1 files changed, 71 insertions, 0 deletions
diff --git a/apps/CameraITS/tests/inprog/test_ev_compensation.py b/apps/CameraITS/tests/inprog/test_ev_compensation.py
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+++ b/apps/CameraITS/tests/inprog/test_ev_compensation.py
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+# 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.image
+import its.device
+import its.objects
+import os.path
+import pylab
+import matplotlib
+import matplotlib.pyplot
+import numpy
+
+def main():
+    """Tests that EV compensation is applied.
+    """
+    NAME = os.path.basename(__file__).split(".")[0]
+
+    MAX_LUMA_DELTA_THRESH = 0.01
+    AVG_LUMA_DELTA_THRESH = 0.001
+
+    with its.device.ItsSession() as cam:
+        props = cam.get_camera_properties()
+        cam.do_3a()
+
+        # Capture auto shots, but with a linear tonemap.
+        req = its.objects.auto_capture_request()
+        req["android.tonemap.mode"] = 0
+        req["android.tonemap.curveRed"] = (0.0, 0.0, 1.0, 1.0)
+        req["android.tonemap.curveGreen"] = (0.0, 0.0, 1.0, 1.0)
+        req["android.tonemap.curveBlue"] = (0.0, 0.0, 1.0, 1.0)
+
+        evs = range(-4,5)
+        lumas = []
+        for ev in evs:
+            req['android.control.aeExposureCompensation'] = ev
+            cap = cam.do_capture(req)
+            y = its.image.convert_capture_to_planes(cap)[0]
+            tile = its.image.get_image_patch(y, 0.45,0.45,0.1,0.1)
+            lumas.append(its.image.compute_image_means(tile)[0])
+
+        ev_step_size_in_stops = its.objects.rational_to_float(
+                props['android.control.aeCompensationStep'])
+        luma_increase_per_step = pow(2, ev_step_size_in_stops)
+        expected_lumas = [lumas[0] * pow(luma_increase_per_step, i) \
+                for i in range(len(evs))]
+
+        pylab.plot(evs, lumas, 'r')
+        pylab.plot(evs, expected_lumas, 'b')
+        matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME))
+
+        luma_diffs = [expected_lumas[i] - lumas[i] for i in range(len(evs))]
+        max_diff = max(luma_diffs)
+        avg_diff = sum(luma_diffs) / len(luma_diffs)
+        print "Max delta between modeled and measured lumas:", max_diff
+        print "Avg delta between modeled and measured lumas:", avg_diff
+        assert(max_diff < MAX_LUMA_DELTA_THRESH)
+        assert(avg_diff < AVG_LUMA_DELTA_THRESH)
+
+if __name__ == '__main__':
+    main()