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megadetector

Generate Python code for MegaDetector single-image, batch, and folder inferences.

2|Updated Mar 6, 2026
Search Tags:#python#pipeline#detection#batch-inference#computer-vision#wildlife#megadetector
One-click install
npx skills add https://github.com/cwinkelmann/usde-innovations-applications-forest-it --skill megadetector
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: megadetector
Source: https://github.com/cwinkelmann/usde-innovations-applications-forest-it/tree/main/.claude/skills/megadetector
Command: npx skills add https://github.com/cwinkelmann/usde-innovations-applications-forest-it --skill megadetector

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill provides a lightweight MegaDetector wrapper that generates working code for single-image, batch, and folder inferences on wildlife datasets.

Core Features & Use Cases

  • Deterministic inferences: load and run MegaDetector on images with a standard output format.
  • Batch & folder workflows: generate scripts that process many images or directories efficiently.
  • Detect-then-classify pipelines: crop detections and feed to a downstream classifier for species identification.

Quick Start

Install the skill and run the MegaDetector code agent to generate a ready-to-run script that processes a folder of camera-trap images.

Frequently Asked Questions about megadetector

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

FAQPage Schema
How do I run MegaDetector batch inference on a folder of wildlife camera trap images?▼

This skill generates working Python scripts that process entire directories of wildlife images efficiently, applying MegaDetector detection with configurable confidence thresholds and unified output formats.

What is a detect-then-classify pipeline for wildlife species identification?▼

A detect-then-classify pipeline crops wildlife detections from camera trap images and feeds them to a downstream classifier for species identification, merging results into unified output for analysis.

Can I use this MegaDetector wrapper with my existing Python computer vision environment?▼

Yes, this MegaDetector wrapper targets standard Python environments with the MegaDetector API, requiring no additional dependencies to generate inference scripts for wildlife datasets.

How do I crop MegaDetector detections and merge results for downstream analysis?▼

This skill demonstrates how to crop detected wildlife regions from images and merge outputs into a unified format, enabling seamless downstream analysis and integration with secondary classifiers.

What MegaDetector model variants and confidence thresholds should I use for wildlife detection?▼

This skill provides guidance on selecting MegaDetector model variants and confidence thresholds for wildlife datasets, ensuring deterministic inferences with standard output formats across batch workflows.

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