157 lines
6.2 KiB
Python
157 lines
6.2 KiB
Python
import cv2
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import numpy as np
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datadir = "log"
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logid = "2"
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log = "/home/shurik/SmartBed/src/%s/sb_%s.log" % (datadir, logid)
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axels4graph=[4, 7, 14, 37, 18]
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maxaxels4graphcnt = 4
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axels4graphcnt = min(maxaxels4graphcnt, len(axels4graph))
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#print(axels4graphcnt)
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scale = 5 # увеличение сигнала на графике
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log_lines = 15
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axel_cnt = 39 # количество акселерометров
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steps = 10 # количество измерений в одной строке
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pdCnt = 39 # кол-во датчиков давления
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data_delta = 1 # пропускаем первое значение - таймер
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pd_delta = steps * axel_cnt * 3 + data_delta
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input_frm_rates = 17
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log_recs_delta = 1.5 # интервал между записями в логе
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pd = []
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ax = [[[],[],[]] for n in range(axel_cnt)]
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times = []
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cc=0
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# read data from system pipe
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from subprocess import Popen, PIPE
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databuf = Popen(["tail", "-n%i" % log_lines, log], stdout=PIPE, encoding='utf-8').communicate()[0]
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#print(log)
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#print("databuf:\n", databuf)
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lines = [line.rstrip() for line in databuf.split("\n")]
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for l in lines:
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if len(l) <=1 :
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break
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times.append(l.split("\t")[0])
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args = l.split("\t")[1].split(",")
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#pd.append([int(args[pd_delta]), int(args[pd_delta+1]), int(args[pd_delta+2]), int(args[pd_delta+3]), int(args[pd_delta+4])])
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for sn in range(steps):
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dlt = sn * 3 * axel_cnt
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for i in range(axel_cnt):
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# если уберут первое значение (метку таймера), то прибавку надо начинать не с 1, а с 0
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ax[i][0].append(int(args[dlt + i*3+1]) if int(args[dlt + i*3+1]) < 32768 else int(args[dlt + i*3+1]) - 65536)
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ax[i][1].append(int(args[dlt + i*3+2]) if int(args[dlt + i*3+2]) < 32768 else int(args[dlt + i*3+2]) - 65536)
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ax[i][2].append(int(args[dlt + i*3+3])-280 if int(args[dlt + i*3+3]) < 32768 else int(args[dlt + i*3+3]) - 65536)
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cc+=1
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#if cc == 2:
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# print(ax)
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ax_shape = np.shape(ax)
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axMax = [[0, 0, 0] for n in range(axel_cnt)]
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axMin = [[0, 0, 0] for n in range(axel_cnt)]
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deltaMax = 0
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for ai in range(axel_cnt):
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for i in range(3):
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axMax[ai][i] = max(ax[ai][i])
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axMin[ai][i] = min(ax[ai][i])
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if axMax[ai][i] == axMin[ai][i]:
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axMax[ai][i] += 1
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deltaMax = (axMax[ai][i] - axMin[ai][i]) if (axMax[ai][i] - axMin[ai][i]) > deltaMax else deltaMax
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a1,a2,glen = np.shape(ax)
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imH, imW = [1080, 1920]
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image_shape = (imH, imW, 3)
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image = np.zeros(image_shape, dtype=np.uint8)
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gpoints = ax_shape[2]
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gphalf = gpoints / 2
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gdelta = 20 # смещение графика от левого/правого края
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hStep = (imH - 10) / (4 / 2) - 10
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wStep = (imW - gdelta*2) / gpoints /2
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pdHStep = (imH - 40) / pdCnt
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hpix = 2 # int(65000 / hStep) # вес одного вертикального пикселя
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isClosed = False
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c0 = (255, 0, 0)
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c1 = (0, 255, 0)
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c2 = (0, 0, 255)
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thickness = 2
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vline = [[imW/2, 20], [imW/2, imH-20]]
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vline = np.array(vline, np.int32).reshape((-1, 1, 2))
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hline = [[20, imH/2], [imW-20, imH/2]]
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hline = np.array(hline, np.int32).reshape((-1, 1, 2))
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radius = 20
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color = [(0, 0, 225), (225, 225, 255)]
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aiH = [1, 1, 0, 0]
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aiW = [0, 1, 0, 1]
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cnt = 0
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fc = 0
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pdcnt = 0
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ret_val = True
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printflag=True
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gstep = 5
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dsize = 20 # размер анализируемого на движение участка
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msize = 3 # meter size / интервал измерения от текущей точки назад
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body = ["nogi", "ruki", "telo"]
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for istep in range(1):
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image *= 0
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image -=1
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acnt = int(cnt / input_frm_rates * (steps / log_recs_delta) )
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pdcnt = int(acnt/10)
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dstart = acnt-dsize if acnt> dsize else 0
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mstart = acnt-msize if acnt> msize else 0
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gstart = 0 # int((acnt-gphalf) if (acnt>gphalf) else 0)
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gstop = glen #int((acnt+gphalf) if (acnt<(glen-gphalf)) else glen)
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chartlen = int(gstop - gstart)
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ldelta = int(gdelta) #int(gdelta if (gstart>0) else gdelta + (gphalf - acnt)*wStep)
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ax4ch = [[[],[],[]] for n in range(axels4graphcnt)]
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j=0
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for i in range(gstart, gstop):
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Wval = [int(ldelta + wStep*j) , int(imW/2+ldelta + wStep*j)]
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for ai in range(axels4graphcnt):
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#print(ai)
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ax4ch[ai][0].append([Wval[aiW[ai]], int((ax[axels4graph[ai]][0][i]*scale+80)/hpix + 10 + aiH[ai]*hStep+150)])
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ax4ch[ai][1].append([Wval[aiW[ai]], int((ax[axels4graph[ai]][1][i]*scale+80)/hpix + 10 + aiH[ai]*hStep+150)])
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ax4ch[ai][2].append([Wval[aiW[ai]], int((ax[axels4graph[ai]][2][i]*scale+80)/hpix + 10 + aiH[ai]*hStep+150)])
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j += 1
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for i in range(axels4graphcnt):
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ax4ch[i][0] = np.array(ax4ch[i][0], np.int32).reshape((-1, 1, 2))
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ax4ch[i][1] = np.array(ax4ch[i][1], np.int32).reshape((-1, 1, 2))
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ax4ch[i][2] = np.array(ax4ch[i][2], np.int32).reshape((-1, 1, 2))
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for i in range(axels4graphcnt):
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image = cv2.polylines(image, [ax4ch[i][0]], isClosed, c0, thickness)
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image = cv2.polylines(image, [ax4ch[i][1]], isClosed, c1, thickness)
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image = cv2.polylines(image, [ax4ch[i][2]], isClosed, c2, thickness)
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image = cv2.polylines(image, [vline], isClosed, (200, 200, 200), thickness)
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image = cv2.polylines(image, [hline], isClosed, (200, 200, 200), thickness)
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if acnt > 3 :
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pdsum = np.sum(pd[pdcnt])
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if pdsum < pdCnt :
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# считаем, что тело лежит на кровати, т.е. (pdsum < 5)
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inumax = 0
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imark = 0
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for iax in range(12):
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anum = int (iax / 3) # номер акселя
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aline = iax % 3 # три оси акселя
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imin, imax, imean = (np.min(ax[anum][aline][mstart:acnt]), np.max(ax[anum][aline][mstart:acnt]), int(np.mean(ax[anum][aline][dstart:acnt])))
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if abs(imax - imean) > sens or abs(imean - imin) > sens :
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inumax += 1
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imark |= (int(iax/6)+1)
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for i in range(axels4graphcnt):
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labH = int(50+imH*aiH[i]/2)
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labW = int(20+imW*aiW[i]/2)
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cv2.putText(image, "axel %i" % axels4graph[i], (labW, labH), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 2)
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imH, imW
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cv2.imwrite("4acsels_chart.png",image)
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