Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Direktori skill
Temukan skill yang dapat digunakan kembali untuk AI agents.
Setiap rekomendasi tetap terhubung dengan repositori, audit, dan jalur pemasangannya.
Hasil pencarian: ground-segmentation
Direktori bahasa InggrisStanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning. [ICLR 2026]
a machine learning image inpainting task that instinctively removes watermarks from image indistinguishable from the ground truth image
A reusable skill kit for AI agents to generate structurally precise and aesthetically standardized draw.io diagrams across major cloud platforms and BPMN, with declarative layout, stencils, and validation.
给纯文本 LLM agent 装上眼睛:图片问答、OCR、截图分析、视觉定位等一套视觉工具箱 + skill,并可无缝接入 Codex、Claude Code、OpenCode、Pi | Give text-only LLM agents vision: image Q&A, OCR, screenshot understanding, visual grounding, image-to-SVG - a vision toolkit & skill, with drop-in integration for Codex, Claude Code, OpenCode, Pi
Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds
Ground truth layer for humans and AI agents working together. Version control for knowledge.
Retentioneering: product analytics, data-driven CJM optimization, marketing analytics, web analytics, transaction analytics, graph visualization, process mining, and behavioral segmentation in Python. Predictive analytics over clickstream, AB tests, machine learning, and Markov Chain simulations.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications