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<Mask>
5 <Rect width="45" x="17" y="439" height="54" type="negative"/>
6 <Rect width="23" x="368" y="180" height="41" type="negative"/>
7 <Rect width="26" x="455" y="251" height="10" type="negative"/>
9 <Algorithm description="Simple comparison (pixel by pixel)" name="simplecompare">
10 <Parameter description="Threshold" name="threshold">0.01</Parameter>
11 <Parameter description="Tolerance" name="tolerance">0</Parameter>
