1# Copyright 2013 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 15import math 16import os.path 17 18import its.caps 19import its.device 20import its.image 21import its.objects 22import its.target 23 24import matplotlib.pylab 25import matplotlib.pyplot 26 27NAME = os.path.basename(__file__).split(".")[0] 28THRESHOLD_MAX_RMS_DIFF = 0.03 29 30 31def main(): 32 """Test that the reported sizes and formats for image capture work. 33 """ 34 35 with its.device.ItsSession() as cam: 36 props = cam.get_camera_properties() 37 its.caps.skip_unless(its.caps.compute_target_exposure(props) and 38 its.caps.per_frame_control(props)) 39 40 # Use a manual request with a linear tonemap so that the YUV and JPEG 41 # should look the same (once converted by the its.image module). 42 e, s = its.target.get_target_exposure_combos(cam)["midExposureTime"] 43 req = its.objects.manual_capture_request(s, e, 0.0, True, props) 44 45 rgbs = [] 46 47 for size in its.objects.get_available_output_sizes("yuv", props): 48 out_surface = {"width": size[0], "height": size[1], "format": "yuv"} 49 cap = cam.do_capture(req, out_surface) 50 assert cap["format"] == "yuv" 51 assert cap["width"] == size[0] 52 assert cap["height"] == size[1] 53 print "Captured YUV %dx%d" % (cap["width"], cap["height"]), 54 img = its.image.convert_capture_to_rgb_image(cap) 55 its.image.write_image(img, "%s_yuv_w%d_h%d.jpg"%( 56 NAME, size[0], size[1])) 57 tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1) 58 rgb = its.image.compute_image_means(tile) 59 print "rgb =", rgb 60 rgbs.append(rgb) 61 62 for size in its.objects.get_available_output_sizes("jpg", props): 63 out_surface = {"width": size[0], "height": size[1], "format": "jpg"} 64 cap = cam.do_capture(req, out_surface) 65 assert cap["format"] == "jpeg" 66 assert cap["width"] == size[0] 67 assert cap["height"] == size[1] 68 img = its.image.decompress_jpeg_to_rgb_image(cap["data"]) 69 its.image.write_image(img, "%s_jpg_w%d_h%d.jpg"%( 70 NAME, size[0], size[1])) 71 assert img.shape[0] == size[1] 72 assert img.shape[1] == size[0] 73 assert img.shape[2] == 3 74 print "Captured JPEG %dx%d" % (cap["width"], cap["height"]), 75 tile = its.image.get_image_patch(img, 0.45, 0.45, 0.1, 0.1) 76 rgb = its.image.compute_image_means(tile) 77 print "rgb =", rgb 78 rgbs.append(rgb) 79 80 # Plot means vs format 81 matplotlib.pylab.title(NAME) 82 matplotlib.pylab.plot(range(len(rgbs)), [r[0] for r in rgbs], "-ro") 83 matplotlib.pylab.plot(range(len(rgbs)), [g[1] for g in rgbs], "-go") 84 matplotlib.pylab.plot(range(len(rgbs)), [b[2] for b in rgbs], "-bo") 85 matplotlib.pylab.ylim([0, 1]) 86 matplotlib.pylab.xlabel("format number") 87 matplotlib.pylab.ylabel("RGB avg [0, 1]") 88 matplotlib.pyplot.savefig("%s_plot_means.png" % (NAME)) 89 90 max_diff = 0 91 rgb0 = rgbs[0] 92 for rgb1 in rgbs[1:]: 93 rms_diff = math.sqrt( 94 sum([pow(rgb0[i] - rgb1[i], 2.0) for i in range(3)]) / 3.0) 95 max_diff = max(max_diff, rms_diff) 96 print "Max RMS difference:", max_diff 97 msg = "Max RMS difference: %.4f, spec: %.3f" % (max_diff, 98 THRESHOLD_MAX_RMS_DIFF) 99 assert max_diff < THRESHOLD_MAX_RMS_DIFF, msg 100 101if __name__ == "__main__": 102 main() 103 104