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Recording EIF Data: A High-fidelity Basis for Reproducing AR Issues

In augmented reality (AR) applications, some complex spatial positioning issues (such as tracking jitter, misalignment between virtual and real objects, content drifting, etc.) are often difficult to fully reproduce through screen recording or logs alone. To address this, we offer the EIF data recording function — a proprietary high-fidelity data dump format that can synchronously record the following key information:

  • Basic device information (model, system, SDK version, etc.)
  • Camera image frames with timestamps
  • The camera's intrinsic and extrinsic matrices of the device
  • IMU sensor data
  • Additional data from external auxiliary inputs (such as GNSS)

Why Is Recording EIF Data Crucial?

Important

EIF data that can reproduce the issue is invaluable.

EIF data can fully reproduce the detailed context when the problem occurred, enabling the development team to accurately reproduce the scenarios encountered by users in an offline environment, greatly improving the efficiency of issue localization. Compared with screen recordings or logs, EIF has the following advantages:

  1. Precise reproduction: Developers can directly replay EIF data in the debugging tool to reproduce the bugs you encountered.
  2. Underlying diagnosis: By comprehensively analyzing various types of data (images, sensors, external inputs, etc.), developers can determine which part of the technology the problem lies in.
  3. Time saving: It avoids the long communication cycle and significantly shortens the period from reporting the problem to resolving it.

How to Record EIF Data

EasyAR provides two ways to record EIF data.

  1. Directly use the API interfaces provided by the SDK to implement the EIF data recording function in your application.
  2. Use the official Mega Toolbox App. It is usually suitable for EasyAR Mega development and issue feedback.

Please refer to our technical documentation for specific operation steps to obtain the operation guide for your usage method and device.

Tip

Visit the following link to view how to call the API interface to implement in-app EIF recording: Input Frame Recording and Simulated Operation.

Visit the following link to view the operation guide for using the Mega Toolbox App: Record Mobile EIF Files Using Toolbox.

A brief overview of the recording process (taking the Mega Toolbox App as an example):

  1. Open the Mega Toolbox App and click On-site Verification and Diagnostic Tool.
  2. Log in to your account, select your positioning library, and start the test.
  3. Try to reproduce your problem. Find an operation mode that can stably reproduce the problem (such as device orientation, browsing method, shooting position, etc.).
  4. After everything is ready, click the red "Record" button to start recording.
  5. After the problem appears, click the red "Stop and Save" button.
  6. The system will automatically generate an EIF file. Connect the device to a computer, export the file to local storage, and then submit it.
Note

EIF files may be large (ranging from hundreds of MB to several GB). It is recommended to record only the core segments containing the problem (usually 10–30 seconds is sufficient).

Best Practice Recommendations

To ensure that your feedback can be processed efficiently, please include the following four types of information when submitting:

Information Type Description
EIF data file The core diagnostic basis, which must include the process of reproducing the problem
Subjective description of the phenomenon Clearly explain the behavior you observed (such as "The navigation arrow suddenly jumped to the ceiling when making a left turn")
Screen recording or screenshot Assist in visualizing the problem and intuitively show "what the user finally saw"
Auxiliary context information Including:
• Your device model and operating system version
• The version number of the EasyAR SDK used in your application
• A description of the environment where the problem occurred (indoor/outdoor, lighting, space size)
• Mega applications need to additionally provide positioning library information, which can be exported in the Unity tool
• CRS cloud recognition applications need to additionally provide information about the cloud recognition library
Tip

Example: "Using EasyAR Sense Unity Plugin 4000.0.1 on Apple Vision Pro (visionOS 26), navigating in an indoor mall, the navigation path suddenly went wrong at a certain position. The EIF file has been recorded: avp_wrong_path_20251218.mkveif, with a screen recording, environmental photos, and positioning library information attached: MegaStudio_ServiceInfo_myaccount_2025-12-18_10-33-26.json."

By providing the above complete information package, you will significantly accelerate the problem analysis and repair process. Thank you for your cooperation!