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- Add Cloudflare Pages deployment for landing page (snapotter.com) and docs (docs.snapotter.com) - Create deploy-landing.yml and update deploy-docs.yml workflows - Update CI to ignore apps/landing/** paths - Fix logo transparency (remove white background) across all apps - Recreate social-preview.png with SnapOtter branding - Update all docs URLs from GitHub Pages to docs.snapotter.com - Update VitePress config: light theme default, fix llms.txt paths - Add .vitepress/cache/ and .env.* to gitignore
202 lines
6.3 KiB
TypeScript
202 lines
6.3 KiB
TypeScript
import { detectFaces } from "@snapotter/ai";
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import { SMART_CROP_FACE_PRESETS } from "@snapotter/shared";
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import type { FastifyInstance } from "fastify";
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import sharp from "sharp";
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import { z } from "zod";
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import { resolveOutputFormat } from "../../lib/output-format.js";
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import { createToolRoute } from "../tool-factory.js";
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const settingsSchema = z
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.object({
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mode: z
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.enum(["subject", "face", "trim", "attention", "content"])
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.default("subject")
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.transform((v) => {
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if (v === "attention") return "subject" as const;
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if (v === "content") return "trim" as const;
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return v;
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}),
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strategy: z.enum(["attention", "entropy"]).default("attention"),
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width: z.number().int().positive().optional(),
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height: z.number().int().positive().optional(),
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padding: z.number().int().min(0).max(50).default(0),
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facePreset: z
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.enum(["closeup", "head-shoulders", "upper-body", "half-body"])
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.default("head-shoulders"),
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sensitivity: z.number().min(0).max(1).default(0.5),
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threshold: z.number().int().min(0).max(255).default(30),
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padToSquare: z.boolean().default(false),
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padColor: z.string().default("#ffffff"),
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targetSize: z.number().int().positive().optional(),
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quality: z.number().int().min(1).max(100).optional(),
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})
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.transform((s) => ({
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...s,
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mode: s.mode as "subject" | "face" | "trim",
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}));
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function clampRegion(
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left: number,
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top: number,
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cropW: number,
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cropH: number,
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imgW: number,
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imgH: number,
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) {
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const w = Math.min(cropW, imgW);
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const h = Math.min(cropH, imgH);
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let l = left;
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let t = top;
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if (l < 0) l = 0;
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if (t < 0) t = 0;
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if (l + w > imgW) l = imgW - w;
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if (t + h > imgH) t = imgH - h;
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return {
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left: Math.round(Math.max(0, l)),
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top: Math.round(Math.max(0, t)),
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width: Math.round(w),
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height: Math.round(h),
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};
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}
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async function processSubject(
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inputBuffer: Buffer,
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settings: z.output<typeof settingsSchema>,
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): Promise<Buffer> {
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const w = settings.width ?? 1080;
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const h = settings.height ?? 1080;
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const strategy =
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settings.strategy === "entropy" ? sharp.strategy.entropy : sharp.strategy.attention;
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if (settings.padding > 0) {
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const scale = 1 + settings.padding / 100;
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const oversizeW = Math.round(w * scale);
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const oversizeH = Math.round(h * scale);
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const oversize = await sharp(inputBuffer)
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.resize(oversizeW, oversizeH, { fit: "cover", position: strategy })
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.toBuffer();
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const extractLeft = Math.round((oversizeW - w) / 2);
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const extractTop = Math.round((oversizeH - h) / 2);
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return sharp(oversize)
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.extract({ left: extractLeft, top: extractTop, width: w, height: h })
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.toBuffer();
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}
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return sharp(inputBuffer).resize(w, h, { fit: "cover", position: strategy }).toBuffer();
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}
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async function processFace(
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inputBuffer: Buffer,
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settings: z.output<typeof settingsSchema>,
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): Promise<Buffer> {
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const result = await detectFaces(inputBuffer, { sensitivity: settings.sensitivity });
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if (result.facesDetected === 0) {
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return processSubject(inputBuffer, { ...settings, strategy: "attention" });
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}
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const meta = await sharp(inputBuffer).metadata();
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const imgW = meta.width ?? 1;
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const imgH = meta.height ?? 1;
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const targetW = settings.width ?? 1080;
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const targetH = settings.height ?? 1080;
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const faces = result.faces;
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const minX = Math.min(...faces.map((f) => f.x));
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const minY = Math.min(...faces.map((f) => f.y));
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const maxX = Math.max(...faces.map((f) => f.x + f.w));
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const maxY = Math.max(...faces.map((f) => f.y + f.h));
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const cx = (minX + maxX) / 2;
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const cy = (minY + maxY) / 2;
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const unionH = maxY - minY;
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const preset = SMART_CROP_FACE_PRESETS.find((p) => p.id === settings.facePreset);
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const multiplier = preset?.multiplier ?? 2.8;
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const aspectRatio = targetW / targetH;
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let cropH = unionH * multiplier * (1 + settings.padding / 100);
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let cropW = cropH * aspectRatio;
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if (cropW > imgW) {
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cropW = imgW;
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cropH = cropW / aspectRatio;
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}
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if (cropH > imgH) {
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cropH = imgH;
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cropW = cropH * aspectRatio;
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}
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const left = cx - cropW / 2;
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const top = cy - cropH / 2;
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const region = clampRegion(left, top, cropW, cropH, imgW, imgH);
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if (region.width < 1 || region.height < 1) {
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return processSubject(inputBuffer, { ...settings, strategy: "attention" });
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}
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const extracted = await sharp(inputBuffer).extract(region).toBuffer();
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return sharp(extracted).resize(targetW, targetH, { fit: "fill" }).toBuffer();
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}
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async function processTrim(
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inputBuffer: Buffer,
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settings: z.output<typeof settingsSchema>,
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): Promise<Buffer> {
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if (settings.padToSquare || settings.targetSize) {
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const trimmed = await sharp(inputBuffer)
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.trim({ threshold: settings.threshold })
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.toBuffer({ resolveWithObject: true });
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const w = trimmed.info.width;
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const h = trimmed.info.height;
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const target = settings.targetSize || Math.max(w, h);
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const padR = Math.round(Number.parseInt(settings.padColor.slice(1, 3), 16));
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const padG = Math.round(Number.parseInt(settings.padColor.slice(3, 5), 16));
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const padB = Math.round(Number.parseInt(settings.padColor.slice(5, 7), 16));
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return sharp(trimmed.data)
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.resize({
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width: target,
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height: target,
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fit: "contain",
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background: { r: padR, g: padG, b: padB, alpha: 1 },
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})
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.toBuffer();
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}
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return sharp(inputBuffer).trim({ threshold: settings.threshold }).toBuffer();
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}
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export function registerSmartCrop(app: FastifyInstance) {
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createToolRoute(app, {
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toolId: "smart-crop",
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settingsSchema,
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process: async (inputBuffer, settings, filename) => {
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const outputFormat = await resolveOutputFormat(inputBuffer, filename, settings.quality);
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let result: Buffer;
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if (settings.mode === "face") {
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result = await processFace(inputBuffer, settings);
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} else if (settings.mode === "trim") {
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result = await processTrim(inputBuffer, settings);
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} else {
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result = await processSubject(inputBuffer, settings);
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}
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result = await sharp(result)
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.toFormat(outputFormat.format, { quality: outputFormat.quality })
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.toBuffer();
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const stem = filename.replace(/\.[^.]+$/, "");
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const outputFilename = `${stem}_smartcrop.${outputFormat.extension}`;
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return { buffer: result, filename: outputFilename, contentType: outputFormat.contentType };
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},
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});
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}
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