def _getSelectionOffsets(self):
fields = self._storyFieldsAndRects[0]
startOffset = None
endOffset = None
curOffset = 0
inHighlightChunk = False
for item in fields:
if (isinstance(item, textInfos.FieldCommand)
and item.command == "formatChange" and item.field.get(
'color', None) == RGB(red=255, green=255, blue=255)):
inHighlightChunk = True
if startOffset is None:
startOffset = curOffset
elif isinstance(item, six.string_types):
try:
import textUtils
curOffset += textUtils.WideStringOffsetConverter(
item).wideStringLength
except ImportError:
curOffset += len(item)
if inHighlightChunk:
endOffset = curOffset
else:
inHighlightChunk = False
if startOffset is not None and endOffset is not None:
return (startOffset, endOffset)
offset = self._getCaretOffset()
return offset, offset
def loadConfAttribra():
global confAttribra
try:
cfg = ConfigObj(cfgFileAttribra, encoding="UTF-8")
for app, mapping in cfg.iteritems():
mappings = {}
for name, value in mapping.iteritems():
if isinstance(value, basestring):
if value.startswith("RGB("): # it's an RGB Object
rgbval = value.split("RGB(")[1]
rgbval = rgbval.split(")")[0]
rgbval = rgbval.split(",")
mappings[name] = [
RGB(int(rgbval[0]), int(rgbval[1]), int(rgbval[2]))]
else:
try:
# if possible adds the value and its int
mappings[name] = [value, int(value)]
except ValueError:
mappings[name] = [value]
else:
mappings[name] = value
confAttribra[app] = mappings
except IOError:
log.debugWarning("No Attribra config file found")
def generate_rainbow(number):
data = []
h = 0.0
for i in range(number):
r, g, b = hsv_to_rgb(h, 1.0, 0.05)
data.append(RGB(r, g, b))
h += 1.0 / number
if h > 1:
h = 0.0
return data
"""
Handler for NVDA's legacy Windows Console support,
used in situations where UIA isn't available.
"""
#: How often to check whether the console is dead (in ms).
CHECK_DEAD_INTERVAL = 100
consoleObject = None #:The console window that is currently in the foreground.
consoleWinEventHookHandles = [
] #:a list of currently registered console win events.
consoleOutputHandle = None
checkDeadTimer = None
CONSOLE_COLORS_TO_RGB = ( #http://en.wikipedia.org/wiki/Color_Graphics_Adapter
RGB(0x00, 0x00, 0x00), #black
RGB(0x00, 0x00, 0xAA), #blue
RGB(0x00, 0xAA, 0x00), #green
RGB(0x00, 0xAA, 0xAA), #cyan
RGB(0xAA, 0x00, 0x00), #red
RGB(0xAA, 0x00, 0xAA), #magenta
RGB(0xAA, 0x55, 0x00), #brown
RGB(0xAA, 0xAA, 0xAA), #white
RGB(0x55, 0x55, 0x55), #gray
RGB(0x55, 0x55, 0xFF), #light blue
RGB(0x55, 0xFF, 0x55), #light green
RGB(0x55, 0xFF, 0xFF), #light cyan
RGB(0xFF, 0x55, 0x55), #light red
RGB(0xFF, 0x55, 0xFF), #light magenta
RGB(0xFF, 0xFF, 0x55), #yellow
RGB(0xFF, 0xFF, 0xFF), #white (high intensity)
A higher width reduces the inner dimensions of the rectangle.
Therefore, if you need to increase the outer dimensions of the rectangle,
you need to increase the margin as well.
@type width: int
@ivar style: The style of the lines to be drawn;
One of the C{winGDI.DashStyle*} enumeration constants.
@type style: int
@ivar margin: The number of pixels between the highlight's rectangle
and the rectangle of the object to be highlighted.
A higher margin stretches the highlight's rectangle.
This value may also be negative.
@type margin: int
"""
BLUE = RGB(0x03, 0x36, 0xFF)
PINK = RGB(0xFF, 0x02, 0x66)
YELLOW = RGB(0xFF, 0xDE, 0x03)
DASH_BLUE = HighlightStyle(BLUE, 5, winGDI.DashStyleDash, 5)
SOLID_PINK = HighlightStyle(PINK, 5, winGDI.DashStyleSolid, 5)
SOLID_BLUE = HighlightStyle(BLUE, 5, winGDI.DashStyleSolid, 5)
SOLID_YELLOW = HighlightStyle(YELLOW, 2, winGDI.DashStyleSolid, 2)
class HighlightWindow(CustomWindow):
transparency = 0xff
className = u"NVDAHighlighter"
windowName = u"NVDA Highlighter Window"
windowStyle = winUser.WS_POPUP | winUser.WS_DISABLED
extendedWindowStyle = winUser.WS_EX_TOPMOST | winUser.WS_EX_LAYERED
transparentColor = 0 # Black
def _isALink(pos):
return DanaEdit._TIMatchesCondition(pos, 'color',
RGB(red=0, green=0, blue=192))
def extract_text(self, apiResult):
entries = []
if "categories" in apiResult:
# Translators: Result label for azure image analyzer
entries.append(_(u"Categories:"))
# Translators: Result label for azure image analyzer
entries.append("{number} categories detected.".format(
number=len(apiResult["categories"])))
for category in apiResult["categories"]:
entries.append(category["name"])
if "detail" in category:
if "celebrities" in category["detail"]:
# Translators: Result label for azure image analyzer
entries.append("{number} celebrities detected.".format(
number=len(category["detail"]["celebrities"])))
for celebrity in category["detail"]["celebrities"]:
entries.append(celebrity["name"])
if "landmarks" in category["detail"]:
# Translators: Result label for azure image analyzer
entries.append("{number} landmarks detected.".format(
number=len(category["detail"]["landmarks"])))
for landmark in category["detail"]["landmarks"]:
entries.append(landmark["name"])
if "adult" in apiResult:
# Translators: Result label for azure image analyzer
entries.append(_(u"Adult content detection:"))
if apiResult["adult"]["isAdultContent"]:
# Translators: Result label for azure image analyzer
entries.append(_(u"This image contains adult content"))
else:
# Translators: Result label for azure image analyzer
entries.append(_(u"This image does not contain adult content"))
if apiResult["adult"]["isRacyContent"]:
# Translators: Result label for azure image analyzer
entries.append(_(u"This image contains racy content"))
else:
# Translators: Result label for azure image analyzer
entries.append(_(u"This image does not contain racy content"))
if "color" in apiResult:
# Translators: Result label for azure image analyzer
entries.append(_(u"Color detection:"))
# Translators: Result label for azure image analyzer
colorMsg = _(
u"Dominant foreground color is {foreGroundColor}.\n Dominant background color is {backGroundColor}."
)
entries.append(
colorMsg.format(
foreGroundColor=apiResult["color"]
["dominantColorForeground"],
backGroundColor=apiResult["color"]
["dominantColorBackground"],
))
hexAccentColor = apiResult["color"]["accentColor"]
r, g, b = unpack("BBB", hexAccentColor.decode("hex"))
rgbAccentColor = RGB(r, g, b)
# Translators: Result label for azure image analyzer
entries.append(
_("Accent color is {color}, its hex code is {hex}.".format(
hex=apiResult["color"]["accentColor"],
color=rgbAccentColor.name)))
# Translators: Result label for azure image analyzer
entries.append(_("Dominant colors:"))
for color in apiResult["color"]["dominantColors"]:
entries.append(color)
if apiResult["color"]["isBWImg"]:
# Translators: Result label for azure image analyzer
entries.append(_(u"The image is black and white."))
else:
# Translators: Result label for azure image analyzer
entries.append(_(u"The image is not black and white."))
if "tags" in apiResult and len(apiResult["tags"]) > 0:
# Translators: Result label for azure image analyzer
entries.append("{number} tags detected.".format(
number=len(apiResult["tags"])))
for tag in apiResult["tags"]:
entries.append(tag["name"])
if "imageType" in apiResult:
# Translators: Result label for azure image analyzer
entries.append(_(u"Detected image type:"))
if apiResult["imageType"]["clipArtType"] == 0:
# Translators: Result label for azure image analyzer
entries.append(_(u"The image is not a clip-art."))
elif apiResult["imageType"]["clipArtType"] == 1:
# Translators: Result label for azure image analyzer
entries.append(_(u"Cannot tell whether is image is clip-art"))
elif apiResult["imageType"]["clipArtType"] == 2:
# Translators: Result label for azure image analyzer
entries.append(_(u"The image is Normal-clip-art"))
elif apiResult["imageType"]["clipArtType"] == 3:
# Translators: Result label for azure image analyzer
entries.append(_(u"The image is Good-clip-art"))
if apiResult["imageType"]["lineDrawingType"] == 1:
# Translators: Result label for azure image analyzer
entries.append(_(u"The image is a lineDrawing"))
else:
# Translators: Result label for azure image analyzer
entries.append(_(u"The image is not a lineDrawing"))
if "description" in apiResult:
# Translators: Result label for azure image analyzer
entries.append("{number} results available.".format(
number=len(apiResult["description"]["captions"])))
for desc in apiResult["description"]["captions"]:
entries.append(desc["text"])
if "objects" in apiResult and len(apiResult["objects"]) > 0:
# Translators: Result label for azure image analyzer
entries.append(
_(u"{number} objects detected.".format(
number=len(apiResult["objects"]))))
resultSets = apiResult["objects"]
if self.text_result:
for result in resultSets:
entries.append(result["object"])
if "brands" in apiResult and len(apiResult["brands"]) > 0:
# Translators: Result label for azure image analyzer
entries.append(
_(u"{number} brands detected.".format(
number=len(apiResult["brands"]))))
resultSets = apiResult["brands"]
if self.text_result:
for result in resultSets:
entries.append(result["name"])
if "faces" in apiResult and len(apiResult["faces"]) > 0:
# Translators: Result label for azure image analyzer
entries.append(
_(u"{number} faces detected.".format(
number=len(apiResult["faces"]))))
if self.text_result:
resultSets = apiResult["faces"]
for result in resultSets:
entries.append(self.getFaceDescription(result))
return u"\r\n".join(entries)