bundle pytorch model
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@ -1,3 +1,5 @@
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!dist/vibeui.pt
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runs
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requirements.txt
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venv
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@ -19,6 +19,9 @@ RUN apt-get update -y && \
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# Install IPFS Kubo
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COPY --from=ipfs/kubo:v0.36.0 /usr/local/bin/ipfs /usr/local/bin/ipfs
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# Include the vibeui pytorch model
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COPY ./dist/vibeui.pt /app/dist/vibeui.pt
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# Copy and install dependencies
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COPY package.json package-lock.json ./
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RUN npm install --ignore-scripts=false --foreground-scripts --verbose
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@ -8,7 +8,7 @@ dotenvx.config({ path: ['../../.env.development'] })
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const EnvSchema = z.object({
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NODE_ENV: z.enum(['development', 'production', 'test']),
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VENV: z.string(),
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VENV: z.string().default('/app/venv'),
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PORT: z.coerce.number().default(3000),
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DATABASE_URL: z.string().url(),
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ORIGIN: z.string(),
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@ -4,51 +4,15 @@ import { withAccelerate } from "@prisma/extension-accelerate";
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import { getOrDownloadAsset } from "../utils/cache";
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import { env } from "../config/env";
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import { getS3Client, uploadFile } from "../utils/s3";
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import { nanoid } from "nanoid";
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import { existsSync, rmSync } from "node:fs";
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import { join, basename, extname } from "node:path";
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import { readFile, writeFile, readdir } from 'node:fs/promises';
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import yaml from 'js-yaml';
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import { getNanoSpawn } from "../utils/nanoSpawn";
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import which from "which";
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import * as ort from 'onnxruntime-node';
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import { inference, loadDataYaml } from "../utils/vibeui";
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import { ffprobe } from "../utils/vibeui";
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import { inference } from "../utils/vibeui";
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import { preparePython } from "../utils/python";
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import { generateActions2, buildFunscript } from "../utils/funscripts";
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import { buildFunscript } from "../utils/funscripts";
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interface Payload {
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vodId: string;
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}
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// interface Detection {
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// startFrame: number;
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// endFrame: number;
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// className: string;
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// }
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// interface DataYaml {
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// path: string;
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// train: string;
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// val: string;
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// names: Record<string, string>;
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// }
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// interface FunscriptAction {
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// at: number;
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// pos: number;
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// }
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// interface Funscript {
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// version: string;
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// actions: FunscriptAction[];
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// }
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// interface ClassPositionMap {
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// [className: string]: number | 'pattern';
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// }
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const prisma = new PrismaClient().$extends(withAccelerate());
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@ -63,206 +27,6 @@ function assertPayload(payload: any): asserts payload is Payload {
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// export async function buildFunscript(
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// helpers: Helpers,
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// predictionOutput: string,
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// videoPath: string
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// ): Promise<string> {
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// const labelDir = join(predictionOutput, 'labels');
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// const yamlPath = join(predictionOutput, 'data.yaml');
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// const outputPath = join(process.env.CACHE_ROOT ?? '/tmp', `${nanoid()}.funscript`);
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// helpers.logger.info('Starting Funscript generation');
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// try {
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// const data = await loadDataYaml(join(env.VIBEUI_DIR, 'data.yaml'))
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// const classPositionMap = await loadClassPositionMap(data, helpers);
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// const { fps, totalFrames } = await loadVideoMetadata(videoPath, helpers);
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// const detectionSegments = await processLabelFiles(labelDir, helpers, data);
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// const totalDurationMs = Math.floor((totalFrames / fps) * 1000);
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// const actions = generateActions2(totalDurationMs, fps, detectionSegments, classPositionMap);
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// await writeFunscript(outputPath, actions, helpers);
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// return outputPath;
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// } catch (error) {
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// helpers.logger.error(`Error generating Funscript: ${error instanceof Error ? error.message : 'Unknown error'}`);
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// throw error;
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// }
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// }
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// async function loadClassPositionMap(data: DataYaml, helpers: Helpers): Promise<ClassPositionMap> {
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// try {
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// if (
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// !data ||
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// typeof data !== 'object' ||
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// !('names' in data) ||
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// typeof data.names !== 'object' ||
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// data.names === null ||
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// Object.keys(data.names).length === 0
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// ) {
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// throw new Error('Invalid data.yaml: "names" field is missing, not an object, or empty');
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// }
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// const positionMap: ClassPositionMap = {
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// ControlledByTipper: 50,
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// ControlledByTipperHigh: 80,
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// ControlledByTipperLow: 20,
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// ControlledByTipperMedium: 50,
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// ControlledByTipperUltrahigh: 95,
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// Ring1: 30,
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// Ring2: 40,
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// Ring3: 50,
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// Ring4: 60,
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// Earthquake: 'pattern',
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// Fireworks: 'pattern',
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// Pulse: 'pattern',
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// Wave: 'pattern',
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// Pause: 0,
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// RandomTime: 70,
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// HighLevel: 80,
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// LowLevel: 20,
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// MediumLevel: 50,
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// UltraHighLevel: 95
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// };
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// const names = Object.values(data.names);
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// for (const name of names) {
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// if (typeof name !== 'string' || name.trim() === '') {
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// helpers.logger.info(`Skipping invalid class name: ${name}`);
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// continue;
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// }
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// if (!(name in positionMap)) {
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// helpers.logger.info(`No position mapping for class "${name}", defaulting to 0`);
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// positionMap[name] = 0;
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// }
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// }
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// helpers.logger.info(`Loaded class position map: ${JSON.stringify(positionMap)}`);
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// return positionMap;
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// } catch (error) {
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// helpers.logger.error(`Error loading data.yaml: ${error instanceof Error ? error.message : 'Unknown error'}`);
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// throw error;
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// }
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// }
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// function generatePatternPositions(startMs: number, durationMs: number, className: string, fps: number): FunscriptAction[] {
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// const actions: FunscriptAction[] = [];
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// const frameDurationMs = 1000 / fps;
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// const totalFrames = Math.floor(durationMs / frameDurationMs);
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// const intervalMs = 100;
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// for (let timeMs = 0; timeMs < durationMs; timeMs += intervalMs) {
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// const progress = timeMs / durationMs;
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// let pos = 0;
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// switch (className) {
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// case 'Pulse':
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// pos = Math.round(50 * Math.sin(progress * 2 * Math.PI));
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// break;
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// case 'Wave':
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// pos = Math.round(50 + 50 * Math.sin(progress * 2 * Math.PI));
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// break;
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// case 'Fireworks':
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// pos = Math.random() > 0.5 ? 80 : 0;
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// break;
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// case 'Earthquake':
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// pos = Math.round(90 * Math.sin(progress * 4 * Math.PI) + (Math.random() - 0.5) * 10);
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// pos = Math.max(0, Math.min(90, pos));
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// break;
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// }
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// actions.push({ at: startMs + timeMs, pos });
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// }
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// return actions;
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// }
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// async function loadVideoMetadata(videoPath: string, helpers: Helpers) {
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// const { fps, frames: totalFrames } = await ffprobe(videoPath);
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// helpers.logger.info(`Video metadata: fps=${fps}, frames=${totalFrames}`);
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// return { fps, totalFrames };
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// }
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// async function processLabelFiles(labelDir: string, helpers: Helpers, data: DataYaml): Promise<Detection[]> {
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// const labelFiles = (await readdir(labelDir)).filter(file => file.endsWith('.txt'));
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// const detections: Map<number, Detection[]> = new Map();
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// const names = data.names;
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// for (const file of labelFiles) {
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// const match = file.match(/(\d+)\.txt$/);
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// if (!match) {
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// helpers.logger.info(`Skipping invalid filename: ${file}`);
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// continue;
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// }
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// const frameIndex = parseInt(match[1], 10);
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// if (isNaN(frameIndex)) {
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// helpers.logger.info(`Skipping invalid frame index from filename: ${file}`);
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// continue;
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// }
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// const content = await readFile(join(labelDir, file), 'utf8');
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// const lines = content.trim().split('\n');
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// const frameDetections: Detection[] = [];
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// let maxConfidence = 0;
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// let selectedClassIndex = -1;
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// for (const line of lines) {
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// const parts = line.trim().split(/\s+/);
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// if (parts.length < 6) continue;
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// const classIndex = parseInt(parts[0], 10);
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// const confidence = parseFloat(parts[5]);
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// if (isNaN(classIndex) || isNaN(confidence)) continue;
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// if (confidence >= 0.7 && confidence > maxConfidence) {
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// maxConfidence = confidence;
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// selectedClassIndex = classIndex;
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// }
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// }
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// if (maxConfidence > 0) {
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// const className = (data.names as Record<string, string>)[selectedClassIndex.toString()];
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// if (className) {
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// frameDetections.push({ startFrame: frameIndex, endFrame: frameIndex, className });
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// }
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// }
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// if (frameDetections.length > 0) {
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// detections.set(frameIndex, frameDetections);
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// }
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// }
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// // Merge overlapping detections into continuous segments
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// const detectionSegments: Detection[] = [];
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// let currentDetection: Detection | null = null;
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// for (const [frameIndex, frameDetections] of detections.entries()) {
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// for (const detection of frameDetections) {
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// if (!currentDetection || currentDetection.className !== detection.className) {
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// if (currentDetection) detectionSegments.push(currentDetection);
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// currentDetection = { ...detection, endFrame: frameIndex };
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// } else {
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// currentDetection.endFrame = frameIndex;
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// }
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// }
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// }
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// if (currentDetection) detectionSegments.push(currentDetection);
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// return detectionSegments;
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// }
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// async function writeFunscript(outputPath: string, actions: FunscriptAction[], helpers: Helpers) {
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// const funscript: Funscript = { version: '1.0', actions };
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// await writeFile(outputPath, JSON.stringify(funscript, null, 2));
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// helpers.logger.info(`Funscript generated: ${outputPath} (${actions.length} actions)`);
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// }
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const createFunscript: Task = async (payload: any, helpers: Helpers) => {
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assertPayload(payload);
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const { vodId } = payload;
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