1 # Copyright 2014 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 15 import its.image 16 import its.caps 17 import its.device 18 import its.objects 19 import its.target 20 import numpy 21 import os.path 22 23 def main(): 24 """Test that raw streams are not croppable. 25 """ 26 NAME = os.path.basename(__file__).split(".")[0] 27 28 DIFF_THRESH = 0.05 29 CROP_REGION_ERROR_THRESHOLD = 0.01 30 31 with its.device.ItsSession() as cam: 32 props = cam.get_camera_properties() 33 its.caps.skip_unless(its.caps.compute_target_exposure(props) and 34 its.caps.raw16(props) and 35 its.caps.per_frame_control(props)) 36 37 # Calculate the active sensor region for a full (non-cropped) image. 38 a = props['android.sensor.info.activeArraySize'] 39 ax, ay = a["left"], a["top"] 40 aw, ah = a["right"] - a["left"], a["bottom"] - a["top"] 41 print "Active sensor region: (%d,%d %dx%d)" % (ax, ay, aw, ah) 42 43 full_region = { 44 "left": 0, 45 "top": 0, 46 "right": aw, 47 "bottom": ah 48 } 49 50 # Calculate a center crop region. 51 zoom = min(3.0, its.objects.get_max_digital_zoom(props)) 52 assert(zoom >= 1) 53 cropw = aw / zoom 54 croph = ah / zoom 55 56 crop_region = { 57 "left": aw / 2 - cropw / 2, 58 "top": ah / 2 - croph / 2, 59 "right": aw / 2 + cropw / 2, 60 "bottom": ah / 2 + croph / 2 61 } 62 63 # Capture without a crop region. 64 # Use a manual request with a linear tonemap so that the YUV and RAW 65 # should look the same (once converted by the its.image module). 66 e, s = its.target.get_target_exposure_combos(cam)["minSensitivity"] 67 req = its.objects.manual_capture_request(s,e, True) 68 cap1_raw, cap1_yuv = cam.do_capture(req, cam.CAP_RAW_YUV) 69 70 # Capture with a crop region. 71 req["android.scaler.cropRegion"] = crop_region 72 cap2_raw, cap2_yuv = cam.do_capture(req, cam.CAP_RAW_YUV) 73 74 # Check the metadata related to crop regions. 75 # When both YUV and RAW are requested, the crop region that's 76 # applied to YUV should be reported. 77 # Note that the crop region returned by the cropped captures doesn't 78 # need to perfectly match the one that was requested. 79 imgs = {} 80 for s, cap, cr_expected, err_delta in [ 81 ("yuv_full",cap1_yuv,full_region,0), 82 ("raw_full",cap1_raw,full_region,0), 83 ("yuv_crop",cap2_yuv,crop_region,CROP_REGION_ERROR_THRESHOLD), 84 ("raw_crop",cap2_raw,crop_region,CROP_REGION_ERROR_THRESHOLD)]: 85 86 # Convert the capture to RGB and dump to a file. 87 img = its.image.convert_capture_to_rgb_image(cap, props=props) 88 its.image.write_image(img, "%s_%s.jpg" % (NAME, s)) 89 imgs[s] = img 90 91 # Get the crop region that is reported in the capture result. 92 cr_reported = cap["metadata"]["android.scaler.cropRegion"] 93 x, y = cr_reported["left"], cr_reported["top"] 94 w = cr_reported["right"] - cr_reported["left"] 95 h = cr_reported["bottom"] - cr_reported["top"] 96 print "Crop reported on %s: (%d,%d %dx%d)" % (s, x, y, w, h) 97 98 # Test that the reported crop region is the same as the expected 99 # one, for a non-cropped capture, and is close to the expected one, 100 # for a cropped capture. 101 ex = aw * err_delta 102 ey = ah * err_delta 103 assert ((abs(cr_expected["left"] - cr_reported["left"]) <= ex) and 104 (abs(cr_expected["right"] - cr_reported["right"]) <= ex) and 105 (abs(cr_expected["top"] - cr_reported["top"]) <= ey) and 106 (abs(cr_expected["bottom"] - cr_reported["bottom"]) <= ey)) 107 108 # Also check the image content; 3 of the 4 shots should match. 109 # Note that all the shots are RGB below; the variable names correspond 110 # to what was captured. 111 112 # Shrink the YUV images 2x2 -> 1 to account for the size reduction that 113 # the raw images went through in the RGB conversion. 114 imgs2 = {} 115 for s,img in imgs.iteritems(): 116 h,w,ch = img.shape 117 if s in ["yuv_full", "yuv_crop"]: 118 img = img.reshape(h/2,2,w/2,2,3).mean(3).mean(1) 119 img = img.reshape(h/2,w/2,3) 120 imgs2[s] = img 121 122 # Strip any border pixels from the raw shots (since the raw images may 123 # be larger than the YUV images). Assume a symmetric padded border. 124 xpad = (imgs2["raw_full"].shape[1] - imgs2["yuv_full"].shape[1]) / 2 125 ypad = (imgs2["raw_full"].shape[0] - imgs2["yuv_full"].shape[0]) / 2 126 wyuv = imgs2["yuv_full"].shape[1] 127 hyuv = imgs2["yuv_full"].shape[0] 128 imgs2["raw_full"]=imgs2["raw_full"][ypad:ypad+hyuv:,xpad:xpad+wyuv:,::] 129 imgs2["raw_crop"]=imgs2["raw_crop"][ypad:ypad+hyuv:,xpad:xpad+wyuv:,::] 130 print "Stripping padding before comparison:", xpad, ypad 131 132 for s,img in imgs2.iteritems(): 133 its.image.write_image(img, "%s_comp_%s.jpg" % (NAME, s)) 134 135 # Compute diffs between images of the same type. 136 # The raw_crop and raw_full shots should be identical (since the crop 137 # doesn't apply to raw images), and the yuv_crop and yuv_full shots 138 # should be different. 139 diff_yuv = numpy.fabs((imgs2["yuv_full"] - imgs2["yuv_crop"])).mean() 140 diff_raw = numpy.fabs((imgs2["raw_full"] - imgs2["raw_crop"])).mean() 141 print "YUV diff (crop vs. non-crop):", diff_yuv 142 print "RAW diff (crop vs. non-crop):", diff_raw 143 144 assert(diff_yuv > DIFF_THRESH) 145 assert(diff_raw < DIFF_THRESH) 146 147 if __name__ == '__main__': 148 main() 149 150
