WhereTimeGoes vs ML Data Factory

WhereTimeGoes helps you build a clear accounting of your day without juggling alarms, spreadsheets, and copy-paste reports. Set the time range you want to track, then get regular notifications (e.g. every 30 minutes) asking what happened in each interval. Entries are free-form, so you can type simple notes like "work", "gym, steam room", "driving to grocery store", or "planning, 20 min email". The app stores everything locally and turns your entries into a spreadsheet-style timeline you can edit later. Reports help you see the patterns behind the raw log. Detailed reports are calculated directly from your entries. Medium and broad reports can group your activities, then score categories against your goal so you can see what helped, what hurt, and what to reduce first. Key features: - Interval notifications for free-form time logging - Editable spreadsheet-style daily timeline - Sleep logging and batch cell editing - Daily, weekly, and monthly report views - Goal-weighted categories with positive and negative impact scores - Pie charts and heat maps - CSV export for analysis in Numbers, Excel, or Google Sheets - Local-first storage on your device - User-provided OpenAI API key stored in Keychain for report generation WhereTimeGoes is for people who want a low-friction way to understand their time, notice waste, and make better decisions tomorrow.

ML Data Factory is a professional-grade mobile utility engineered to bridge the gap between raw video footage and the high-quality datasets required for machine learning. Designed for data engineers, sports analysts, and AI researchers, this app allows you to curate, manufacture, and package machine learning datasets entirely from your iPhone or iPad. Stop wasting time with bulky desktop software. Whether you are in the field or at your desk, ML Data Factory provides a streamlined, high-throughput pipeline to transform raw video into structured, AI-ready training data. Key Features: Precision Data Pipeline: Seamlessly ingest raw video from iCloud, the local Files app, or your Photo Library. Support for bulk-uploading allows you to queue multiple videos for efficient, uninterrupted processing. Direct-Link Ingestion: Paste direct video URLs to stream and download high-quality footage directly into your processing queue. Frame-Accurate Scrubbing: Utilize high-precision seeking controls to pinpoint the exact millisecond of an action. Whether you are analyzing a sports swing or a manufacturing process, you have full control with frame-by-frame navigation. ML-Ready Visual Guides: Built-in 224x224 crop guides ensure your visual subjects are perfectly framed for popular machine learning models (e.g., ResNet, MobileNet), ensuring data consistency before you ever snap a frame. Dynamic Dataset Labeling: Create, manage, and toggle custom categories on the fly. Organize your dataset into structured folders that match your specific training labels. Customizable Capture Length: Adjust your capture window dynamically—choose between 30, 60, 90, 120, or 150 frames to match the specific needs of your ML model's temporal requirements. One-Tap Manifest Export: With a single tap, the app compiles your categorized clips into a structured dataset_manifest.json and bundles everything into a single .zip archive. Easily AirDrop or transfer your entire, ready-to-train dataset to your workstation for immediate use in Create ML, PyTorch, or TensorFlow. Technical Specifications: High-Speed I/O: Built on the AVFoundation framework for efficient, asynchronous video processing and extraction. Optimized Performance: Fully compliant with modern iOS 18+ standards for maximum stability and performance on the latest hardware. Data Integrity: All dataset operations are performed using atomic write protocols to ensure no data is corrupted or lost during the extraction and zipping process. User-Centric Design: High-contrast, dark-themed industrial interface designed for high-focus professional environments.