megadetector

Name: megadetector
Availability: InStock
Author: cwinkelmann

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

Ready to run

npx skills add https://github.com/cwinkelmann/usde-innovations-applications-forest-it --skill megadetector

💬 Prompt for ChatGPT / Claude Chat▼

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.