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 15import its.device 16import its.caps 17import its.objects 18import its.image 19import os.path 20import pylab 21import matplotlib 22import matplotlib.pyplot 23 24def main(): 25 """Capture a set of raw images with increasing gains and measure the noise. 26 """ 27 NAME = os.path.basename(__file__).split(".")[0] 28 29 # Each shot must be 1% noisier (by the variance metric) than the previous 30 # one. 31 VAR_THRESH = 1.01 32 33 NUM_STEPS = 5 34 35 with its.device.ItsSession() as cam: 36 37 props = cam.get_camera_properties() 38 its.caps.skip_unless(its.caps.raw16(props) and 39 its.caps.manual_sensor(props) and 40 its.caps.read_3a(props) and 41 its.caps.per_frame_control(props)) 42 43 # Expose for the scene with min sensitivity 44 sens_min, sens_max = props['android.sensor.info.sensitivityRange'] 45 sens_step = (sens_max - sens_min) / NUM_STEPS 46 s_ae,e_ae,_,_,_ = cam.do_3a(get_results=True) 47 s_e_prod = s_ae * e_ae 48 49 variances = [] 50 for s in range(sens_min, sens_max, sens_step): 51 52 e = int(s_e_prod / float(s)) 53 req = its.objects.manual_capture_request(s, e) 54 55 # Capture raw+yuv, but only look at the raw. 56 cap,_ = cam.do_capture(req, cam.CAP_RAW_YUV) 57 58 # Measure the variance. Each shot should be noisier than the 59 # previous shot (as the gain is increasing). 60 plane = its.image.convert_capture_to_planes(cap, props)[1] 61 tile = its.image.get_image_patch(plane, 0.45,0.45,0.1,0.1) 62 var = its.image.compute_image_variances(tile)[0] 63 variances.append(var) 64 65 img = its.image.convert_capture_to_rgb_image(cap, props=props) 66 its.image.write_image(img, "%s_s=%05d_var=%f.jpg" % (NAME,s,var)) 67 print "s=%d, e=%d, var=%e"%(s,e,var) 68 69 pylab.plot(range(len(variances)), variances) 70 matplotlib.pyplot.savefig("%s_variances.png" % (NAME)) 71 72 # Test that each shot is noisier than the previous one. 73 for i in range(len(variances) - 1): 74 assert(variances[i] < variances[i+1] / VAR_THRESH) 75 76if __name__ == '__main__': 77 main() 78 79