1# Copyright 2014 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
15# --------------------------------------------------------------------------- #
16# The Google Python style guide should be used for scripts:                   #
17# http://google-styleguide.googlecode.com/svn/trunk/pyguide.html              #
18# --------------------------------------------------------------------------- #
19
20# The ITS modules that are in the utils directory. To see formatted
21# docs, use the "pydoc" command:
22#
23# > pydoc image_processing_utils
24#
25import capture_request_utils
26import image_processing_utils
27import its_base_test
28import its_session_utils
29
30# Standard Python modules.
31import logging
32import os.path
33
34# Modules from the numpy, scipy, and matplotlib libraries. These are used for
35# the image processing code, and images are represented as numpy arrays.
36from matplotlib import pylab
37import numpy
38import matplotlib
39import matplotlib.pyplot
40
41# Module for Mobly
42from mobly import test_runner
43
44# A convention in each script is to use the filename (without the extension)
45# as the name of the test, when printing results to the screen or dumping files.
46_NAME = os.path.basename(__file__).split('.')[0]
47
48
49# Each script has a class definition
50class TutorialTest(its_base_test.ItsBaseTest):
51  """Test the validity of some metadata entries.
52
53  Looks at the capture results and at the camera characteristics objects.
54  Script uses a config.yml file in the CameraITS directory.
55  A sample config.yml file:
56    TestBeds:
57    - Name: TEST_BED_TUTORIAL
58      Controllers:
59          AndroidDevice:
60            - serial: 03281FDD40008Y
61              label: dut
62      TestParams:
63        camera: "1"
64        scene: "0"
65
66  A sample script call:
67    python tests/tutorial.py --config config.yml
68
69  """
70
71  def test_tutorial(self):
72    # Each script has a string description of what it does. This is the first
73    # entry inside the main function.
74    """Tutorial script to show how to use the ITS infrastructure."""
75
76    # The standard way to open a session with a connected camera device. This
77    # creates a cam object which encapsulates the session and which is active
78    # within the scope of the 'with' block; when the block exits, the camera
79    # session is closed. The device and camera are defined in the config.yml
80    # file.
81    with its_session_utils.ItsSession(
82        device_id=self.dut.serial,
83        camera_id=self.camera_id,
84        hidden_physical_id=self.hidden_physical_id) as cam:
85
86      # Append the log_path to store images in the proper location.
87      # Images will be stored in the test output folder:
88      # /tmp/logs/mobly/$TEST_BED_NAME/$DATE/TutorialTest
89      file_name = os.path.join(self.log_path, _NAME)
90
91      # Get the static properties of the camera device. Returns a Python
92      # associative array object; print it to the console.
93      props = cam.get_camera_properties()
94      logging.debug('props\n%s', str(props))
95
96      # Grab a YUV frame with manual exposure of sensitivity = 200, exposure
97      # duration = 50ms.
98      req = capture_request_utils.manual_capture_request(200, 50*1000*1000)
99      cap = cam.do_capture(req)
100
101      # Print the properties of the captured frame; width and height are
102      # integers, and the metadata is a Python associative array object.
103      # logging.info will be printed to screen & test_log.INFO
104      # logging.debug to test_log.DEBUG in /tmp/logs/mobly/... directory
105      logging.info('Captured image width: %d, height: %d',
106                   cap['width'], cap['height'])
107      logging.debug('metadata\n%s', str(cap['metadata']))
108
109      # The captured image is YUV420. Convert to RGB, and save as a file.
110      rgbimg = image_processing_utils.convert_capture_to_rgb_image(cap)
111      image_processing_utils.write_image(rgbimg, '%s_rgb_1.jpg' % file_name)
112
113      # Can also get the Y,U,V planes separately; save these to greyscale
114      # files.
115      yimg, uimg, vimg = image_processing_utils.convert_capture_to_planes(cap)
116      image_processing_utils.write_image(yimg, '%s_y_plane_1.jpg' % file_name)
117      image_processing_utils.write_image(uimg, '%s_u_plane_1.jpg' % file_name)
118      image_processing_utils.write_image(vimg, '%s_v_plane_1.jpg' % file_name)
119
120      # Run 3A on the device. In this case, just use the entire image as the
121      # 3A region, and run each of AWB,AE,AF. Can also change the region and
122      # specify independently for each of AE,AWB,AF whether it should run.
123      #
124      # NOTE: This may fail, if the camera isn't pointed at a reasonable
125      # target scene. If it fails, the script will end. The logcat messages
126      # can be inspected to see the status of 3A running on the device.
127      #
128      # If this keeps on failing, try also rebooting the device before
129      # running the test.
130      sens, exp, gains, xform, focus = cam.do_3a(get_results=True)
131      logging.info('AE: sensitivity %d, exposure %dms', sens, exp/1000000.0)
132      logging.info('AWB: gains %s', str(gains))
133      logging.info('AWB: transform %s', str(xform))
134      logging.info('AF: distance %.4f', focus)
135
136      # Grab a new manual frame, using the 3A values, and convert it to RGB
137      # and save it to a file too. Note that the 'req' object is just a
138      # Python dictionary that is pre-populated by the capture_request_utils
139      # functions (in this case a default manual capture), and the key/value
140      # pairs in the object can be used to set any field of the capture
141      # request. Here, the AWB gains and transform (CCM) are being used.
142      # Note that the CCM transform is in a rational format in capture
143      # requests, meaning it is an object with integer numerators and
144      # denominators. The 3A routine returns simple floats instead, however,
145      # so a conversion from float to rational must be performed.
146      req = capture_request_utils.manual_capture_request(sens, exp)
147      xform_rat = capture_request_utils.float_to_rational(xform)
148
149      req['android.colorCorrection.transform'] = xform_rat
150      req['android.colorCorrection.gains'] = gains
151      cap = cam.do_capture(req)
152      rgbimg = image_processing_utils.convert_capture_to_rgb_image(cap)
153      image_processing_utils.write_image(rgbimg, f'{file_name}_rgb_2.jpg')
154
155      # log the actual capture request object that was used.
156      logging.debug('req: %s', str(req))
157
158      # Images are numpy arrays. The dimensions are (h,w,3) when indexing,
159      # in the case of RGB images. Greyscale images are (h,w,1). Pixels are
160      # generally float32 values in the [0,1] range, however some of the
161      # helper functions in image_processing_utils deal with the packed YUV420
162      # and other formats of images that come from the device (and convert
163      # them to float32).
164      # Print the dimensions of the image, and the top-left pixel value,
165      # which is an array of 3 floats.
166      logging.info('RGB image dimensions: %s', str(rgbimg.shape))
167      logging.info('RGB image top-left pixel: %s', str(rgbimg[0, 0]))
168
169      # Grab a center tile from the image; this returns a new image. Save
170      # this tile image. In this case, the tile is the middle 10% x 10%
171      # rectangle.
172      tile = image_processing_utils.get_image_patch(
173          rgbimg, 0.45, 0.45, 0.1, 0.1)
174      image_processing_utils.write_image(tile, f'{file_name}_rgb_2_tile.jpg')
175
176      # Compute the mean values of the center tile image.
177      rgb_means = image_processing_utils.compute_image_means(tile)
178      logging.info('RGB means: %s', str(rgb_means))
179
180      # Apply a lookup table to the image, and save the new version. The LUT
181      # is basically a tonemap, and can be used to implement a gamma curve.
182      # In this case, the LUT is used to double the value of each pixel.
183      lut = numpy.array([2*i for i in range(65536)])
184      rgbimg_lut = image_processing_utils.apply_lut_to_image(rgbimg, lut)
185      image_processing_utils.write_image(
186          rgbimg_lut, f'{file_name}_rgb_2_lut.jpg')
187
188      # Compute a histogram of the luma image, in 256 buckets.
189      yimg, _, _ = image_processing_utils.convert_capture_to_planes(cap)
190      hist, _ = numpy.histogram(yimg*255, 256, (0, 256))
191
192      # Plot the histogram using matplotlib, and save as a PNG image.
193      pylab.plot(range(256), hist.tolist())
194      pylab.xlabel('Luma DN')
195      pylab.ylabel('Pixel count')
196      pylab.title('Histogram of luma channel of captured image')
197      matplotlib.pyplot.savefig(f'{file_name}_histogram.png')
198
199      # Capture a frame to be returned as a JPEG. Load it as an RGB image,
200      # then save it back as a JPEG.
201      cap = cam.do_capture(req, cam.CAP_JPEG)
202      rgbimg = image_processing_utils.convert_capture_to_rgb_image(cap)
203      image_processing_utils.write_image(rgbimg, f'{file_name}_jpg.jpg')
204      r, _, _ = image_processing_utils.convert_capture_to_planes(cap)
205      image_processing_utils.write_image(r, f'{file_name}_r.jpg')
206
207# This is the standard boilerplate in each test that allows the script to both
208# be executed directly and imported as a module.
209if __name__ == '__main__':
210  test_runner.main()
211
212