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 15import its.image 16import its.caps 17import its.device 18import its.objects 19from matplotlib import pylab 20import os.path 21import matplotlib 22import matplotlib.pyplot 23 24def main(): 25 """Test that the device will produce full black+white images. 26 """ 27 NAME = os.path.basename(__file__).split(".")[0] 28 29 r_means = [] 30 g_means = [] 31 b_means = [] 32 33 with its.device.ItsSession() as cam: 34 props = cam.get_camera_properties() 35 its.caps.skip_unless(its.caps.manual_sensor(props) and 36 its.caps.per_frame_control(props)) 37 38 debug = its.caps.debug_mode() 39 largest_yuv = its.objects.get_largest_yuv_format(props) 40 if debug: 41 fmt = largest_yuv 42 else: 43 match_ar = (largest_yuv['width'], largest_yuv['height']) 44 fmt = its.objects.get_smallest_yuv_format(props, match_ar=match_ar) 45 46 expt_range = props['android.sensor.info.exposureTimeRange'] 47 sens_range = props['android.sensor.info.sensitivityRange'] 48 49 # Take a shot with very low ISO and exposure time. Expect it to 50 # be black. 51 print "Black shot: sens = %d, exp time = %.4fms" % ( 52 sens_range[0], expt_range[0]/1000000.0) 53 req = its.objects.manual_capture_request(sens_range[0], expt_range[0]) 54 cap = cam.do_capture(req, fmt) 55 img = its.image.convert_capture_to_rgb_image(cap) 56 its.image.write_image(img, "%s_black.jpg" % (NAME)) 57 tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1) 58 black_means = its.image.compute_image_means(tile) 59 r_means.append(black_means[0]) 60 g_means.append(black_means[1]) 61 b_means.append(black_means[2]) 62 print "Dark pixel means:", black_means 63 64 # Take a shot with very high ISO and exposure time. Expect it to 65 # be white. 66 print "White shot: sens = %d, exp time = %.2fms" % ( 67 sens_range[1], expt_range[1]/1000000.0) 68 req = its.objects.manual_capture_request(sens_range[1], expt_range[1]) 69 cap = cam.do_capture(req, fmt) 70 img = its.image.convert_capture_to_rgb_image(cap) 71 its.image.write_image(img, "%s_white.jpg" % (NAME)) 72 tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1) 73 white_means = its.image.compute_image_means(tile) 74 r_means.append(white_means[0]) 75 g_means.append(white_means[1]) 76 b_means.append(white_means[2]) 77 print "Bright pixel means:", white_means 78 79 # Draw a plot. 80 pylab.plot([0,1], r_means, 'r') 81 pylab.plot([0,1], g_means, 'g') 82 pylab.plot([0,1], b_means, 'b') 83 pylab.ylim([0,1]) 84 matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME)) 85 86 for val in black_means: 87 assert(val < 0.025) 88 for val in white_means: 89 assert(val > 0.975) 90 91if __name__ == '__main__': 92 main() 93 94