Home | History | Annotate | Download | only in scene1 
      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 
     15 import its.device
     16 import its.caps
     17 import its.objects
     18 import its.image
     19 import os.path
     20 import pylab
     21 import matplotlib
     22 import matplotlib.pyplot
     23 
     24 def main():
     25     """Capture a set of raw images with increasing gains and measure the noise.
     26 
     27     Capture raw-only, in a burst.
     28     """
     29     NAME = os.path.basename(__file__).split(".")[0]
     30 
     31     # Each shot must be 1% noisier (by the variance metric) than the previous
     32     # one.
     33     VAR_THRESH = 1.01
     34 
     35     NUM_STEPS = 5
     36 
     37     with its.device.ItsSession() as cam:
     38 
     39         props = cam.get_camera_properties()
     40         its.caps.skip_unless(its.caps.raw16(props) and
     41                              its.caps.manual_sensor(props) and
     42                              its.caps.read_3a(props) and
     43                              its.caps.per_frame_control(props))
     44 
     45         # Expose for the scene with min sensitivity
     46         sens_min, sens_max = props['android.sensor.info.sensitivityRange']
     47         # Digital gains might not be visible on RAW data
     48         sens_max = props['android.sensor.maxAnalogSensitivity']
     49         sens_step = (sens_max - sens_min) / NUM_STEPS
     50         s_ae,e_ae,_,_,f_dist  = cam.do_3a(get_results=True)
     51         s_e_prod = s_ae * e_ae
     52 
     53         reqs = []
     54         settings = []
     55         for s in range(sens_min, sens_max, sens_step):
     56             e = int(s_e_prod / float(s))
     57             req = its.objects.manual_capture_request(s, e, f_dist)
     58             reqs.append(req)
     59             settings.append((s,e))
     60 
     61         caps = cam.do_capture(reqs, cam.CAP_RAW)
     62 
     63         variances = []
     64         for i,cap in enumerate(caps):
     65             (s,e) = settings[i]
     66 
     67             # Measure the variance. Each shot should be noisier than the
     68             # previous shot (as the gain is increasing).
     69             plane = its.image.convert_capture_to_planes(cap, props)[1]
     70             tile = its.image.get_image_patch(plane, 0.45,0.45,0.1,0.1)
     71             var = its.image.compute_image_variances(tile)[0]
     72             variances.append(var)
     73 
     74             img = its.image.convert_capture_to_rgb_image(cap, props=props)
     75             its.image.write_image(img, "%s_s=%05d_var=%f.jpg" % (NAME,s,var))
     76             print "s=%d, e=%d, var=%e"%(s,e,var)
     77 
     78         pylab.plot(range(len(variances)), variances)
     79         matplotlib.pyplot.savefig("%s_variances.png" % (NAME))
     80 
     81         # Test that each shot is noisier than the previous one.
     82         for i in range(len(variances) - 1):
     83             assert(variances[i] < variances[i+1] / VAR_THRESH)
     84 
     85 if __name__ == '__main__':
     86     main()
     87 
     88