photo-import-setup

Automate Metashape MCP project initialization with photo import, GPS, sensors, and masks.

31|4|Updated Feb 21, 2026
One-click install
npx skills add https://github.com/jenkinsm13/metashape-mcp --skill photo-import-setup
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: photo-import-setup
Source: https://github.com/jenkinsm13/metashape-mcp/tree/main/skills/photo-import-setup
Command: npx skills add https://github.com/jenkinsm13/metashape-mcp --skill photo-import-setup

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates Metashape MCP project initialization including create/open, photo import, GPS loading, sensor configuration, and mask handling to prepare data for alignment.

Core Features & Use Cases

  • Create or open a Metashape project and import photos in bulk
  • Load GPS references and configure sensor settings (fisheye, rolling shutter, multi-camera rigs)
  • Import EXR alpha masks and verify camera metadata
  • Analyze image quality and flag/disable low-quality frames to protect alignment
  • Prepare the workspace for subsequent alignment steps (match_photos, align_cameras)

Quick Start

Create a new Metashape MCP project, import your first batch of photos with GPS data, and apply sensor configuration to get the project ready for alignment.

Frequently Asked Questions about photo-import-setup

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up a Metashape project from raw photos?

To set up a Metashape project, you need to automate project initialization by importing photos, loading GPS references, configuring sensors, and handling masks to prepare an alignment-ready workspace.

Can I configure fisheye and rolling shutter sensors in Metashape MCP?

Yes, Metashape MCP sensor configuration supports fisheye lenses, rolling shutter correction, and multi-camera rigs to accurately calibrate your imported photos for photogrammetry alignment.

How do I import GPS references and EXR alpha masks into Metashape?

You import GPS references and EXR alpha masks by loading them into your Metashape project during initialization, verifying camera metadata to ensure proper reference accuracy and masking for image processing.

What is the best way to handle low-quality frames before photogrammetry alignment?

The best way to handle low-quality frames is to analyze image quality during project setup, flagging or disabling poor photos to protect the subsequent match_photos and align_cameras steps.

Does this Metashape project setup work for aerial and close-range capture scenarios?

Yes, this project setup supports new projects or additions across aerial, close-range, and vehicle-mounted capture scenarios, applying the necessary sensor configuration and GPS references for each environment.

Why is setting reference accuracy and GPU usage important for Metashape photogrammetry?

Setting reference accuracy and configuring GPU usage optimizes your Metashape workspace performance, ensuring the imported photos and GPS data process efficiently for accurate camera alignment.