Merge branch 'devel-avarta-80-quick' of https://code.slightech.com:666/mynteye/mynt-eye-sdk-2 into devel-avarta-80-quick
This commit is contained in:
Kalman
commit
8d945fe042
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@ -97,10 +97,10 @@ class BinDataset(object):
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if What.imu in result:
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imu = result[What.imu]
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np.array([(
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imu.timestamp,
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imu.timestamp, imu.flag,
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imu.accel_x, imu.accel_y, imu.accel_z,
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imu.gyro_x, imu.gyro_y, imu.gyro_z
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)], dtype="f8, f8, f8, f8, f8, f8, f8").tofile(f_imu)
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)], dtype="f8, i4, f8, f8, f8, f8, f8, f8").tofile(f_imu)
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imu_count = imu_count + 1
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has_imu = True
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sys.stdout.write('\r img: {}, imu: {}'.format(img_count, imu_count))
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@ -130,7 +130,7 @@ class BinDataset(object):
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if self.has_imu:
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imus = np.memmap(self._binimu, dtype=[
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('t', 'f8'),
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('t', 'f8'), ('flag', 'i4'),
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('accel_x', 'f8'), ('accel_y', 'f8'), ('accel_z', 'f8'),
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('gyro_x', 'f8'), ('gyro_y', 'f8'), ('gyro_z', 'f8'),
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], mode='r')
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@ -145,92 +145,111 @@ class BinDataset(object):
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print(' img: {}, imu: {}'.format(period_img, period_imu))
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imgs_t_diff = np.diff(imgs['t'])
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imus_t_diff = np.diff(imus['t'])
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# imus_t_diff = np.diff(imus['t'])
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accel = imus[imus['flag'] == 1]
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accel_t_diff = np.diff(accel['t'])
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gyro = imus[imus['flag'] == 2]
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gyro_t_diff = np.diff(gyro['t'])
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print('\ncount')
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print(' imgs: {}, imus: {}, accel: {}, gyro: {}'.format(
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imgs.size, imus.size, accel.size, gyro.size))
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print('\ndiff count')
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print(' imgs: {}, imus: {}'.format(imgs['t'].size, imus['t'].size))
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print(' imgs_t_diff: {}, imus_t_diff: {}'
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.format(imgs_t_diff.size, imus_t_diff.size))
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print(' imgs_t_diff: {}, accel_t_diff: {}, gyro_t_diff: {}'.format(
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imgs_t_diff.size, accel_t_diff.size, gyro_t_diff.size))
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print('\ndiff where (factor={})'.format(args.factor))
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where = np.argwhere(imgs_t_diff > period_img * (1 + args.factor))
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print(' imgs where diff > {}*{} ({})'.format(period_img,
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1 + args.factor, where.size))
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for x in where:
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print(' {:8d}: {:.16f}'.format(x[0], imgs_t_diff[x][0]))
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where = np.argwhere(imgs_t_diff < period_img * (1 - args.factor))
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print(' imgs where diff < {}*{} ({})'.format(period_img,
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1 - args.factor, where.size))
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for x in where:
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print(' {:8d}: {:.16f}'.format(x[0], imgs_t_diff[x][0]))
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where = np.argwhere(imus_t_diff > period_imu * (1 + args.factor))
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print(' imus where diff > {}*{} ({})'.format(period_imu,
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1 + args.factor, where.size))
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for x in where:
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print(' {:8d}: {:.16f}'.format(x[0], imus_t_diff[x][0]))
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where = np.argwhere(imus_t_diff < period_imu * (1 - args.factor))
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print(' imus where diff < {}*{} ({})'.format(period_imu,
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1 - args.factor, where.size))
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for x in where:
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print(' {:8d}: {:.16f}'.format(x[0], imus_t_diff[x][0]))
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self._print_t_diff_where('imgs', imgs_t_diff, period_img, args.factor)
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# self._print_t_diff_where('imus', imus_t_diff, period_imu, args.factor)
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self._print_t_diff_where('accel', accel_t_diff, period_imu, args.factor)
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self._print_t_diff_where('gyro', gyro_t_diff, period_imu, args.factor)
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import pandas as pd
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bins = imgs['t']
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bins_n = imgs['t'].size
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bins = pd.Series(data=bins).drop_duplicates(keep='first')
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cats = pd.cut(imus['t'], bins)
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print('\nimage timestamp duplicates: {}'.format(bins_n - bins.size))
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self._plot(outdir, imgs_t_diff, imus_t_diff, cats.value_counts())
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def _cut_by_imgs_t(imus_t):
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cats = pd.cut(imus_t, bins)
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return cats.value_counts()
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def _plot(self, outdir, imgs_t_diff, imus_t_diff, imgs_t_imus):
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self._plot(
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outdir,
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imgs_t_diff,
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accel_t_diff,
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_cut_by_imgs_t(
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accel['t']),
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gyro_t_diff,
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_cut_by_imgs_t(
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gyro['t']))
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def _print_t_diff_where(self, name, t_diff, period, factor):
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import numpy as np
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where = np.argwhere(t_diff > period * (1 + factor))
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print(' {} where diff > {}*{} ({})'.format(
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name, period, 1 + factor, where.size))
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for x in where:
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print(' {:8d}: {:.16f}'.format(x[0], t_diff[x][0]))
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where = np.argwhere(t_diff < period * (1 - factor))
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print(' {} where diff < {}*{} ({})'.format(
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name, period, 1 - factor, where.size))
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for x in where:
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print(' {:8d}: {:.16f}'.format(x[0], t_diff[x][0]))
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def _plot(self, outdir, imgs_t_diff,
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accel_t_diff, accel_counts, gyro_t_diff, gyro_counts):
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import matplotlib.pyplot as plt
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import numpy as np
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fig_1 = plt.figure(1, [16, 6])
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fig_1 = plt.figure(1, [16, 12])
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fig_1.suptitle('Stamp Analytics')
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fig_1.subplots_adjust(
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left=0.1,
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right=0.95,
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top=0.85,
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bottom=0.15,
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wspace=0.4)
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wspace=0.4,
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hspace=0.4)
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ax_imgs_t_diff = fig_1.add_subplot(131)
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ax_imgs_t_diff = fig_1.add_subplot(231)
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ax_imgs_t_diff.set_title('Image Timestamp Diff')
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ax_imgs_t_diff.set_xlabel('diff index')
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ax_imgs_t_diff.set_ylabel('diff (s)')
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ax_imgs_t_diff.axis('auto')
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ax_imus_t_diff = fig_1.add_subplot(132)
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ax_imus_t_diff.set_title('Imu Timestamp Diff')
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ax_imgs_t_diff.set_xlim([0, imgs_t_diff.size])
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ax_imgs_t_diff.plot(imgs_t_diff)
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def _plot_imus(name, t_diff, counts, pos_offset=0):
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ax_imus_t_diff = fig_1.add_subplot(232 + pos_offset)
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ax_imus_t_diff.set_title('{} Timestamp Diff'.format(name))
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ax_imus_t_diff.set_xlabel('diff index')
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ax_imus_t_diff.set_ylabel('diff (s)')
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ax_imus_t_diff.axis('auto')
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ax_imgs_t_imus = fig_1.add_subplot(133)
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ax_imgs_t_imus.set_title('Imu Count Per Image Intervel')
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ax_imgs_t_imus.set_xlabel('intervel index')
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ax_imgs_t_imus.set_ylabel('imu count')
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ax_imgs_t_imus.axis('auto')
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ax_imus_t_diff.set_xlim([0, t_diff.size - 1])
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ax_imus_t_diff.plot(t_diff)
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ax_imgs_t_diff.set_xlim([0, imgs_t_diff.size])
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ax_imgs_t_diff.plot(imgs_t_diff)
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ax_imus_counts = fig_1.add_subplot(233 + pos_offset)
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ax_imus_counts.set_title('{} Count Per Image Intervel'.format(name))
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ax_imus_counts.set_xlabel('intervel index')
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ax_imus_counts.set_ylabel('imu count')
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ax_imus_counts.axis('auto')
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ax_imus_t_diff.set_xlim([0, imus_t_diff.size])
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ax_imus_t_diff.plot(imus_t_diff)
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# print(counts.values)
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# counts.plot(kind='line', ax=ax_imus_counts)
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data = counts.values
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ax_imus_counts.set_xlim([0, data.size])
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ax_imus_counts.set_ylim([np.min(data) - 1, np.max(data) + 1])
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ax_imus_counts.plot(data)
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# print(imgs_t_imus.values)
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# imgs_t_imus.plot(kind='line', ax=ax_imgs_t_imus)
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data = imgs_t_imus.values
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ax_imgs_t_imus.set_xlim([0, data.size])
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ax_imgs_t_imus.set_ylim([np.min(data) - 1, np.max(data) + 1])
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ax_imgs_t_imus.plot(data)
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_plot_imus('Accel', accel_t_diff, accel_counts)
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_plot_imus('Gyro', gyro_t_diff, gyro_counts, 3)
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if outdir:
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figpath = os.path.join(outdir, RESULT_FIGURE)
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@ -81,6 +81,7 @@ class IMU(Data):
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def __init__(self):
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super(IMU, self).__init__()
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self._flag = 0
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self._accel_x = 0
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self._accel_y = 0
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self._accel_z = 0
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@ -88,6 +89,14 @@ class IMU(Data):
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self._gyro_y = 0
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self._gyro_z = 0
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@property
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def flag(self):
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return self._flag
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@flag.setter
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def flag(self, flag):
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self._flag = flag
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@property
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def accel(self):
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return self._accel_x, self._accel_y, self._accel_z
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@ -381,6 +390,7 @@ class MYNTEYE(Dataset):
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values = [_.strip() for _ in line.split(',')]
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imu = IMU()
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imu.timestamp = float(values[fields['timestamp']]) * 0.000001
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imu.flag = values[fields['flag']]
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imu.accel_x = float(values[fields['accel_x']])
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imu.accel_y = float(values[fields['accel_y']])
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imu.accel_z = float(values[fields['accel_z']])
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