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 15 import its.image 16 import its.device 17 import its.objects 18 import sys 19 import numpy 20 import Image 21 import pprint 22 import math 23 import pylab 24 import os.path 25 import matplotlib 26 import matplotlib.pyplot 27 28 def main(): 29 """Test that device processing can be inverted to linear pixels. 30 31 Captures a sequence of shots with the device pointed at a uniform 32 target. Attempts to invert all the ISP processing to get back to 33 linear R,G,B pixel data. 34 """ 35 NAME = os.path.basename(__file__).split(".")[0] 36 37 # TODO: Query the allowable tonemap curve sizes; here, it's hardcoded to 38 # a length=64 list of tuples. The max allowed length should be inside the 39 # camera properties object. 40 L = 64 41 LM1 = float(L-1) 42 43 gamma_lut = numpy.array( 44 sum([[i/LM1, math.pow(i/LM1, 1/2.2)] for i in xrange(L)], [])) 45 inv_gamma_lut = numpy.array( 46 sum([[i/LM1, math.pow(i/LM1, 2.2)] for i in xrange(L)], [])) 47 48 req = { 49 "android.sensor.exposureTime": 10*1000*1000, 50 "android.sensor.frameDuration": 0, 51 "android.control.mode": 0, 52 "android.control.aeMode": 0, 53 "android.control.awbMode": 0, 54 "android.control.afMode": 0, 55 "android.blackLevel.lock": True, 56 57 # Each channel is a simple gamma curve. 58 "android.tonemap.mode": 0, 59 "android.tonemap.curveRed": gamma_lut.tolist(), 60 "android.tonemap.curveGreen": gamma_lut.tolist(), 61 "android.tonemap.curveBlue": gamma_lut.tolist(), 62 } 63 64 sensitivities = range(100,500,50)+range(500,1000,100)+range(1000,3000,300) 65 66 with its.device.ItsSession() as cam: 67 68 # For i=0, don't set manual color correction gains and transform. Graph 69 # with solid R,G,B curves. 70 # 71 # For i=1, set identity transform and unit gains. Graph with dashed 72 # curves. 73 74 for i in xrange(2): 75 76 r_means = [] 77 g_means = [] 78 b_means = [] 79 80 if i == 1: 81 req["android.colorCorrection.mode"] = 0 82 req["android.colorCorrection.transform"] = ( 83 its.objects.int_to_rational([1,0,0, 0,1,0, 0,0,1])) 84 req["android.colorCorrection.gains"] = [1,1,1,1] 85 86 for sens in sensitivities: 87 req["android.sensor.sensitivity"] = sens 88 fname, w, h, cap_md = cam.do_capture(req) 89 img = its.image.load_yuv420_to_rgb_image(fname, w, h) 90 its.image.write_image( 91 img, "%s_sens=%04d.jpg" % (NAME, sens)) 92 img = its.image.apply_lut_to_image(img, inv_gamma_lut[1::2] * LM1) 93 tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1) 94 rgb_means = its.image.compute_image_means(tile) 95 r_means.append(rgb_means[0]) 96 g_means.append(rgb_means[1]) 97 b_means.append(rgb_means[2]) 98 99 pylab.plot(sensitivities, r_means, ['r','r--'][i]) 100 pylab.plot(sensitivities, g_means, ['g','g--'][i]) 101 pylab.plot(sensitivities, b_means, ['b','b--'][i]) 102 103 pylab.ylim([0,1]) 104 matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME)) 105 106 if __name__ == '__main__': 107 main() 108 109
