The　process　of　manually　rendering　traditional　Chinese　meticulous　flower　painting　is　complicated　and　highly　skilled.　The　existing　automatic　line　drawing　colorization　is　difficult　to　generate　natural　and　reasonable　gradient　effect.　On　the　basis　of　condition　generative　adversarial　network(CGAN),　an　interactive　meticulous　flower　coloring　algorithm　via　attention　guidance　is　proposed　to　accomplish　the　colorization　of　meticulous　flowers　from　line　drawing.　A　color　attention　map　depicting　the　color　category　and　layout　of　flowers　is　designed　to　guide　the　proposed　network　to　learn　important　color　features　in　the　training　stage.　The　color　attention　map　is　considered　as　the　means　of　interaction　between　the　user　and　the　system　for　color　design　in　the　application　stage.　In　the　network　structure　design,　a　local　color-coding　sub-network　is　constructed　and　trained　to　encode　the　flower　color　attention　map.　The　encoded　information　is　introduced　into　the　conditional　normalization　process　of　each　layer　of　the　generator　as　an　affine　parameter　to　accomplish　learning　and　controlling　of　colors.　Since　the　depth　features　emphasize　global　semantic　information,　the　local　high-frequency　information　reflecting　line　features　might　be　lost.　A　cross-layer　connection　structure　is　introduced　into　the　generator　network　to　strengthen　the　learning　of　line　features.　Experimental　results　show　that　the　proposed　algorithm　renders　line　drawing　of　flowers　better　into　meticulous　flowers　and　the　generated　images　are　accordant　with　the　color　distribution　and　characteristics　of　real　meticulous　flowers　with　good　artistic　reality　and　appreciation.　©　2020,　Science　Press.　All　right　reserved.