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/cts/apps/CameraITS/tests/scene3/
Dtest_3a_consistency.py19 import numpy as np namespace
55 assert np.isclose(np.amax(iso_exps), np.amin(iso_exps), ISO_EXP_TOL)
56 assert np.isclose(np.amax(g_gains), np.amin(g_gains), GGAIN_TOL)
57 assert np.isclose(np.amax(fds), np.amin(fds), FD_TOL)
59 assert not np.isnan(g)
61 assert not np.isnan(x)
Dtest_flip_mirror.py23 import numpy as np namespace
65 patch = its.cv2image.scale_img(patch.astype(np.uint8), chart.scale)
68 assert np.max(patch)-np.min(patch) > 255/8
72 its.image.write_image(template[:, :, np.newaxis]/255.0,
76 its.image.write_image(patch[:, :, np.newaxis]/255.0,
92 comp_chart = np.flipud(patch)
94 comp_chart = np.fliplr(patch)
96 comp_chart = np.flipud(np.fliplr(patch))
107 CHART_ORIENTATIONS[np.argmax(opts)])
Dtest_lens_movement_reporting.py22 import numpy as np namespace
128 diffs = np.gradient(times)
129 assert np.isclose(np.amax(diffs)-np.amax(diffs), 0, atol=FRAME_TIME_TOL)
149 assert np.isclose(min_loc, max_loc, rtol=POSITION_TOL)
154 assert np.isclose(min_sharp, max_sharp, rtol=SHARPNESS_TOL)
158 assert np.isclose(d_af_fd[first_key]['loc'], d_af_fd[first_key]['fd'],
165 assert np.isclose(min_loc, max_loc, rtol=POSITION_TOL)
170 assert np.isclose(min_sharp, max_sharp, rtol=SHARPNESS_TOL)
173 assert np.isclose(d_min_fd[NUM_IMGS*2-1]['loc'],
Dtest_lens_position.py22 import numpy as np namespace
59 fds_f = np.arange(hyperfocal, min_fd, (min_fd-hyperfocal)/(NUM_STEPS-1))
60 fds_f = np.append(fds_f, min_fd)
160 assert np.isclose(d_stat[i]['loc'], d_stat[i]['fd'],
162 assert np.isclose(d_stat[i]['loc'], d_stat[j]['loc'],
164 assert np.isclose(d_stat[i]['sharpness'], d_stat[j]['sharpness'],
169 diffs = np.gradient(times)
170 assert np.isclose(np.amin(diffs), np.amax(diffs), atol=FRAME_TIME_TOL)
176 assert np.isclose(d_stat[i]['loc'], d_move[i]['loc'],
188 assert np.isclose(
/cts/apps/CameraITS/tests/scene2_a/
Dtest_effects.py20 import numpy as np namespace
71 y_min, y_max = np.amin(y)*YUV_MAX, np.amax(y)*YUV_MAX
77 u_min, u_max = np.amin(u)*YUV_MAX, np.amax(u)*YUV_MAX
78 v_min, v_max = np.amin(v)*YUV_MAX, np.amax(v)*YUV_MAX
89 u_min, u_max = np.amin(u)*YUV_MAX, np.amax(u)*YUV_MAX
90 v_min, v_max = np.amin(v)*YUV_MAX, np.amax(v)*YUV_MAX
Dtest_jpeg_quality.py26 import numpy as np namespace
83 jpeg = np.concatenate((jpeg[0:i], jpeg[length:]), axis=None)
147 luma = np.array(jpeg[luma_start:luma_start+dqt_size])
148 chroma = np.array(jpeg[chroma_start:chroma_start+dqt_size])
149 lumas.append(np.mean(luma))
150 chromas.append(np.mean(chroma))
160 matrix = np.array(jpeg[start:start+dqt_size])
162 chromas.append(np.mean(matrix))
167 lumas.append(np.mean(matrix))
240 lumas = np.array(lumas)
[all …]
/cts/apps/CameraITS/tests/scene0/
Dtest_test_patterns.py21 import numpy as np namespace
48 var_max = max(np.amax(r_tile), np.amax(gr_tile), np.amax(gb_tile),
49 np.amax(b_tile))
50 var_min = min(np.amin(r_tile), np.amin(gr_tile), np.amin(gb_tile),
51 np.amin(b_tile))
55 return np.isclose(var_max, var_min, atol=CH_TOL)
77 img = np.fliplr(img)
81 color_match.append(np.allclose(its.image.compute_image_means(tile),
Dtest_tonemap_curve.py21 import numpy as np namespace
71 if np.allclose(COLOR_CHECKER[color], raw_means, atol=RAW_TOL):
96 raw_means = np.array(its.image.compute_image_means(raw_patch))
97 raw_vars = np.array(its.image.compute_image_variances(raw_patch))
98 yuv_means = np.array(its.image.compute_image_means(yuv_patch))
100 yuv_vars = np.array(its.image.compute_image_variances(yuv_patch))
101 if not np.allclose(raw_means, yuv_means, atol=RGB_MEAN_TOL):
103 str(raw_means), str(np.round(yuv_means, 3)), RGB_MEAN_TOL))
104 if not np.allclose(raw_vars, yuv_vars, atol=RGB_VAR_TOL):
Dtest_vibration_restriction.py23 import numpy as np namespace
69 var_w_vibration = np.var(magnitudes)
76 var_wo_vibration = np.var(magnitudes)
90 var_w_vibration_restricted = np.var(magnitudes)
/cts/apps/CameraITS/tests/scene4/
Dtest_multi_camera_alignment.py27 import numpy as np namespace
36 TRANS_REF_MATRIX = np.array([0, 0, 0])
69 np.isclose(chart_distance, its.cv2image.CHART_DISTANCE_RFOV, rtol=0.1)):
72 np.isclose(chart_distance, its.cv2image.CHART_DISTANCE_WFOV, rtol=0.1)):
199 k_x1 = np.dot(k[0, :], r[:, 0])
200 k_x2 = np.dot(k[0, :], r[:, 1])
201 k_x3 = z_w * np.dot(k[0, :], r[:, 2]) + np.dot(k[0, :], t)
202 k_y1 = np.dot(k[1, :], r[:, 0])
203 k_y2 = np.dot(k[1, :], r[:, 1])
204 k_y3 = z_w * np.dot(k[1, :], r[:, 2]) + np.dot(k[1, :], t)
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Dtest_aspect_ratio_and_crop.py23 import numpy as np namespace
85 if np.isclose(float(w)/h, match_ar, atol=AR_DIFF_ATOL):
153 ical = np.array(props["android.lens.intrinsicCalibration"])
167 k = np.array([[ical[0], ical[4], ical[2]],
173 assert np.isclose(fd_w_pix, ical[0], rtol=0.20), e_msg
176 assert np.isclose(fd_h_pix, ical[1], rtol=0.20), e_msg
184 opencv_dist = np.array([rad_dist[0], rad_dist[1],
255 circle_area = math.pi * math.pow(np.mean([circle_w, circle_h])/2.0, 2)
281 _, img_bw = cv2.threshold(np.uint8(img_gray), 0, 255,
595 if chk_enabled and not np.isclose(fov_percent, chk_percent,
/cts/suite/audio_quality/test_description/processing/
Dcalc_thd.py17 import numpy as np namespace
25 fftData = abs(fft.fft(data * np.hanning(len(data))))
31 np.argmax(fftData[baseI - iMargain /2: baseI + iMargain/2])
32 peakLoc = np.argmax(fftData[:fftLen])
53 index = np.linspace(0.0, samples, num=samples, endpoint=False)
55 multiplier = 2.0 * np.pi * signalFrequency / float(samplingRate)
56 data = np.sin(index * multiplier)
Dcalc_delay.py17 import numpy as np namespace
29 return np.dot(data0[n:N+n], data1reversed)
57 return np.argmax(result)
68 index = np.linspace(0.0, samples, num=samples, endpoint=False)
70 multiplier = 2.0 * np.pi * signalFrequency / float(samplingRate)
71 data0 = np.sin(index * multiplier)
Dgen_random.py18 import numpy as np namespace
32 result = np.zeros(samples * 2 if stereo else samples, dtype=np.int16)
33 randomSignal = np.random.normal(scale = peakAmpl * 2 / 3, size=samples)
Dexample.py18 import numpy as np namespace
45 stereo = stereoInt.astype(np.int16)
48 mono = monoInt.astype(np.int16)
Dcheck_spectrum_playback.py18 import numpy as np namespace
54 spectrum = np.sqrt(abs(Phh[iLow:iHigh]))
55 spectrumMean = np.mean(spectrum)
63 spectrumResult = np.zeros(len(spectrum), dtype=np.int16)
Dcheck_spectrum.py18 import numpy as np namespace
59 amplitudeRatio = np.sqrt(abs(Pdd[iLow:iHigh]/Phh[iLow:iHigh]))
60 ratioMean = np.mean(amplitudeRatio)
68 RatioResult = np.zeros(len(amplitudeRatio), dtype=np.int16)
76 monoData = np.zeros(n)
/cts/apps/CameraITS/tests/scene1_1/
Dtest_ae_af.py19 import numpy as np namespace
59 assert not np.isnan(g)
62 assert not np.isnan(x)
64 assert np.isclose(gains[2], GREEN_GAIN, GREEN_GAIN_TOL)
Dtest_3a.py18 import numpy as np namespace
41 assert not np.isnan(g)
44 assert not np.isnan(x)
/cts/apps/CameraITS/tools/
Ddng_noise_model.py26 import numpy as np namespace
138 means_p = np.asarray(means_p).flatten()
139 vars_p = np.asarray(vars_p).flatten()
196 sens = np.asarray([e[0] for e in measured_models[pidx]])
197 sens_sq = np.square(sens)
200 gains = np.asarray([s[0] for s in samples[pidx]])
201 means = np.asarray([s[1] for s in samples[pidx]])
202 vars_ = np.asarray([s[2] for s in samples[pidx]])
210 digital_gains = np.maximum(gains/sens_max_analog, 1)
211 assert np.all(digital_gains == 1)
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Dload_scene.py22 import numpy as np namespace
55 if np.isclose(chart_scaling, its.cv2image.SCALE_TELE_IN_WFOV_BOX, atol=0.01):
58 elif np.isclose(chart_scaling, its.cv2image.SCALE_RFOV_IN_WFOV_BOX, atol=0.01):
/cts/apps/CameraITS/tests/scene6/
Dtest_zoom.py25 import numpy as np namespace
90 _, img_bw = cv2.threshold(np.uint8(gray), 0, 255,
171 z_list = np.arange(z_min, z_max, float(z_max-z_min)/(NUM_STEPS-1))
172 z_list = np.append(z_list, z_max)
184 img = img.astype(np.uint8)
221 assert np.isclose(z_ratio, radius_ratio, rtol=RADIUS_RTOL), msg
235 assert np.isclose(offset_rel, 1.0, rtol=OFFSET_RTOL), msg
/cts/apps/CameraITS/tests/rolling_shutter_skew/
Dtest_rolling_shutter_skew.py20 import numpy as np namespace
319 np_cluster = np.array([[c.x, c.y] for c in largest_cluster])
369 img = img.astype(np.uint8)
382 kernel = np.ones((3, 3), np.uint8)
416 self.x = int(np.mean(contour[:, 0, 0]))
417 self.y = int(np.mean(contour[:, 0, 1]))
419 x_r = (np.max(contour[:, 0, 0]) - np.min(contour[:, 0, 0])) / 2.0
420 y_r = (np.max(contour[:, 0, 1]) - np.min(contour[:, 0, 1])) / 2.0
570 points = np.array([[x, y], [x + w, y], [x + w, y + h], [x, y + h]],
571 np.int32)
/cts/suite/audio_quality/test_description/conf/
Dcheck_conf.py18 import numpy as np namespace
25 a = np.array([1,2,3])
/cts/apps/CameraITS/tests/scene2_b/
Dtest_auto_per_frame_control.py24 import numpy as np namespace
50 diff = list((np.array(lsc[idx]) - np.array(lsc[idx-1])) /
51 np.array(lsc[idx-1]))
87 return (np.allclose(awb_gains_0, awb_gains_1, rtol=0.01) and
88 ccm_0 == ccm_1 and np.isclose(fd_0, fd_1, rtol=0.01))
167 awb_ccm = np.array(its.objects.rational_to_float(frame['ccm'])).reshape(3, 3)

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