalculatorNode() @ 0x56281e88d83b mediapipe::internal::SchedulerQueue::RunNextTask() @ 0x56281e8cbfe7 mediapipe::ThreadPool::RunWorker() @ 0x56281e8ccd59 mediapipe::ThreadPool::WorkerThread::ThreadBody() @ 0x7fda734ad609 start_thread @ 0x7fda700de293 clone @ (nil) (unknown) Aborted (core dumped)

Hi @abhisaar, Can you share your code changes to troubleshoot the issue. Thanks!

Thank you @sgowroji for your reply. Please find attached my build file (added a .txt so that Github will let me attach it). I am building the already provided targets at 'face_effect:face_effect_gpu_deps' and using the stock 'face_effect_gpu.pbtxt' file.

Happy to provide more details!

BUILD.txt

Hi Sunil, would you need any other information from me? Thank you.

Hi, I ran into same issue as well. Did you guys find any solution for that in the mean time? Thanks.

Hello @abhisaar, We are upgrading the MediaPipe Legacy Solutions to new MediaPipe solutions However, the libraries, documentation, and source code for all the MediaPipe Legacy Solutions will continue to be available in our GitHub repository and through library distribution services, such as Maven and NPM.

You can continue to use those legacy solutions in your applications if you choose. Though, we would request you to check new MediaPipe solutions which can help you more easily build and customize ML solutions for your applications. These new solutions will provide a superset of capabilities available in the legacy solutions. Thank you

This issue has been marked stale because it has no recent activity since 7 days. It will be closed if no further activity occurs. Thank you.

This issue was closed due to lack of activity after being marked stale for past 7 days.

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