1# Copyright 2019 The Android Open Source Project
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7#      http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14"""Verifies camera will produce full black & full white images."""
15
16
17import logging
18import os.path
19import matplotlib
20from matplotlib import pylab
21
22
23from mobly import test_runner
24import numpy as np
25
26import its_base_test
27import camera_properties_utils
28import capture_request_utils
29import image_processing_utils
30import its_session_utils
31
32CH_FULL_SCALE = 255
33CH_THRESH_BLACK = 6
34CH_THRESH_WHITE = CH_FULL_SCALE - 6
35CH_TOL_WHITE = 2
36COLOR_PLANES = ['R', 'G', 'B']
37NAME = os.path.splitext(os.path.basename(__file__))[0]
38PATCH_H = 0.1
39PATCH_W = 0.1
40PATCH_X = 0.45
41PATCH_Y = 0.45
42VGA_WIDTH, VGA_HEIGHT = 640, 480
43
44
45def do_img_capture(cam, s, e, fmt, latency, cap_name, log_path):
46  """Do the image captures with the defined parameters.
47
48  Args:
49    cam: its_session open for camera
50    s: sensitivity for request
51    e: exposure in ns for request
52    fmt: format of request
53    latency: number of frames for sync latency of request
54    cap_name: string to define the capture
55    log_path: path for plot directory
56
57  Returns:
58    means values of center patch from capture
59  """
60
61  req = capture_request_utils.manual_capture_request(s, e)
62  cap = its_session_utils.do_capture_with_latency(cam, req, latency, fmt)
63  img = image_processing_utils.convert_capture_to_rgb_image(cap)
64  image_processing_utils.write_image(
65      img, '%s_%s.jpg' % (os.path.join(log_path, NAME), cap_name))
66  patch = image_processing_utils.get_image_patch(
67      img, PATCH_X, PATCH_Y, PATCH_W, PATCH_H)
68  means = image_processing_utils.compute_image_means(patch)
69  means = [m * CH_FULL_SCALE for m in means]
70  logging.debug('%s pixel means: %s', cap_name, str(means))
71  r_exp = cap['metadata']['android.sensor.exposureTime']
72  r_iso = cap['metadata']['android.sensor.sensitivity']
73  logging.debug('%s shot write values: sens = %d, exp time = %.4fms',
74                cap_name, s, (e / 1000000.0))
75  logging.debug('%s shot read values: sens = %d, exp time = %.4fms',
76                cap_name, r_iso, (r_exp / 1000000.0))
77  return means
78
79
80class BlackWhiteTest(its_base_test.ItsBaseTest):
81  """Test that device will prodoce full black + white images.
82  """
83
84  def test_black_white(self):
85    r_means = []
86    g_means = []
87    b_means = []
88
89    with its_session_utils.ItsSession(
90        device_id=self.dut.serial,
91        camera_id=self.camera_id,
92        hidden_physical_id=self.hidden_physical_id) as cam:
93      props = cam.get_camera_properties()
94      props = cam.override_with_hidden_physical_camera_props(props)
95
96      # Check SKIP conditions
97      camera_properties_utils.skip_unless(
98          camera_properties_utils.manual_sensor(props))
99
100      # Load chart for scene
101      its_session_utils.load_scene(
102          cam, props, self.scene, self.tablet, self.chart_distance)
103
104      # Initialize params for requests
105      latency = camera_properties_utils.sync_latency(props)
106      fmt = {'format': 'yuv', 'width': VGA_WIDTH, 'height': VGA_HEIGHT}
107      expt_range = props['android.sensor.info.exposureTimeRange']
108      sens_range = props['android.sensor.info.sensitivityRange']
109      log_path = self.log_path
110
111      # Take shot with very low ISO and exp time: expect it to be black
112      s = sens_range[0]
113      e = expt_range[0]
114      black_means = do_img_capture(cam, s, e, fmt, latency, 'black', log_path)
115      r_means.append(black_means[0])
116      g_means.append(black_means[1])
117      b_means.append(black_means[2])
118
119      # Take shot with very high ISO and exp time: expect it to be white.
120      s = sens_range[1]
121      e = expt_range[1]
122      white_means = do_img_capture(cam, s, e, fmt, latency, 'white', log_path)
123      r_means.append(white_means[0])
124      g_means.append(white_means[1])
125      b_means.append(white_means[2])
126
127      # Draw plot
128      pylab.title('test_black_white')
129      pylab.plot([0, 1], r_means, '-ro')
130      pylab.plot([0, 1], g_means, '-go')
131      pylab.plot([0, 1], b_means, '-bo')
132      pylab.xlabel('Capture Number')
133      pylab.ylabel('Output Values [0:255]')
134      pylab.ylim([0, 255])
135      matplotlib.pyplot.savefig('%s_plot_means.png' % (
136          os.path.join(log_path, NAME)))
137
138      # Assert blacks below CH_THRESH_BLACK
139      for ch, mean in enumerate(black_means):
140        e_msg = '%s black: %.1f, THRESH: %.f' % (
141            COLOR_PLANES[ch], mean, CH_THRESH_BLACK)
142        assert mean < CH_THRESH_BLACK, e_msg
143
144      # Assert whites above CH_THRESH_WHITE
145      for ch, mean in enumerate(white_means):
146        e_msg = '%s white: %.1f, THRESH: %.f' % (
147            COLOR_PLANES[ch], mean, CH_THRESH_WHITE)
148        assert mean > CH_THRESH_WHITE, e_msg
149
150      # Assert channels saturate evenly (was test_channel_saturation)
151      e_msg = 'ch saturation not equal! RGB: %s, ATOL: %.f' % (
152          str(white_means), CH_TOL_WHITE)
153      assert np.isclose(
154          np.amin(white_means), np.amax(white_means), atol=CH_TOL_WHITE), e_msg
155
156if __name__ == '__main__':
157  test_runner.main()
158
159