63 lines
1.4 KiB
Python
63 lines
1.4 KiB
Python
# -*- coding: utf-8 -*-
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"""
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Created on Thu Nov 22 14:16:46 2018
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@author: pivatom
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"""
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import numpy as np
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import cv2
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img = cv2.imread('H:\car\GestureRecognition\IMG_0818.png', 1)
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# Downscale the image
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img = cv2.resize(img, None, fx=0.1, fy=0.1, interpolation = cv2.INTER_AREA)
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img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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img_gray[img_gray[:,:] > 90] = 255
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img_gray[img_gray[:,:] < 90] = 0
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# Threshold to binary.
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ret,img_thresh = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY)
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# Doesn't take too long.
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k = np.sum(img_thresh) / 255
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x_ind = np.indices(img_thresh.shape[1])
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coords = np.zeros(img_thresh.shape)
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# generate individual coordinates for x then transpose the matrix o
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#
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# First sum x coordinates.
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#xb = int(img_ind[img_thresh == 255].sum(axis=1).sum()/k)
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#print(xb)
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# Then sum y coordinates
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#yb = int(img_ind[img_thresh == 255].sum(axis=0).sum()/k)
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#print(yb)
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x,y,k,xb,yb = 0,0,0,0,0
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# this is inherently slow...like very very slow...
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for pix in img_thresh:
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for j in pix:
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if j == 255:
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k += 1
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xb += x
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yb += y
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x += 1
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y += 1
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x = 0
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centre = (int(xb/k), int(yb/k))
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cv2.rectangle(img_thresh, centre, (centre[0] + 20, centre[1] + 20), (0,0,255), 3)
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cv2.circle(img_thresh, centre, 140, (0,0,0), 3)
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# Now need to trace around the circle to figure out where the fingers are.
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cv2.imshow("Binary-cot-out", img_thresh)
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cv2.waitKey(0)
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cv2.destroyAllWindows()
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