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1# Copyright 2013 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 YUV & JPEG image captures have similar brightness."""
15
16
17import logging
18import os.path
19import matplotlib
20from matplotlib import pylab
21from mobly import test_runner
22
23import its_base_test
24import camera_properties_utils
25import capture_request_utils
26import image_processing_utils
27import its_session_utils
28import target_exposure_utils
29
30NAME = os.path.splitext(os.path.basename(__file__))[0]
31PATCH_H = 0.1  # center 10%
32PATCH_W = 0.1
33PATCH_X = 0.5 - PATCH_W/2
34PATCH_Y = 0.5 - PATCH_H/2
35THRESHOLD_MAX_RMS_DIFF = 0.03
36
37
38def do_capture_and_extract_rgb_means(req, cam, size, img_type, log_path, debug):
39  """Do capture and extra rgb_means of center patch.
40
41  Args:
42    req: capture request
43    cam: camera object
44    size: [width, height]
45    img_type: string of 'yuv' or 'jpeg'
46    log_path: location for saving image
47    debug: boolean to flag saving captured images
48
49  Returns:
50    center patch RGB means
51  """
52  out_surface = {'width': size[0], 'height': size[1], 'format': img_type}
53  cap = cam.do_capture(req, out_surface)
54  if img_type == 'jpg':
55    assert cap['format'] == 'jpeg'
56    img = image_processing_utils.decompress_jpeg_to_rgb_image(cap['data'])
57  else:
58    assert cap['format'] == img_type
59    img = image_processing_utils.convert_capture_to_rgb_image(cap)
60  assert cap['width'] == size[0]
61  assert cap['height'] == size[1]
62
63  if debug:
64    image_processing_utils.write_image(img, '%s_%s_w%d_h%d.jpg'%(
65        os.path.join(log_path, NAME), img_type, size[0], size[1]))
66  if img_type == 'jpg':
67    assert img.shape[0] == size[1]
68    assert img.shape[1] == size[0]
69    assert img.shape[2] == 3
70  patch = image_processing_utils.get_image_patch(
71      img, PATCH_X, PATCH_Y, PATCH_W, PATCH_H)
72  rgb = image_processing_utils.compute_image_means(patch)
73  logging.debug('Captured %s %dx%d rgb = %s',
74                img_type, cap['width'], cap['height'], str(rgb))
75  return rgb
76
77
78class YuvJpegAllTest(its_base_test.ItsBaseTest):
79  """Test reported sizes & fmts for YUV & JPEG caps return similar images."""
80
81  def test_yuv_jpeg_all(self):
82    logging.debug('Starting %s', NAME)
83    with its_session_utils.ItsSession(
84        device_id=self.dut.serial,
85        camera_id=self.camera_id,
86        hidden_physical_id=self.hidden_physical_id) as cam:
87      props = cam.get_camera_properties()
88      props = cam.override_with_hidden_physical_camera_props(props)
89      camera_properties_utils.skip_unless(
90          camera_properties_utils.compute_target_exposure(props) and
91          camera_properties_utils.per_frame_control(props))
92      log_path = self.log_path
93      debug = self.debug_mode
94
95      # Load chart for scene
96      its_session_utils.load_scene(
97          cam, props, self.scene, self.tablet, self.chart_distance)
98
99      # Use a manual request with a linear tonemap so that the YUV and JPEG
100      # should look the same (once converted by the image_processing_utils).
101      e, s = target_exposure_utils.get_target_exposure_combos(
102          log_path, cam)['midExposureTime']
103      req = capture_request_utils.manual_capture_request(s, e, 0.0, True, props)
104
105      rgbs = []
106      for size in capture_request_utils.get_available_output_sizes(
107          'yuv', props):
108        rgbs.append(do_capture_and_extract_rgb_means(
109            req, cam, size, 'yuv', log_path, debug))
110
111      for size in capture_request_utils.get_available_output_sizes(
112          'jpg', props):
113        rgbs.append(do_capture_and_extract_rgb_means(
114            req, cam, size, 'jpg', log_path, debug))
115
116      # Plot means vs format
117      pylab.figure(NAME)
118      pylab.title(NAME)
119      pylab.plot(range(len(rgbs)), [r[0] for r in rgbs], '-ro')
120      pylab.plot(range(len(rgbs)), [g[1] for g in rgbs], '-go')
121      pylab.plot(range(len(rgbs)), [b[2] for b in rgbs], '-bo')
122      pylab.ylim([0, 1])
123      pylab.xlabel('format number')
124      pylab.ylabel('RGB avg [0, 1]')
125      matplotlib.pyplot.savefig(
126          '%s_plot_means.png' % os.path.join(log_path, NAME))
127
128      # Assert all captured images are similar in RBG space
129      max_diff = 0
130      for rgb_i in rgbs[1:]:
131        rms_diff = image_processing_utils.compute_image_rms_difference(
132            rgbs[0], rgb_i)  # use first capture as reference
133        max_diff = max(max_diff, rms_diff)
134      msg = 'Max RMS difference: %.4f' % max_diff
135      logging.debug('%s', msg)
136      e_msg = msg + ' spec: %.3f' % THRESHOLD_MAX_RMS_DIFF
137      assert max_diff < THRESHOLD_MAX_RMS_DIFF, e_msg
138
139if __name__ == '__main__':
140  test_runner.main()
141