365d0800c0
BUG=475714 Review URL: https://codereview.chromium.org/1125633002 Cr-Commit-Position: refs/heads/master@{#328163}
186 lines
6.4 KiB
Python
186 lines
6.4 KiB
Python
# Copyright 2014 The Chromium Authors. All rights reserved.
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# Use of this source code is governed by a BSD-style license that can be
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# found in the LICENSE file.
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from __future__ import division
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from telemetry.core import util
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from telemetry.image_processing import histogram
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from telemetry.image_processing import rgba_color
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from telemetry.util import external_modules
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util.AddDirToPythonPath(util.GetTelemetryDir(), 'third_party', 'png')
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import png # pylint: disable=F0401
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cv2 = external_modules.ImportOptionalModule('cv2')
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np = external_modules.ImportRequiredModule('numpy')
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def Channels(image):
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return image.shape[2]
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def Width(image):
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return image.shape[1]
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def Height(image):
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return image.shape[0]
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def Pixels(image):
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return bytearray(np.uint8(image[:, :, ::-1]).flat) # Convert from bgr to rgb.
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def GetPixelColor(image, x, y):
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bgr = image[y][x]
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return rgba_color.RgbaColor(bgr[2], bgr[1], bgr[0])
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def WritePngFile(image, path):
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if cv2 is not None:
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cv2.imwrite(path, image)
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else:
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with open(path, "wb") as f:
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metadata = {}
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metadata['size'] = (Width(image), Height(image))
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metadata['alpha'] = False
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metadata['bitdepth'] = 8
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img = image[:, :, ::-1]
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pixels = img.reshape(-1).tolist()
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png.Writer(**metadata).write_array(f, pixels)
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def FromRGBPixels(width, height, pixels, bpp):
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img = np.array(pixels, order='F', dtype=np.uint8)
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img.resize((height, width, bpp))
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if bpp == 4:
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img = img[:, :, :3] # Drop alpha.
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return img[:, :, ::-1] # Convert from rgb to bgr.
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def FromPngFile(path):
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if cv2 is not None:
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img = cv2.imread(path, cv2.CV_LOAD_IMAGE_COLOR)
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if img is None:
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raise ValueError('Image at path {0} could not be read'.format(path))
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return img
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else:
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with open(path, "rb") as f:
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return FromPng(f.read())
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def FromPng(png_data):
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if cv2 is not None:
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file_bytes = np.asarray(bytearray(png_data), dtype=np.uint8)
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return cv2.imdecode(file_bytes, cv2.CV_LOAD_IMAGE_COLOR)
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else:
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width, height, pixels, meta = png.Reader(bytes=png_data).read_flat()
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return FromRGBPixels(width, height, pixels, 4 if meta['alpha'] else 3)
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def _SimpleDiff(image1, image2):
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if cv2 is not None:
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return cv2.absdiff(image1, image2)
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else:
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amax = np.maximum(image1, image2)
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amin = np.minimum(image1, image2)
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return amax - amin
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def AreEqual(image1, image2, tolerance, likely_equal):
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if image1.shape != image2.shape:
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return False
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self_image = image1
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other_image = image2
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if tolerance:
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if likely_equal:
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return np.amax(_SimpleDiff(image1, image2)) <= tolerance
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else:
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for row in xrange(Height(image1)):
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if np.amax(_SimpleDiff(image1[row], image2[row])) > tolerance:
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return False
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return True
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else:
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if likely_equal:
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return (self_image == other_image).all()
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else:
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for row in xrange(Height(image1)):
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if not (self_image[row] == other_image[row]).all():
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return False
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return True
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def Diff(image1, image2):
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self_image = image1
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other_image = image2
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if image1.shape[2] != image2.shape[2]:
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raise ValueError('Cannot diff images of differing bit depth')
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if image1.shape[:2] != image2.shape[:2]:
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width = max(Width(image1), Width(image2))
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height = max(Height(image1), Height(image2))
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self_image = np.zeros((width, height, image1.shape[2]), np.uint8)
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other_image = np.zeros((width, height, image1.shape[2]), np.uint8)
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self_image[0:Height(image1), 0:Width(image1)] = image1
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other_image[0:Height(image2), 0:Width(image2)] = image2
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return _SimpleDiff(self_image, other_image)
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def GetBoundingBox(image, color, tolerance):
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if cv2 is not None:
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color = np.array([color.b, color.g, color.r])
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img = cv2.inRange(image, np.subtract(color[0:3], tolerance),
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np.add(color[0:3], tolerance))
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count = cv2.countNonZero(img)
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if count == 0:
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return None, 0
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contours, _ = cv2.findContours(img, cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)
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contour = np.concatenate(contours)
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return cv2.boundingRect(contour), count
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else:
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if tolerance:
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color = np.array([color.b, color.g, color.r])
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colorm = color - tolerance
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colorp = color + tolerance
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b = image[:, :, 0]
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g = image[:, :, 1]
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r = image[:, :, 2]
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w = np.where(((b >= colorm[0]) & (b <= colorp[0]) &
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(g >= colorm[1]) & (g <= colorp[1]) &
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(r >= colorm[2]) & (r <= colorp[2])))
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else:
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w = np.where((image[:, :, 0] == color.b) &
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(image[:, :, 1] == color.g) &
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(image[:, :, 2] == color.r))
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if len(w[0]) == 0:
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return None, 0
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return (w[1][0], w[0][0], w[1][-1] - w[1][0] + 1, w[0][-1] - w[0][0] + 1), \
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len(w[0])
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def Crop(image, left, top, width, height):
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img_height, img_width = image.shape[:2]
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if (left < 0 or top < 0 or
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(left + width) > img_width or
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(top + height) > img_height):
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raise ValueError('Invalid dimensions')
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return image[top:top + height, left:left + width]
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def GetColorHistogram(image, ignore_color, tolerance):
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if cv2 is not None:
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mask = None
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if ignore_color is not None:
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color = np.array([ignore_color.b, ignore_color.g, ignore_color.r])
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mask = ~cv2.inRange(image, np.subtract(color, tolerance),
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np.add(color, tolerance))
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flatten = np.ndarray.flatten
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hist_b = flatten(cv2.calcHist([image], [0], mask, [256], [0, 256]))
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hist_g = flatten(cv2.calcHist([image], [1], mask, [256], [0, 256]))
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hist_r = flatten(cv2.calcHist([image], [2], mask, [256], [0, 256]))
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else:
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filtered = image.reshape(-1, 3)
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if ignore_color is not None:
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color = np.array([ignore_color.b, ignore_color.g, ignore_color.r])
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colorm = np.array(color) - tolerance
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colorp = np.array(color) + tolerance
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in_range = ((filtered[:, 0] < colorm[0]) | (filtered[:, 0] > colorp[0]) |
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(filtered[:, 1] < colorm[1]) | (filtered[:, 1] > colorp[1]) |
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(filtered[:, 2] < colorm[2]) | (filtered[:, 2] > colorp[2]))
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filtered = np.compress(in_range, filtered, axis=0)
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if len(filtered[:, 0]) == 0:
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return histogram.ColorHistogram(np.zeros((256)), np.zeros((256)),
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np.zeros((256)), ignore_color)
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hist_b = np.bincount(filtered[:, 0], minlength=256)
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hist_g = np.bincount(filtered[:, 1], minlength=256)
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hist_r = np.bincount(filtered[:, 2], minlength=256)
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return histogram.ColorHistogram(hist_r, hist_g, hist_b, ignore_color)
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