Newer
Older
adjustgpx-core / importPicture / doc / EXiF.class.violet.html
<HTML>
<HEAD>
<META name="description"
	content="Violet UML Editor cross format document" />
<META name="keywords" content="Violet, UML" />
<META charset="UTF-8" />
<SCRIPT type="text/javascript">
	function switchVisibility() {
		var obj = document.getElementById("content");
		obj.style.display = (obj.style.display == "block") ? "none" : "block";
	}
</SCRIPT>
</HEAD>
<BODY>
	This file was generated with Violet UML Editor 2.1.0.
	&nbsp;&nbsp;(&nbsp;<A href=# onclick="switchVisibility()">View Source</A>&nbsp;/&nbsp;<A href="http://sourceforge.net/projects/violet/files/violetumleditor/" target="_blank">Download Violet</A>&nbsp;)
	<BR />
	<BR />
	<SCRIPT id="content" type="text/xml"><![CDATA[<ClassDiagramGraph id="1">
  <nodes id="2">
    <InterfaceNode id="3">
      <children id="4"/>
      <location class="Point2D.Double" id="5" x="20.0" y="20.0"/>
      <id id="6" value="141bece1-4023-41c9-a2e8-8040d6e7de86"/>
      <revision>1</revision>
      <backgroundColor id="7">
        <red>255</red>
        <green>255</green>
        <blue>255</blue>
        <alpha>255</alpha>
      </backgroundColor>
      <borderColor id="8">
        <red>0</red>
        <green>0</green>
        <blue>0</blue>
        <alpha>255</alpha>
      </borderColor>
      <textColor reference="8"/>
      <name id="9" justification="1" size="3" underlined="false">
        <text>«ImageMetadata»</text>
      </name>
      <methods id="10" justification="0" size="4" underlined="false">
        <text></text>
      </methods>
    </InterfaceNode>
    <ClassNode id="11">
      <children id="12"/>
      <location class="Point2D.Double" id="13" x="10.0" y="110.0"/>
      <id id="14" value="6f5f7c44-9cda-4fd2-8be1-9a94326f8747"/>
      <revision>1</revision>
      <backgroundColor reference="7"/>
      <borderColor reference="8"/>
      <textColor reference="8"/>
      <name id="15" justification="1" size="3" underlined="false">
        <text>JpegImageMetadata</text>
      </name>
      <attributes id="16" justification="0" size="4" underlined="false">
        <text></text>
      </attributes>
      <methods id="17" justification="0" size="4" underlined="false">
        <text>+ getExif(): TiffImageMetadata</text>
      </methods>
    </ClassNode>
    <ClassNode id="18">
      <children id="19"/>
      <location class="Point2D.Double" id="20" x="290.0" y="110.0"/>
      <id id="21" value="b966178f-c278-495a-a66e-05110715a8ba"/>
      <revision>1</revision>
      <backgroundColor reference="7"/>
      <borderColor reference="8"/>
      <textColor reference="8"/>
      <name id="22" justification="1" size="3" underlined="false">
        <text>exif : TiffImageMetada
</text>
      </name>
      <attributes id="23" justification="0" size="4" underlined="false">
        <text>- content: TiffContents</text>
      </attributes>
      <methods id="24" justification="0" size="4" underlined="false">
        <text>+ getOutputSet(): TiffOutputSet</text>
      </methods>
    </ClassNode>
    <ClassNode id="25">
      <children id="26"/>
      <location class="Point2D.Double" id="27" x="980.0" y="90.0"/>
      <id id="28" value="19de1c4a-6a41-49c5-bf2a-8a1faeba9a24"/>
      <revision>1</revision>
      <backgroundColor reference="7"/>
      <borderColor reference="8"/>
      <textColor reference="8"/>
      <name id="29" justification="1" size="3" underlined="false">
        <text>TiffOutputDirectory
(gpsDirectory)</text>
      </name>
      <attributes id="30" justification="0" size="4" underlined="false">
        <text></text>
      </attributes>
      <methods id="31" justification="0" size="4" underlined="false">
        <text>+ getFields(): List&lt;TiffOutputField&gt;
+ removeField(key: TiffOutputField.tagInfo)
+ add(tagInfo:TagInfoAscii, values:String[]) : void</text>
      </methods>
    </ClassNode>
    <ClassNode id="32">
      <children id="33"/>
      <location class="Point2D.Double" id="34" x="600.0" y="100.0"/>
      <id id="35" value="b25d1b25-fdbb-4736-9b07-bbbe6e33860a"/>
      <revision>1</revision>
      <backgroundColor reference="7"/>
      <borderColor reference="8"/>
      <textColor reference="8"/>
      <name id="36" justification="1" size="3" underlined="false">
        <text>TiffOutputSet
(outputSet)</text>
      </name>
      <attributes id="37" justification="0" size="4" underlined="false">
        <text></text>
      </attributes>
      <methods id="38" justification="0" size="4" underlined="false">
        <text>+ getGPSDirectory(): TiffOutputDirectory</text>
      </methods>
    </ClassNode>
    <ClassNode id="39">
      <children id="40"/>
      <location class="Point2D.Double" id="41" x="1080.0" y="300.0"/>
      <id id="42" value="5a42e800-9f90-4fe9-abab-477a0852dee1"/>
      <revision>1</revision>
      <backgroundColor reference="7"/>
      <borderColor reference="8"/>
      <textColor reference="8"/>
      <name id="43" justification="1" size="3" underlined="false">
        <text>java.io.List</text>
      </name>
      <attributes id="44" justification="0" size="4" underlined="false">
        <text></text>
      </attributes>
      <methods id="45" justification="0" size="4" underlined="false">
        <text></text>
      </methods>
    </ClassNode>
    <ClassNode id="46">
      <children id="47"/>
      <location class="Point2D.Double" id="48" x="1070.0" y="420.0"/>
      <id id="49" value="06d3943c-473e-4695-aa69-2b3364e8f3f4"/>
      <revision>1</revision>
      <backgroundColor reference="7"/>
      <borderColor reference="8"/>
      <textColor reference="8"/>
      <name id="50" justification="1" size="3" underlined="false">
        <text>TiffOutputField</text>
      </name>
      <attributes id="51" justification="0" size="4" underlined="false">
        <text>+ tagInfo</text>
      </attributes>
      <methods id="52" justification="0" size="4" underlined="false">
        <text></text>
      </methods>
    </ClassNode>
    <InterfaceNode id="53">
      <children id="54"/>
      <location class="Point2D.Double" id="55" x="330.0" y="10.0"/>
      <id id="56" value="1cd2131a-7b04-4a56-93c9-949e2bd54fa3"/>
      <revision>1</revision>
      <backgroundColor id="57">
        <red>255</red>
        <green>255</green>
        <blue>255</blue>
        <alpha>255</alpha>
      </backgroundColor>
      <borderColor id="58">
        <red>0</red>
        <green>0</green>
        <blue>0</blue>
        <alpha>255</alpha>
      </borderColor>
      <textColor reference="58"/>
      <name id="59" justification="1" size="3" underlined="false">
        <text>«Imaging»</text>
      </name>
      <methods id="60" justification="0" size="4" underlined="false">
        <text>+ getMetadata(file:File)</text>
      </methods>
    </InterfaceNode>
    <ClassNode id="61">
      <children id="62"/>
      <location class="Point2D.Double" id="63" x="250.0" y="330.0"/>
      <id id="64" value="2d20fc7d-49f4-46fb-9da5-14c14ee32ceb"/>
      <revision>1</revision>
      <backgroundColor reference="57"/>
      <borderColor reference="58"/>
      <textColor reference="58"/>
      <name id="65" justification="1" size="3" underlined="false">
        <text>GPSInfo</text>
      </name>
      <attributes id="66" justification="0" size="4" underlined="false">
        <text></text>
      </attributes>
      <methods id="67" justification="0" size="4" underlined="false">
        <text>+ getLatitudeAsDegreesNorth() : double
+ getLongitudeAsDegreesEast() : double</text>
      </methods>
    </ClassNode>
  </nodes>
  <edges id="68">
    <CompositionEdge id="69">
      <start class="ClassNode" reference="18"/>
      <end class="ClassNode" reference="11"/>
      <startLocation class="Point2D.Double" id="70" x="70.0" y="20.0"/>
      <endLocation class="Point2D.Double" id="71" x="140.0" y="50.0"/>
      <transitionPoints id="72"/>
      <id id="73" value="516b1ac1-150a-42fe-941a-2866baf497dd"/>
      <revision>1</revision>
      <bentStyle name="AUTO"/>
      <startLabel>0..1</startLabel>
      <middleLabel>getExif()</middleLabel>
      <endLabel></endLabel>
    </CompositionEdge>
    <InterfaceInheritanceEdge id="74">
      <start class="ClassNode" reference="11"/>
      <end class="InterfaceNode" reference="3"/>
      <startLocation class="Point2D.Double" id="75" x="90.0" y="50.0"/>
      <endLocation class="Point2D.Double" id="76" x="80.0" y="30.0"/>
      <transitionPoints id="77"/>
      <id id="78" value="80e6e38d-53ef-4849-9d90-b9a2c2dc5fd0"/>
      <revision>1</revision>
      <bentStyle name="AUTO"/>
      <startLabel></startLabel>
      <middleLabel></middleLabel>
      <endLabel></endLabel>
    </InterfaceInheritanceEdge>
    <CompositionEdge id="79">
      <start class="ClassNode" reference="32"/>
      <end class="ClassNode" reference="18"/>
      <startLocation class="Point2D.Double" id="80" x="60.0" y="30.0"/>
      <endLocation class="Point2D.Double" id="81" x="140.0" y="100.0"/>
      <transitionPoints id="82"/>
      <id id="83" value="b52729a0-5367-45b9-bd3d-d1987c830f25"/>
      <revision>1</revision>
      <bentStyle name="AUTO"/>
      <startLabel>1</startLabel>
      <middleLabel>getOutputSet()</middleLabel>
      <endLabel></endLabel>
    </CompositionEdge>
    <CompositionEdge id="84">
      <start class="ClassNode" reference="25"/>
      <end class="ClassNode" reference="32"/>
      <startLocation class="Point2D.Double" id="85" x="90.0" y="40.0"/>
      <endLocation class="Point2D.Double" id="86" x="200.0" y="80.0"/>
      <transitionPoints id="87"/>
      <id id="88" value="0649afe3-3491-4c1b-a4c8-2f989dc6ad32"/>
      <revision>1</revision>
      <bentStyle name="AUTO"/>
      <startLabel>1</startLabel>
      <middleLabel>getGPSDirectory()</middleLabel>
      <endLabel></endLabel>
    </CompositionEdge>
    <CompositionEdge id="89">
      <start class="ClassNode" reference="39"/>
      <end class="ClassNode" reference="25"/>
      <startLocation class="Point2D.Double" id="90" x="70.0" y="20.0"/>
      <endLocation class="Point2D.Double" id="91" x="120.0" y="100.0"/>
      <transitionPoints id="92"/>
      <id id="93" value="ccf5391a-467f-41bb-a2ef-32242e0b54a5"/>
      <revision>1</revision>
      <bentStyle name="VHV"/>
      <startLabel>1</startLabel>
      <middleLabel>getFields()</middleLabel>
      <endLabel></endLabel>
    </CompositionEdge>
    <AggregationEdge id="94">
      <start class="ClassNode" reference="46"/>
      <end class="ClassNode" reference="39"/>
      <startLocation class="Point2D.Double" id="95" x="80.0" y="30.0"/>
      <endLocation class="Point2D.Double" id="96" x="70.0" y="40.0"/>
      <transitionPoints id="97"/>
      <id id="98" value="880de603-5ed4-41bc-9e00-d427598f30c6"/>
      <revision>1</revision>
      <bentStyle name="AUTO"/>
      <startLabel>0..*</startLabel>
      <middleLabel></middleLabel>
      <endLabel></endLabel>
    </AggregationEdge>
    <AggregationEdge id="99">
      <start class="InterfaceNode" reference="3"/>
      <end class="InterfaceNode" reference="53"/>
      <startLocation class="Point2D.Double" id="100" x="100.0" y="30.0"/>
      <endLocation class="Point2D.Double" id="101" x="40.0" y="30.0"/>
      <transitionPoints id="102"/>
      <id id="103" value="415ddb9e-5584-47cf-902e-229f2414df2d"/>
      <revision>1</revision>
      <bentStyle name="AUTO"/>
      <startLabel>1</startLabel>
      <middleLabel>getMetadata(file)</middleLabel>
      <endLabel>1</endLabel>
    </AggregationEdge>
    <CompositionEdge id="104">
      <start class="ClassNode" reference="18"/>
      <end class="ClassNode" reference="61"/>
      <startLocation class="Point2D.Double" id="105" x="90.0" y="60.0"/>
      <endLocation class="Point2D.Double" id="106" x="90.0" y="70.0"/>
      <transitionPoints id="107"/>
      <id id="108" value="64c1f884-7944-42bd-a2c0-eb509548ec67"/>
      <revision>1</revision>
      <bentStyle name="AUTO"/>
      <startLabel></startLabel>
      <middleLabel>+ getExif()</middleLabel>
      <endLabel></endLabel>
    </CompositionEdge>
  </edges>
</ClassDiagramGraph>]]></SCRIPT>
	<BR />
	<BR />
	<IMG alt="embedded diagram image" src="data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAABOcAAAIDCAIAAADABe1IAABnsUlEQVR42uzdf0he6Z3//8w4riuu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" />
</BODY>
</HTML>