pose_detection library

On-device pose detection and landmark estimation using TensorFlow Lite.

This library provides a Flutter plugin for real-time human pose detection using Google's MediaPipe BlazePose models. It detects persons in images and extracts 33 body landmarks (keypoints) for each detected person.

Quick Start:

import 'package:pose_detection/pose_detection.dart';

// One-step construction
final detector = await PoseDetector.create();

// Or two-step, if you need to configure between construction and init
final detector = PoseDetector();
await detector.initialize();

final poses = await detector.detect(imageBytes);
for (final pose in poses) {
  print('Person detected at ${pose.boundingBox}');
  if (pose.hasLandmarks) {
    final nose = pose.getLandmark(PoseLandmarkType.nose);
    print('Nose position: (${nose?.x}, ${nose?.y})');
  }
}

await detector.dispose();

Main Classes:

• PoseDetector: Main API for pose detection (background isolate on native; async browser runtime on web)
• Pose: Detected person with bounding box and optional 33 landmarks
• PoseLandmark: Single body keypoint with 3D coordinates and visibility
• PoseLandmarkType: Enum of 33 body parts (nose, shoulders, knees, etc.)
• BoundingBox: Axis-aligned rectangle for person location

Detection Modes:

• PoseMode.boxes: Fast detection returning only bounding boxes
• PoseMode.boxesAndLandmarks: Full pipeline with 33 landmarks per person

Model Variants:

• PoseLandmarkModel.lite: Fastest, good accuracy
• PoseLandmarkModel.full: Balanced speed/accuracy
• PoseLandmarkModel.heavy: Slowest, best accuracy (default)