🌟 Summary Ultralytics 8.4.123 expands depth-estimation dataset compatibility, allowing standard scaled PNG and floating-point NPY depth maps to be used directly across training, NDJSON conversion, and Ultralytics Platform workflows. 🚀 📊 Key Changes 🗂️ Broader depth format support Accepts plain 16-bit grayscale PNG depth maps. Adds support for floating-point .npy depth maps with values stored in meters. PNG files no longer require Ultralytics-specific embedded metadata. ⚙️ Configurable depth scaling Adds the optional depth_scale dataset YAML field. Defaults to 1000, meaning PNG values are interpreted as millimeters. Supports datasets with other conventions, such as KITTI (256) and Virtual KITTI 2 (100). 🔗 Improved dataset pairing and validation Depth files are matched by filename stem in parallel images/ and depth/ directories. PNG files are preferred, with automatic fallback to NPY files. Depth maps may use a smaller resolution than RGB images when their aspect ratios match. Invalid values, including zero, NaN, and infinity, are safely handled. 📥 NDJSON depth dataset support Depth records now only require a paired depth.url. Dataset-level depth_scale is preserved when converting NDJSON to YOLO format. Large downloads are processed in batches to reduce memory usage. ☁️ Ultralytics Platform integration Depth datasets can now be uploaded, exported, and used for training on the Platform. NDJSON exports include the depth task, scaling configuration, and paired depth URLs. Depth estimation is now fully listed among the Platform's supported task types. 🧰 Dataset configurations updated Built-in depth datasets now preserve their native storage scales instead of converting everything to meter-based metadata PNGs. Documentation and tests were updated for ARKitScenes, DIODE, KITTI, TartanAir, Virtual KITTI 2, Depth8, and other depth datasets. 🎯 Purpose & Impact ✅ Easier dataset adoption: Existing depth datasets can be used with less preprocessing and fewer custom conversion scripts. 📦 Simpler, more portable files: Plain PNG and NPY formats work with common tools and do not depend on special PNG metadata. 🎯 More accurate dataset handling: Dataset-specific scales preserve the intended precision and depth range. 🚀 End-to-end depth workflows: Users can now prepare, upload, convert, and train depth datasets through the Ultralytics Platform. ⚠️ Migration consideration: Older self-describing Ultralytics depth PNGs that rely on embedded metadata may need to be converted to the new scaled PNG format. See the depth dataset format documentation. What's Changed Accept existing depth dataset formats by @glenn-jocher in https://github.com/ultralytics/ultralytics/pull/25859 Full Changelog: https://github.com/ultralytics/ultralytics/compare/v8.4.122...v8.4.123