def __init__(self, src): self._src = src self._kinect = Kinect() self._body = BodyDetector() self._hand = HandDetector() self._contour = HandContourDetector() self._pose = PoseClassifier(MultiPoseClassifier(src))
def __init__(self, id, nsamples, dst): self._id = id self._nsamples = nsamples self._dst = dst self._kinect = Kinect() self._body = BodyDetector() self._hand = HandDetector() self._contour = HandContourDetector() self._feature = GaborDescriptors(4, 4)
def __init__(self, id, nsamples, dst): self._id = id self._nsamples = nsamples self._dst = dst self._kinect = Kinect() self._body = BodyDetector() self._hand = HandDetector() self._contour = HandContourDetector() self._fdesc = FourierDescriptors() self._train = []
def __init__(self): self._kinect = Kinect() self._body = BodyDetector() self._hand = HandDetector(HandOtsu()) self._contour = HandContourDetector() self._palm = PalmDetector()
#!/usr/bin/env python # -*- coding: utf-8 -*- import cv2 import numpy as np import config from kinect import Kinect from body import BodyDetector from hand import HandDetector, HandContourDetector from pose import PoseClassifier, OpenCloseClassifier, MultiPoseClassifier kinect = Kinect() body = BodyDetector() hand = HandDetector() contour = HandContourDetector() #pose = PoseClassifier(OpenCloseClassifier()) pose = PoseClassifier(MultiPoseClassifier()) for (depth, depth8, rgb) in kinect.get_data(): b = body.run(depth8) (h, _) = hand.run(b) #cv2.imshow('hand', h) (ccc, box, hc) = contour.run(h) if len(ccc) < 100: