| # Copyright 2014 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 its.image |
| import its.caps |
| import its.device |
| import its.objects |
| import its.target |
| import numpy |
| import os.path |
| |
| def main(): |
| """Test that raw streams are not croppable. |
| """ |
| NAME = os.path.basename(__file__).split(".")[0] |
| |
| DIFF_THRESH = 0.05 |
| CROP_REGION_ERROR_THRESHOLD = 0.01 |
| |
| with its.device.ItsSession() as cam: |
| props = cam.get_camera_properties() |
| its.caps.skip_unless(its.caps.compute_target_exposure(props) and |
| its.caps.raw16(props) and |
| its.caps.per_frame_control(props)) |
| |
| # Calculate the active sensor region for a full (non-cropped) image. |
| a = props['android.sensor.info.activeArraySize'] |
| ax, ay = a["left"], a["top"] |
| aw, ah = a["right"] - a["left"], a["bottom"] - a["top"] |
| print "Active sensor region: (%d,%d %dx%d)" % (ax, ay, aw, ah) |
| |
| full_region = { |
| "left": 0, |
| "top": 0, |
| "right": aw, |
| "bottom": ah |
| } |
| |
| # Calculate a center crop region. |
| zoom = min(3.0, its.objects.get_max_digital_zoom(props)) |
| assert(zoom >= 1) |
| cropw = aw / zoom |
| croph = ah / zoom |
| |
| crop_region = { |
| "left": aw / 2 - cropw / 2, |
| "top": ah / 2 - croph / 2, |
| "right": aw / 2 + cropw / 2, |
| "bottom": ah / 2 + croph / 2 |
| } |
| |
| # Capture without a crop region. |
| # Use a manual request with a linear tonemap so that the YUV and RAW |
| # should look the same (once converted by the its.image module). |
| e, s = its.target.get_target_exposure_combos(cam)["minSensitivity"] |
| req = its.objects.manual_capture_request(s,e, True) |
| cap1_raw, cap1_yuv = cam.do_capture(req, cam.CAP_RAW_YUV) |
| |
| # Capture with a crop region. |
| req["android.scaler.cropRegion"] = crop_region |
| cap2_raw, cap2_yuv = cam.do_capture(req, cam.CAP_RAW_YUV) |
| |
| # Check the metadata related to crop regions. |
| # When both YUV and RAW are requested, the crop region that's |
| # applied to YUV should be reported. |
| # Note that the crop region returned by the cropped captures doesn't |
| # need to perfectly match the one that was requested. |
| imgs = {} |
| for s, cap, cr_expected, err_delta in [ |
| ("yuv_full",cap1_yuv,full_region,0), |
| ("raw_full",cap1_raw,full_region,0), |
| ("yuv_crop",cap2_yuv,crop_region,CROP_REGION_ERROR_THRESHOLD), |
| ("raw_crop",cap2_raw,crop_region,CROP_REGION_ERROR_THRESHOLD)]: |
| |
| # Convert the capture to RGB and dump to a file. |
| img = its.image.convert_capture_to_rgb_image(cap, props=props) |
| its.image.write_image(img, "%s_%s.jpg" % (NAME, s)) |
| imgs[s] = img |
| |
| # Get the crop region that is reported in the capture result. |
| cr_reported = cap["metadata"]["android.scaler.cropRegion"] |
| x, y = cr_reported["left"], cr_reported["top"] |
| w = cr_reported["right"] - cr_reported["left"] |
| h = cr_reported["bottom"] - cr_reported["top"] |
| print "Crop reported on %s: (%d,%d %dx%d)" % (s, x, y, w, h) |
| |
| # Test that the reported crop region is the same as the expected |
| # one, for a non-cropped capture, and is close to the expected one, |
| # for a cropped capture. |
| ex = aw * err_delta |
| ey = ah * err_delta |
| assert ((abs(cr_expected["left"] - cr_reported["left"]) <= ex) and |
| (abs(cr_expected["right"] - cr_reported["right"]) <= ex) and |
| (abs(cr_expected["top"] - cr_reported["top"]) <= ey) and |
| (abs(cr_expected["bottom"] - cr_reported["bottom"]) <= ey)) |
| |
| # Also check the image content; 3 of the 4 shots should match. |
| # Note that all the shots are RGB below; the variable names correspond |
| # to what was captured. |
| |
| # Shrink the YUV images 2x2 -> 1 to account for the size reduction that |
| # the raw images went through in the RGB conversion. |
| imgs2 = {} |
| for s,img in imgs.iteritems(): |
| h,w,ch = img.shape |
| if s in ["yuv_full", "yuv_crop"]: |
| img = img.reshape(h/2,2,w/2,2,3).mean(3).mean(1) |
| img = img.reshape(h/2,w/2,3) |
| imgs2[s] = img |
| |
| # Strip any border pixels from the raw shots (since the raw images may |
| # be larger than the YUV images). Assume a symmetric padded border. |
| xpad = (imgs2["raw_full"].shape[1] - imgs2["yuv_full"].shape[1]) / 2 |
| ypad = (imgs2["raw_full"].shape[0] - imgs2["yuv_full"].shape[0]) / 2 |
| wyuv = imgs2["yuv_full"].shape[1] |
| hyuv = imgs2["yuv_full"].shape[0] |
| imgs2["raw_full"]=imgs2["raw_full"][ypad:ypad+hyuv:,xpad:xpad+wyuv:,::] |
| imgs2["raw_crop"]=imgs2["raw_crop"][ypad:ypad+hyuv:,xpad:xpad+wyuv:,::] |
| print "Stripping padding before comparison:", xpad, ypad |
| |
| for s,img in imgs2.iteritems(): |
| its.image.write_image(img, "%s_comp_%s.jpg" % (NAME, s)) |
| |
| # Compute diffs between images of the same type. |
| # The raw_crop and raw_full shots should be identical (since the crop |
| # doesn't apply to raw images), and the yuv_crop and yuv_full shots |
| # should be different. |
| diff_yuv = numpy.fabs((imgs2["yuv_full"] - imgs2["yuv_crop"])).mean() |
| diff_raw = numpy.fabs((imgs2["raw_full"] - imgs2["raw_crop"])).mean() |
| print "YUV diff (crop vs. non-crop):", diff_yuv |
| print "RAW diff (crop vs. non-crop):", diff_raw |
| |
| assert(diff_yuv > DIFF_THRESH) |
| assert(diff_raw < DIFF_THRESH) |
| |
| if __name__ == '__main__': |
| main() |
| |