---
id: matrice-analytics
version: "0.1.458"
license: LicenseRef-Proprietary
license_treatment: unclear
maintenance: active
---

# matrice-analytics — Post-processing analytics for Matrice.ai inference pipelines

License: unclear · Maintenance: active · Downloads: 2.2M/mo

## What it is and what it does

matrice-analytics is a post-processing system for the Matrice Python SDK that transforms raw inference results into structured analytics. It wraps numpy and scipy to provide standardized processing pipelines for two main use cases: people counting (with zone analysis, occupancy tracking, and alerts) and customer service analytics (staff utilization, customer-staff interactions, queue insights). All operations return ProcessingResult objects with status, metrics, insights, and warnings.

The package uses a registry pattern with type-safe dataclass configurations that support JSON/YAML file loading. It's designed for developers building analytics on top of computer vision inference—typical workflows involve loading raw detections, applying a use case configuration, and extracting business metrics. The system includes error handling that returns structured results even on partial failures, plus automatic insight generation and performance statistics.

Use it for:

- Count people in zones (entrance, checkout areas) with occupancy alerts and temporal trends for retail analytics
- Analyze staff utilization and customer-staff interactions to measure service quality and queue efficiency
- Track unique individuals across frames to measure dwell time and movement patterns in defined areas
- Generate business intelligence metrics from detection results without writing custom post-processing logic
- Load and apply pre-configured analytics pipelines from JSON/YAML files across multiple inference runs

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides post-processing and analytics for inference pipeline results, with configurable use cases for people counting and customer service analysis using numpy and scipy.

Yes, with conditions. The package is actively maintained, has low install friction, and solves a real problem for developers building analytics on inference results. However, the proprietary license is unclear—verify licensing terms before use. No known security vulnerabilities. Best suited for projects already using the Matrice SDK or similar inference pipelines where standardized post-processing is valuable.

## Install

pip install matrice-analytics
uv add matrice-analytics
poetry add matrice-analytics

## Installing matrice-analytics

Before you install: Low install friction with a pure-Python wheel and only numpy and scipy as runtime dependencies. Active maintenance with a recent release (3 days old as of the fact sheet date), supporting Python 3.8 through 3.12.

License in practice: Licensed as proprietary (LicenseRef-Proprietary) with unclear treatment. Verify licensing terms and restrictions before integrating into commercial or open-source projects.

Quickstart:

pip install matrice-analytics

from matrice_analytics.post_processing import PostProcessor

processor = PostProcessor()
result = processor.process_simple(
    raw_results,
    usecase="people_counting",
    confidence_threshold=0.5
)
print(result.summary)

Verify before relying:

- Whether proprietary license permits use in commercial applications or requires licensing agreement
- Actual performance characteristics and scalability limits for large inference datasets
- Whether zone configuration and tracking features work reliably across different camera angles and environments

## Package facts

- License: LicenseRef-Proprietary (unclear)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 2.2M/month (top 5,000 on PyPI)
- Known vulnerabilities: none known

## Tags

inference post-processing analytics, people counting detection, customer service metrics, zone-based occupancy analysis, detection result processing, tracking and counting, business intelligence from video, inference-analytics, computer-vision, post-processing

[View on SkillFed](https://skillfed.io/packages/matrice-analytics) · [View on PyPI](https://pypi.org/project/matrice-analytics/)