| # Copyright 2015 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 os.path |
| |
| import its.caps |
| import its.cv2image |
| import its.device |
| import its.image |
| import its.objects |
| import its.target |
| |
| import matplotlib |
| from matplotlib import pylab |
| import numpy |
| |
| NAME = os.path.basename(__file__).split(".")[0] |
| NUM_SAMPLES = 4 |
| THRESH_REL_SHARPNESS_DIFF = 0.15 |
| |
| |
| def check_edge_modes(sharpness): |
| """Check that the sharpness for the different edge modes is correct.""" |
| print " Verify HQ(2) is sharper than OFF(0)" |
| assert sharpness[2] > sharpness[0] |
| |
| print " Verify ZSL(3) is similar to OFF(0)" |
| e_msg = "ZSL: %.5f, OFF: %.5f, RTOL: %.2f" % ( |
| sharpness[3], sharpness[0], THRESH_REL_SHARPNESS_DIFF) |
| assert numpy.isclose(sharpness[3], sharpness[0], |
| THRESH_REL_SHARPNESS_DIFF), e_msg |
| |
| print " Verify OFF(0) is not sharper than FAST(1)" |
| assert sharpness[1] > sharpness[0] * (1.0 - THRESH_REL_SHARPNESS_DIFF) |
| |
| print " Verify FAST(1) is not sharper than HQ(2)" |
| assert sharpness[2] > sharpness[1] * (1.0 - THRESH_REL_SHARPNESS_DIFF) |
| |
| |
| def test_edge_mode(cam, edge_mode, sensitivity, exp, fd, out_surface, chart, |
| reprocess_format=None): |
| """Return sharpness of the output images and the capture result metadata. |
| |
| Processes a capture request with a given edge mode, sensitivity, exposure |
| time, focus distance, output surface parameter, and reprocess format |
| (None for a regular request.) |
| |
| Args: |
| cam: An open device session. |
| edge_mode: Edge mode for the request as defined in android.edge.mode |
| sensitivity: Sensitivity for the request as defined in |
| android.sensor.sensitivity |
| exp: Exposure time for the request as defined in |
| android.sensor.exposureTime. |
| fd: Focus distance for the request as defined in |
| android.lens.focusDistance |
| out_surface: Specifications of the output image format and size. |
| chart: object containing chart information |
| reprocess_format: (Optional) The reprocessing format. If not None, |
| reprocessing will be enabled. |
| |
| Returns: |
| Object containing reported edge mode and the sharpness of the output |
| image, keyed by the following strings: |
| "edge_mode" |
| "sharpness" |
| """ |
| |
| req = its.objects.manual_capture_request(sensitivity, exp) |
| req["android.lens.focusDistance"] = fd |
| req["android.edge.mode"] = edge_mode |
| if reprocess_format: |
| req["android.reprocess.effectiveExposureFactor"] = 1.0 |
| |
| sharpness_list = [] |
| caps = cam.do_capture([req]*NUM_SAMPLES, [out_surface], reprocess_format) |
| for n in range(NUM_SAMPLES): |
| y, _, _ = its.image.convert_capture_to_planes(caps[n]) |
| chart.img = its.image.normalize_img(its.image.get_image_patch( |
| y, chart.xnorm, chart.ynorm, chart.wnorm, chart.hnorm)) |
| if n == 0: |
| its.image.write_image(chart.img, "%s_reprocess_fmt_%s_edge=%d.jpg" % |
| (NAME, reprocess_format, edge_mode)) |
| res_edge_mode = caps[n]["metadata"]["android.edge.mode"] |
| sharpness_list.append(its.image.compute_image_sharpness(chart.img)) |
| |
| ret = {} |
| ret["edge_mode"] = res_edge_mode |
| ret["sharpness"] = numpy.mean(sharpness_list) |
| |
| return ret |
| |
| |
| def main(): |
| """Test android.edge.mode param applied when set for reprocessing requests. |
| |
| Capture non-reprocess images for each edge mode and calculate their |
| sharpness as a baseline. |
| |
| Capture reprocessed images for each supported reprocess format and edge_mode |
| mode. Calculate the sharpness of reprocessed images and compare them against |
| the sharpess of non-reprocess images. |
| """ |
| |
| with its.device.ItsSession() as cam: |
| props = cam.get_camera_properties() |
| |
| its.caps.skip_unless(its.caps.read_3a(props) and |
| its.caps.per_frame_control(props) and |
| its.caps.edge_mode(props, 0) and |
| (its.caps.yuv_reprocess(props) or |
| its.caps.private_reprocess(props))) |
| |
| # initialize chart class and locate chart in scene |
| chart = its.cv2image.Chart() |
| |
| with its.device.ItsSession() as cam: |
| mono_camera = its.caps.mono_camera(props) |
| # If reprocessing is supported, ZSL EE mode must be avaiable. |
| assert its.caps.edge_mode(props, 3), "EE mode not available!" |
| |
| reprocess_formats = [] |
| if its.caps.yuv_reprocess(props): |
| reprocess_formats.append("yuv") |
| if its.caps.private_reprocess(props): |
| reprocess_formats.append("private") |
| |
| size = its.objects.get_available_output_sizes("jpg", props)[0] |
| out_surface = {"width": size[0], "height": size[1], "format": "jpg"} |
| |
| # Get proper sensitivity, exposure time, and focus distance. |
| s, e, _, _, fd = cam.do_3a(get_results=True, mono_camera=mono_camera) |
| |
| # Intialize plot |
| pylab.figure("reprocess_result") |
| gr_color = {"yuv": "r", "private": "g", "none": "b"} |
| |
| # Get the sharpness for each edge mode for regular requests |
| sharpness_regular = [] |
| edge_mode_reported_regular = [] |
| for edge_mode in range(4): |
| # Skip unavailable modes |
| if not its.caps.edge_mode(props, edge_mode): |
| edge_mode_reported_regular.append(edge_mode) |
| sharpness_regular.append(0) |
| continue |
| ret = test_edge_mode(cam, edge_mode, s, e, fd, out_surface, chart) |
| edge_mode_reported_regular.append(ret["edge_mode"]) |
| sharpness_regular.append(ret["sharpness"]) |
| |
| pylab.plot(range(4), sharpness_regular, "-"+gr_color["none"]+"o") |
| print "Reported edge modes", |
| print "regular requests:", edge_mode_reported_regular |
| print "Sharpness with EE mode [0,1,2,3]:", sharpness_regular |
| print "" |
| |
| # Get the sharpness for each reprocess format and edge mode for |
| # reprocess requests. |
| sharpnesses_reprocess = [] |
| edge_mode_reported_reprocess = [] |
| |
| for reprocess_format in reprocess_formats: |
| # List of sharpness |
| sharpnesses = [] |
| edge_mode_reported = [] |
| for edge_mode in range(4): |
| # Skip unavailable modes |
| if not its.caps.edge_mode(props, edge_mode): |
| edge_mode_reported.append(edge_mode) |
| sharpnesses.append(0) |
| continue |
| |
| ret = test_edge_mode(cam, edge_mode, s, e, fd, out_surface, |
| chart, reprocess_format) |
| edge_mode_reported.append(ret["edge_mode"]) |
| sharpnesses.append(ret["sharpness"]) |
| |
| sharpnesses_reprocess.append(sharpnesses) |
| edge_mode_reported_reprocess.append(edge_mode_reported) |
| |
| pylab.plot(range(4), sharpnesses, |
| "-"+gr_color[reprocess_format]+"o") |
| print "Reported edge modes w/ request fmt %s:" % reprocess_format |
| print "Sharpness with EE mode [0,1,2,3] for %s reprocess:" % ( |
| reprocess_format), sharpnesses |
| print "" |
| |
| # Finalize plot |
| pylab.title("Red-YUV Reprocess Green-Private Reprocess Blue-None") |
| pylab.xlabel("Edge Enhance Mode") |
| pylab.ylabel("Sharpness") |
| pylab.xticks(range(4)) |
| matplotlib.pyplot.savefig("%s_plot_EE.png" % |
| ("test_reprocess_edge_enhancement")) |
| print "regular requests:" |
| check_edge_modes(sharpness_regular) |
| |
| for reprocess_format in range(len(reprocess_formats)): |
| print "\nreprocess format:", reprocess_format |
| check_edge_modes(sharpnesses_reprocess[reprocess_format]) |
| |
| hq_div_off_reprocess = (sharpnesses_reprocess[reprocess_format][2] / |
| sharpnesses_reprocess[reprocess_format][0]) |
| hq_div_off_regular = sharpness_regular[2] / sharpness_regular[0] |
| e_msg = "HQ/OFF_reprocess: %.4f, HQ/OFF_reg: %.4f, RTOL: %.2f" % ( |
| hq_div_off_reprocess, hq_div_off_regular, |
| THRESH_REL_SHARPNESS_DIFF) |
| print " Verify reprocess HQ(2) ~= reg HQ(2) relative to OFF(0)" |
| assert numpy.isclose(hq_div_off_reprocess, hq_div_off_regular, |
| THRESH_REL_SHARPNESS_DIFF), e_msg |
| |
| if __name__ == "__main__": |
| main() |
| |