CameraITS: Restructured test folders to group by scenes.

Change-Id: I3dc66bd44569f4416826d7f23b4e63533058bd3f

1 files changed, 102 insertions, 0 deletions

diff --git a/apps/CameraITS/tests/scene1/test_param_noise_reduction.py b/apps/CameraITS/tests/scene1/test_param_noise_reduction.py
new file mode 100644
index 0000000..d183630
--- /dev/null
+++ b/apps/CameraITS/tests/scene1/test_param_noise_reduction.py
@@ -0,0 +1,102 @@
+# Copyright 2013 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 pylab
+import os.path
+import matplotlib
+import matplotlib.pyplot
+
+def main():
+    """Test that the android.noiseReduction.mode param is applied when set.
+
+    Capture images with the camera dimly lit. Uses a long exposure
+    and a high analog gain to ensure the captured image is noisy.
+
+    Captures three images, for NR off, "fast", and "high quality".
+    Also captures an image with low gain and NR off, and uses the variance
+    of this as the baseline.
+    """
+    NAME = os.path.basename(__file__).split(".")[0]
+
+    THRESHOLD_MIN_VARIANCE_RATIO = 0.7
+
+    req = {
+        "android.control.mode": 0,
+        "android.control.aeMode": 0,
+        "android.control.awbMode": 0,
+        "android.control.afMode": 0,
+        "android.sensor.frameDuration": 0
+        }
+
+    # List of variances for Y,U,V.
+    variances = [[],[],[]]
+
+    # Reference (baseline) variance for each of Y,U,V.
+    ref_variance = []
+
+    nr_modes_reported = []
+
+    with its.device.ItsSession() as cam:
+        # NR mode 0 with low gain
+        req["android.noiseReduction.mode"] = 0
+        req["android.sensor.sensitivity"] = 100
+        req["android.sensor.exposureTime"] = 20*1000*1000
+        cap = cam.do_capture(req)
+        its.image.write_image(
+                its.image.convert_capture_to_rgb_image(cap),
+                "%s_low_gain.jpg" % (NAME))
+        planes = its.image.convert_capture_to_planes(cap)
+        for j in range(3):
+            img = planes[j]
+            tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1)
+            ref_variance.append(its.image.compute_image_variances(tile)[0])
+
+        for i in range(3):
+            # NR modes 0, 1, 2 with high gain
+            req["android.noiseReduction.mode"] = i
+            req["android.sensor.sensitivity"] = 100*16
+            req["android.sensor.exposureTime"] = (20*1000*1000/16)
+            cap = cam.do_capture(req)
+            nr_modes_reported.append(
+                    cap["metadata"]["android.noiseReduction.mode"])
+            its.image.write_image(
+                    its.image.convert_capture_to_rgb_image(cap),
+                    "%s_high_gain_nr=%d.jpg" % (NAME, i))
+            planes = its.image.convert_capture_to_planes(cap)
+            for j in range(3):
+                img = planes[j]
+                tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1)
+                variance = its.image.compute_image_variances(tile)[0]
+                variances[j].append(variance / ref_variance[j])
+
+    # Draw a plot.
+    for j in range(3):
+        pylab.plot(range(3), variances[j], "rgb"[j])
+    matplotlib.pyplot.savefig("%s_plot_variances.png" % (NAME))
+
+    assert(nr_modes_reported == [0,1,2])
+
+    # Check that the variance of the NR=0 image is much higher than for the
+    # NR=1 and NR=2 images.
+    for j in range(3):
+        for i in range(1,3):
+            assert(variances[j][i] / variances[j][0] <
+                   THRESHOLD_MIN_VARIANCE_RATIO)
+
+if __name__ == '__main__':
+    main()
+