: Include information from the MMDeploy result package, such as the backend model (ONNX/TorchScript) and deployment environment.
In C/C++ development, -M and -MM are flags used with GCC to generate dependency files ( .d files). :
In enterprise environments, reports are often "bundled" into ZIP files for bulk downloading or deployment. How to Use MMDetection | Train RTMDet on a Custom Dataset MF-MM.zip
To develop a report for the file, you need to first clarify the context of the file. Based on common technical uses of these abbreviations, this file likely pertains to one of the following scenarios: 1. Computer Vision & Machine Learning (OpenMMLab)
: Use the output of gcc -MM to list all header files associated with your source code. : Include information from the MMDeploy result package,
: Report the model's performance (mAP, FPS) on the custom dataset.
: List the backbone, neck, and detector combinations used in the report. 2. Software Development (GCC / Compilation) How to Use MMDetection | Train RTMDet on
: Include a summary of the compilation process and any missing module errors. 3. Business Systems (Dynamics 365 / BI Publisher)