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 30 with its.device.ItsSession() as cam: 31 props = cam.get_camera_properties() 32 if (not its.caps.compute_target_exposure(props) or 33 not its.caps.raw16(props)): 34 print "Test skipped" 35 return 36 37 a = props['android.sensor.info.activeArraySize'] 38 ax, ay = a["left"], a["top"] 39 aw, ah = a["right"] - a["left"], a["bottom"] - a["top"] 40 print "Active sensor region: (%d,%d %dx%d)" % (ax, ay, aw, ah) 41 42 # Capture without a crop region. 43 # Use a manual request with a linear tonemap so that the YUV and RAW 44 # should look the same (once converted by the its.image module). 45 e, s = its.target.get_target_exposure_combos(cam)["minSensitivity"] 46 req = its.objects.manual_capture_request(s,e, True) 47 cap1_raw, cap1_yuv = cam.do_capture(req, cam.CAP_RAW_YUV) 48 49 # Capture with a center crop region. 50 req["android.scaler.cropRegion"] = { 51 "top": ay + ah/3, 52 "left": ax + aw/3, 53 "right": ax + 2*aw/3, 54 "bottom": ay + 2*ah/3} 55 cap2_raw, cap2_yuv = cam.do_capture(req, cam.CAP_RAW_YUV) 56 57 reported_crops = [] 58 imgs = {} 59 for s,cap in [("yuv_full",cap1_yuv), ("raw_full",cap1_raw), 60 ("yuv_crop",cap2_yuv), ("raw_crop",cap2_raw)]: 61 img = its.image.convert_capture_to_rgb_image(cap, props=props) 62 its.image.write_image(img, "%s_%s.jpg" % (NAME, s)) 63 r = cap["metadata"]["android.scaler.cropRegion"] 64 x, y = a["left"], a["top"] 65 w, h = a["right"] - a["left"], a["bottom"] - a["top"] 66 reported_crops.append((x,y,w,h)) 67 imgs[s] = img 68 print "Crop on %s: (%d,%d %dx%d)" % (s, x,y,w,h) 69 70 # The metadata should report uncropped for all shots (since there is 71 # at least 1 uncropped stream in each case). 72 for (x,y,w,h) in reported_crops: 73 assert((ax,ay,aw,ah) == (x,y,w,h)) 74 75 # Also check the image content; 3 of the 4 shots should match. 76 # Note that all the shots are RGB below; the variable names correspond 77 # to what was captured. 78 # Average the images down 4x4 -> 1 prior to comparison to smooth out 79 # noise. 80 # Shrink the YUV images an additional 2x2 -> 1 to account for the size 81 # reduction that the raw images went through in the RGB conversion. 82 imgs2 = {} 83 for s,img in imgs.iteritems(): 84 h,w,ch = img.shape 85 m = 4 86 if s in ["yuv_full", "yuv_crop"]: 87 m = 8 88 img = img.reshape(h/m,m,w/m,m,3).mean(3).mean(1).reshape(h/m,w/m,3) 89 imgs2[s] = img 90 print s, img.shape 91 92 # Strip any border pixels from the raw shots (since the raw images may 93 # be larger than the YUV images). Assume a symmetric padded border. 94 xpad = (imgs2["raw_full"].shape[1] - imgs2["yuv_full"].shape[1]) / 2 95 ypad = (imgs2["raw_full"].shape[0] - imgs2["yuv_full"].shape[0]) / 2 96 wyuv = imgs2["yuv_full"].shape[1] 97 hyuv = imgs2["yuv_full"].shape[0] 98 imgs2["raw_full"]=imgs2["raw_full"][ypad:ypad+hyuv:,xpad:xpad+wyuv:,::] 99 imgs2["raw_crop"]=imgs2["raw_crop"][ypad:ypad+hyuv:,xpad:xpad+wyuv:,::] 100 print "Stripping padding before comparison:", xpad, ypad 101 102 for s,img in imgs2.iteritems(): 103 its.image.write_image(img, "%s_comp_%s.jpg" % (NAME, s)) 104 105 # Compute image diffs. 106 diff_yuv = numpy.fabs((imgs2["yuv_full"] - imgs2["yuv_crop"])).mean() 107 diff_raw = numpy.fabs((imgs2["raw_full"] - imgs2["raw_crop"])).mean() 108 print "YUV diff (crop vs. non-crop):", diff_yuv 109 print "RAW diff (crop vs. non-crop):", diff_raw 110 111 assert(diff_yuv > DIFF_THRESH) 112 assert(diff_raw < DIFF_THRESH) 113 114 if __name__ == '__main__': 115 main() 116 117
