1# Copyright 2020 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 android.jpeg.quality increases JPEG image quality.""" 15 16 17import logging 18import math 19import os.path 20 21from matplotlib import pylab 22import matplotlib.pyplot 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 32_JPEG_APPN_MARKERS = [[255, 224], [255, 225], [255, 226], [255, 227], 33 [255, 228], [255, 229], [255, 230], [255, 231], 34 [255, 232], [255, 235]] 35_JPEG_DHT_MARKER = [255, 196] # JPEG Define Huffman Table 36_JPEG_DQT_MARKER = [255, 219] # JPEG Define Quantization Table 37_JPEG_DQT_TOL = 0.8 # -20% for each +20 in jpeg.quality (empirical number) 38_JPEG_EOI_MARKER = [255, 217] # JPEG End of Image 39_JPEG_SOI_MARKER = [255, 216] # JPEG Start of Image 40_JPEG_SOS_MARKER = [255, 218] # JPEG Start of Scan 41_NAME = os.path.splitext(os.path.basename(__file__))[0] 42_QUALITIES = [25, 45, 65, 85] 43_SYMBOLS = ['o', 's', 'v', '^', '<', '>'] 44 45 46def is_square(integer): 47 root = math.sqrt(integer) 48 return integer == int(root + 0.5)**2 49 50 51def strip_soi_marker(jpeg): 52 """Strip off start of image marker. 53 54 SOI is of form [xFF xD8] and JPEG needs to start with marker. 55 56 Args: 57 jpeg: 1-D numpy int [0:255] array; values from JPEG capture 58 59 Returns: 60 jpeg with SOI marker stripped off. 61 """ 62 63 soi = jpeg[0:2] 64 if list(soi) != _JPEG_SOI_MARKER: 65 raise AssertionError('JPEG has no Start Of Image marker') 66 return jpeg[2:] 67 68 69def strip_appn_data(jpeg): 70 """Strip off application specific data at beginning of JPEG. 71 72 APPN markers are of form [xFF, xE*, size_msb, size_lsb] and should follow 73 SOI marker. 74 75 Args: 76 jpeg: 1-D numpy int [0:255] array; values from JPEG capture 77 78 Returns: 79 jpeg with APPN marker(s) and data stripped off. 80 """ 81 82 length = 0 83 i = 0 84 # find APPN markers and strip off payloads at beginning of jpeg 85 while i < len(jpeg) - 1: 86 if [jpeg[i], jpeg[i + 1]] in _JPEG_APPN_MARKERS: 87 length = jpeg[i + 2] * 256 + jpeg[i + 3] + 2 88 logging.debug('stripped APPN length:%d', length) 89 jpeg = np.concatenate((jpeg[0:i], jpeg[length:]), axis=None) 90 elif ([jpeg[i], jpeg[i + 1]] == _JPEG_DQT_MARKER or 91 [jpeg[i], jpeg[i + 1]] == _JPEG_DHT_MARKER): 92 break 93 else: 94 i += 1 95 96 return jpeg 97 98 99def find_dqt_markers(marker, jpeg): 100 """Find location(s) of marker list in jpeg. 101 102 DQT marker is of form [xFF, xDB]. 103 104 Args: 105 marker: list; marker values 106 jpeg: 1-D numpy int [0:255] array; JPEG capture w/ SOI & APPN stripped 107 108 Returns: 109 locs: list; marker locations in jpeg 110 """ 111 locs = [] 112 marker_len = len(marker) 113 for i in range(len(jpeg) - marker_len + 1): 114 if list(jpeg[i:i + marker_len]) == marker: 115 locs.append(i) 116 return locs 117 118 119def extract_dqts(jpeg, debug=False): 120 """Find and extract the DQT info in the JPEG. 121 122 SOI marker and APPN markers plus data are stripped off front of JPEG. 123 DQT marker is of form [xFF, xDB] followed by [size_msb, size_lsb]. 124 Size includes the size values, but not the marker values. 125 Luma DQT is prefixed by 0, Chroma DQT by 1. 126 DQTs can have both luma & chroma or each individually. 127 There can be more than one DQT table for luma and chroma. 128 129 Args: 130 jpeg: 1-D numpy int [0:255] array; values from JPEG capture 131 debug: bool; command line flag to print debug data 132 133 Returns: 134 lumas,chromas: lists of numpy means of luma & chroma DQT matrices. 135 Higher values represent higher compression. 136 """ 137 138 dqt_markers = find_dqt_markers(_JPEG_DQT_MARKER, jpeg) 139 logging.debug('DQT header loc(s):%s', dqt_markers) 140 lumas = [] 141 chromas = [] 142 for i, dqt in enumerate(dqt_markers): 143 if debug: 144 logging.debug('DQT %d start: %d, marker: %s, length: %s', i, dqt, 145 jpeg[dqt:dqt + 2], jpeg[dqt + 2:dqt + 4]) 146 dqt_size = jpeg[dqt + 2] * 256 + jpeg[dqt + 3] - 2 # strip off size marker 147 if dqt_size % 2 == 0: # even payload means luma & chroma 148 logging.debug(' both luma & chroma DQT matrices in marker') 149 dqt_size = (dqt_size - 2) // 2 # subtact off luma/chroma markers 150 if not is_square(dqt_size): 151 raise AssertionError(f'DQT size: {dqt_size}') 152 luma_start = dqt + 5 # skip header, length, & matrix id 153 chroma_start = luma_start + dqt_size + 1 # skip lumen & matrix_id 154 luma = np.array(jpeg[luma_start: luma_start + dqt_size]) 155 chroma = np.array(jpeg[chroma_start: chroma_start + dqt_size]) 156 lumas.append(np.mean(luma)) 157 chromas.append(np.mean(chroma)) 158 if debug: 159 h = int(math.sqrt(dqt_size)) 160 logging.debug(' luma:%s', luma.reshape(h, h)) 161 logging.debug(' chroma:%s', chroma.reshape(h, h)) 162 else: # odd payload means only 1 matrix 163 logging.debug(' single DQT matrix in marker') 164 dqt_size = dqt_size - 1 # subtract off luma/chroma marker 165 if not is_square(dqt_size): 166 raise AssertionError(f'DQT size: {dqt_size}') 167 start = dqt + 5 168 matrix = np.array(jpeg[start:start + dqt_size]) 169 if jpeg[dqt + 4]: # chroma == 1 170 chromas.append(np.mean(matrix)) 171 if debug: 172 h = int(math.sqrt(dqt_size)) 173 logging.debug(' chroma:%s', matrix.reshape(h, h)) 174 else: # luma == 0 175 lumas.append(np.mean(matrix)) 176 if debug: 177 h = int(math.sqrt(dqt_size)) 178 logging.debug(' luma:%s', matrix.reshape(h, h)) 179 180 return lumas, chromas 181 182 183def plot_data(qualities, lumas, chromas, img_name): 184 """Create plot of data.""" 185 logging.debug('qualities: %s', str(qualities)) 186 logging.debug('luma DQT avgs: %s', str(lumas)) 187 logging.debug('chroma DQT avgs: %s', str(chromas)) 188 pylab.title(_NAME) 189 for i in range(lumas.shape[1]): 190 pylab.plot( 191 qualities, lumas[:, i], '-g' + _SYMBOLS[i], label='luma_dqt' + str(i)) 192 pylab.plot( 193 qualities, 194 chromas[:, i], 195 '-r' + _SYMBOLS[i], 196 label='chroma_dqt' + str(i)) 197 pylab.xlim([0, 100]) 198 pylab.ylim([0, None]) 199 pylab.xlabel('jpeg.quality') 200 pylab.ylabel('DQT luma/chroma matrix averages') 201 pylab.legend(loc='upper right', numpoints=1, fancybox=True) 202 matplotlib.pyplot.savefig(f'{img_name}_plot.png') 203 204 205class JpegQualityTest(its_base_test.ItsBaseTest): 206 """Test the camera JPEG compression quality. 207 208 Step JPEG qualities through android.jpeg.quality. Ensure quanitization 209 matrix decreases with quality increase. Matrix should decrease as the 210 matrix represents the division factor. Higher numbers --> fewer quantization 211 levels. 212 """ 213 214 def test_jpeg_quality(self): 215 logging.debug('Starting %s', _NAME) 216 # init variables 217 lumas = [] 218 chromas = [] 219 220 with its_session_utils.ItsSession( 221 device_id=self.dut.serial, 222 camera_id=self.camera_id, 223 hidden_physical_id=self.hidden_physical_id) as cam: 224 225 props = cam.get_camera_properties() 226 props = cam.override_with_hidden_physical_camera_props(props) 227 debug = self.debug_mode 228 229 # Load chart for scene 230 its_session_utils.load_scene( 231 cam, props, self.scene, self.tablet, self.chart_distance) 232 233 # Check skip conditions 234 camera_properties_utils.skip_unless( 235 camera_properties_utils.jpeg_quality(props)) 236 cam.do_3a() 237 238 # do captures over jpeg quality range 239 req = capture_request_utils.auto_capture_request() 240 for q in _QUALITIES: 241 logging.debug('jpeg.quality: %.d', q) 242 req['android.jpeg.quality'] = q 243 cap = cam.do_capture(req, cam.CAP_JPEG) 244 jpeg = cap['data'] 245 246 # strip off start of image 247 jpeg = strip_soi_marker(jpeg) 248 249 # strip off application specific data 250 jpeg = strip_appn_data(jpeg) 251 logging.debug('remaining JPEG header:%s', jpeg[0:4]) 252 253 # find and extract DQTs 254 lumas_i, chromas_i = extract_dqts(jpeg, debug) 255 lumas.append(lumas_i) 256 chromas.append(chromas_i) 257 258 # save JPEG image 259 img = image_processing_utils.convert_capture_to_rgb_image( 260 cap, props=props) 261 img_name = os.path.join(self.log_path, _NAME) 262 image_processing_utils.write_image(img, f'{img_name}_{q}.jpg') 263 264 # turn lumas/chromas into np array to ease multi-dimensional plots/asserts 265 lumas = np.array(lumas) 266 chromas = np.array(chromas) 267 268 # create plot of luma & chroma averages vs quality 269 plot_data(_QUALITIES, lumas, chromas, img_name) 270 271 # assert decreasing luma/chroma with improved jpeg quality 272 for i in range(lumas.shape[1]): 273 l = lumas[:, i] 274 c = chromas[:, i] 275 if not all(y < x * _JPEG_DQT_TOL for x, y in zip(l, l[1:])): 276 raise AssertionError(f'luma DQT avgs: {l}, TOL: {_JPEG_DQT_TOL}') 277 278 if not all(y < x * _JPEG_DQT_TOL for x, y in zip(c, c[1:])): 279 raise AssertionError(f'chroma DQT avgs: {c}, TOL: {_JPEG_DQT_TOL}') 280 281if __name__ == '__main__': 282 test_runner.main() 283