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      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 os.path
     21 import numpy
     22 
     23 def main():
     24     """Test that crop regions work.
     25     """
     26     NAME = os.path.basename(__file__).split(".")[0]
     27 
     28     # A list of 5 regions, specified in normalized (x,y,w,h) coords.
     29     # The regions correspond to: TL, TR, BL, BR, CENT
     30     REGIONS = [(0.0, 0.0, 0.5, 0.5),
     31                (0.5, 0.0, 0.5, 0.5),
     32                (0.0, 0.5, 0.5, 0.5),
     33                (0.5, 0.5, 0.5, 0.5),
     34                (0.25, 0.25, 0.5, 0.5)]
     35 
     36     with its.device.ItsSession() as cam:
     37         props = cam.get_camera_properties()
     38         if not its.caps.compute_target_exposure(props):
     39             print "Test skipped"
     40             return
     41 
     42         a = props['android.sensor.info.activeArraySize']
     43         ax, ay = a["left"], a["top"]
     44         aw, ah = a["right"] - a["left"], a["bottom"] - a["top"]
     45         e, s = its.target.get_target_exposure_combos(cam)["minSensitivity"]
     46         print "Active sensor region (%d,%d %dx%d)" % (ax, ay, aw, ah)
     47 
     48         # Uses a 2x digital zoom.
     49         assert(props['android.scaler.availableMaxDigitalZoom'] >= 2)
     50 
     51         # Capture a full frame.
     52         req = its.objects.manual_capture_request(s,e)
     53         cap_full = cam.do_capture(req)
     54         img_full = its.image.convert_capture_to_rgb_image(cap_full)
     55         its.image.write_image(img_full, "%s_full.jpg" % (NAME))
     56         wfull, hfull = cap_full["width"], cap_full["height"]
     57 
     58         # Capture a burst of crop region frames.
     59         # Note that each region is 1/2x1/2 of the full frame, and is digitally
     60         # zoomed into the full size output image, so must be downscaled (below)
     61         # by 2x when compared to a tile of the full image.
     62         reqs = []
     63         for x,y,w,h in REGIONS:
     64             req = its.objects.manual_capture_request(s,e)
     65             req["android.scaler.cropRegion"] = {
     66                     "top": int(ah * y),
     67                     "left": int(aw * x),
     68                     "right": int(aw * (x + w)),
     69                     "bottom": int(ah * (y + h))}
     70             reqs.append(req)
     71         caps_regions = cam.do_capture(reqs)
     72         match_failed = False
     73         for i,cap in enumerate(caps_regions):
     74             a = cap["metadata"]["android.scaler.cropRegion"]
     75             ax, ay = a["left"], a["top"]
     76             aw, ah = a["right"] - a["left"], a["bottom"] - a["top"]
     77 
     78             # Match this crop image against each of the five regions of
     79             # the full image, to find the best match (which should be
     80             # the region that corresponds to this crop image).
     81             img_crop = its.image.convert_capture_to_rgb_image(cap)
     82             img_crop = its.image.downscale_image(img_crop, 2)
     83             its.image.write_image(img_crop, "%s_crop%d.jpg" % (NAME, i))
     84             min_diff = None
     85             min_diff_region = None
     86             for j,(x,y,w,h) in enumerate(REGIONS):
     87                 tile_full = its.image.get_image_patch(img_full, x,y,w,h)
     88                 wtest = min(tile_full.shape[1], aw)
     89                 htest = min(tile_full.shape[0], ah)
     90                 tile_full = tile_full[0:htest:, 0:wtest:, ::]
     91                 tile_crop = img_crop[0:htest:, 0:wtest:, ::]
     92                 its.image.write_image(tile_full, "%s_fullregion%d.jpg"%(NAME,j))
     93                 diff = numpy.fabs(tile_full - tile_crop).mean()
     94                 if min_diff is None or diff < min_diff:
     95                     min_diff = diff
     96                     min_diff_region = j
     97             if i != min_diff_region:
     98                 match_failed = True
     99             print "Crop image %d (%d,%d %dx%d) best match with region %d"%(
    100                     i, ax, ay, aw, ah, min_diff_region)
    101 
    102         assert(not match_failed)
    103 
    104 if __name__ == '__main__':
    105     main()
    106 
    107