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 pylab 19 import os.path 20 import matplotlib 21 import matplotlib.pyplot 22 import numpy 23 24 def main(): 25 """Black level consistence test. 26 27 Test: capture dark frames and check if black level correction is done 28 correctly. 29 1. Black level should be roughly consistent for repeating shots. 30 2. Noise distribution should be roughly centered at black level. 31 32 Shoot with the camera covered (i.e.) dark/black. The test varies the 33 sensitivity parameter. 34 """ 35 NAME = os.path.basename(__file__).split(".")[0] 36 37 NUM_REPEAT = 3 38 NUM_STEPS = 3 39 40 # Only check the center part where LSC has little effects. 41 R = 200 42 43 # The most frequent pixel value in each image; assume this is the black 44 # level, since the images are all dark (shot with the lens covered). 45 ymodes = [] 46 umodes = [] 47 vmodes = [] 48 49 with its.device.ItsSession() as cam: 50 props = cam.get_camera_properties() 51 sens_range = props['android.sensor.info.sensitivityRange'] 52 sens_step = (sens_range[1] - sens_range[0]) / float(NUM_STEPS-1) 53 sensitivities = [sens_range[0] + i*sens_step for i in range(NUM_STEPS)] 54 print "Sensitivities:", sensitivities 55 56 for si, s in enumerate(sensitivities): 57 for rep in xrange(NUM_REPEAT): 58 req = its.objects.manual_capture_request(100, 1*1000*1000) 59 req["android.blackLevel.lock"] = True 60 req["android.sensor.sensitivity"] = s 61 cap = cam.do_capture(req) 62 yimg,uimg,vimg = its.image.convert_capture_to_planes(cap) 63 w = cap["width"] 64 h = cap["height"] 65 66 # Magnify the noise in saved images to help visualize. 67 its.image.write_image(yimg * 2, 68 "%s_s=%05d_y.jpg" % (NAME, s), True) 69 its.image.write_image(numpy.absolute(uimg - 0.5) * 2, 70 "%s_s=%05d_u.jpg" % (NAME, s), True) 71 72 yimg = yimg[w/2-R:w/2+R, h/2-R:h/2+R] 73 uimg = uimg[w/4-R/2:w/4+R/2, w/4-R/2:w/4+R/2] 74 vimg = vimg[w/4-R/2:w/4+R/2, w/4-R/2:w/4+R/2] 75 yhist,_ = numpy.histogram(yimg*255, 256, (0,256)) 76 ymodes.append(numpy.argmax(yhist)) 77 uhist,_ = numpy.histogram(uimg*255, 256, (0,256)) 78 umodes.append(numpy.argmax(uhist)) 79 vhist,_ = numpy.histogram(vimg*255, 256, (0,256)) 80 vmodes.append(numpy.argmax(vhist)) 81 82 # Take 32 bins from Y, U, and V. 83 # Histograms of U and V are cropped at the center of 128. 84 pylab.plot(range(32), yhist.tolist()[0:32], 'rgb'[si]) 85 pylab.plot(range(32), uhist.tolist()[112:144], 'rgb'[si]+'--') 86 pylab.plot(range(32), vhist.tolist()[112:144], 'rgb'[si]+'--') 87 88 pylab.xlabel("DN: Y[0:32], U[112:144], V[112:144]") 89 pylab.ylabel("Pixel count") 90 pylab.title("Histograms for different sensitivities") 91 matplotlib.pyplot.savefig("%s_plot_histograms.png" % (NAME)) 92 93 print "Y black levels:", ymodes 94 print "U black levels:", umodes 95 print "V black levels:", vmodes 96 97 if __name__ == '__main__': 98 main() 99 100
