| # Copyright 2014 The Android Open Source Project |
| # |
| # Licensed under the Apache License, Version 2.0 (the "License"); |
| # you may not use this file except in compliance with the License. |
| # You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| |
| import its.device |
| import its.caps |
| import its.objects |
| import its.image |
| import os.path |
| import pylab |
| import matplotlib |
| import matplotlib.pyplot |
| |
| def main(): |
| """Capture a set of raw images with increasing gains and measure the noise. |
| """ |
| NAME = os.path.basename(__file__).split(".")[0] |
| |
| # Each shot must be 1% noisier (by the variance metric) than the previous |
| # one. |
| VAR_THRESH = 1.01 |
| |
| NUM_STEPS = 5 |
| |
| with its.device.ItsSession() as cam: |
| |
| props = cam.get_camera_properties() |
| its.caps.skip_unless(its.caps.raw16(props) and |
| its.caps.manual_sensor(props) and |
| its.caps.read_3a(props) and |
| its.caps.per_frame_control(props)) |
| |
| # Expose for the scene with min sensitivity |
| sens_min, sens_max = props['android.sensor.info.sensitivityRange'] |
| sens_step = (sens_max - sens_min) / NUM_STEPS |
| s_ae,e_ae,_,_,_ = cam.do_3a(get_results=True) |
| s_e_prod = s_ae * e_ae |
| |
| variances = [] |
| for s in range(sens_min, sens_max, sens_step): |
| |
| e = int(s_e_prod / float(s)) |
| req = its.objects.manual_capture_request(s, e) |
| |
| # Capture raw+yuv, but only look at the raw. |
| cap,_ = cam.do_capture(req, cam.CAP_RAW_YUV) |
| |
| # Measure the variance. Each shot should be noisier than the |
| # previous shot (as the gain is increasing). |
| plane = its.image.convert_capture_to_planes(cap, props)[1] |
| tile = its.image.get_image_patch(plane, 0.45,0.45,0.1,0.1) |
| var = its.image.compute_image_variances(tile)[0] |
| variances.append(var) |
| |
| img = its.image.convert_capture_to_rgb_image(cap, props=props) |
| its.image.write_image(img, "%s_s=%05d_var=%f.jpg" % (NAME,s,var)) |
| print "s=%d, e=%d, var=%e"%(s,e,var) |
| |
| pylab.plot(range(len(variances)), variances) |
| matplotlib.pyplot.savefig("%s_variances.png" % (NAME)) |
| |
| # Test that each shot is noisier than the previous one. |
| for i in range(len(variances) - 1): |
| assert(variances[i] < variances[i+1] / VAR_THRESH) |
| |
| if __name__ == '__main__': |
| main() |
| |