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kevinqz/Depth-Anything-V2-Small-CoreAI
Depth-Anything-V2-Small-CoreAI is a depth estimation model from kevinqz. Use it for the depth estimation task on the model card, and read the license before you ship it in a product. It is set up for coreai. The card lists the license as apache-2.0.
Canonical: kevinqz/Depth-Anything-V2-Small-CoreAI — source of truth.
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Updated Jul 10, 2026
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From the Hugging Face model README
Canonical:
kevinqz/Depth-Anything-V2-Small-CoreAI— source of truth.
An Apple Core AI conversion of depth-anything/Depth-Anything-V2-Small-hf — a monocular depth estimator that maps a single RGB image to a per-pixel (inverse-)depth map. Produced by coreai-fabric and indexed by coreai-catalog.
Dense prediction, fully on-device. This is a single-forward dense predictor — RGB image (1×3×518×518) in, per-pixel depth (1×518×518) out, no loop. The host owns only image preprocessing (resize to a multiple of 14, ImageNet normalize) and any depth colormap for display.
| Field | Value |
|---|---|
| Parameters | 0.025B |
| Architecture | cnn/transformer |
| Capabilities | monocular-depth |
| Input | 1×3×518×518 |
| Output (depth) | 1×518×518 |
| Quantization / precision | none / float32 |
| On-disk size | 94 MB |
| Asset kind | single-graph dense predictor (image -> per-pixel depth) |
| assetVersion | 2.0 |
The bundle is a single static-size graph: pixel_values (1×3×518×518) in → predicted_depth (1×518×518) out. You supply the resize-to-multiple-of-14 + ImageNet normalization and any visualization/colormap in your host code (Swift or Python).
pip install coreai-catalog && coreai-catalog install depth-anything-v2-small
minimum_os v27,
so the on-device Swift runtime requires macOS/iOS 27+. A Mac on macOS 26 can
convert and inspect it but not run it on-device.coreai-fabric verify.| Field | Value |
|---|---|
| Base model | depth-anything/Depth-Anything-V2-Small-hf @ 5426e4f0f36572d16453bbda7a8389317b1bef99 |
| Converted by | models/depth_anything/export.py (version not reported) |
| Recipe | depth-anything-v2-small (recipe_source: fabric) |
| Precision / quantization | float32 / none |
| Conversion date | 2026-07-10 |
Machine-readable, in this repo:
parity-report.json ·
reproduce-manifest.json · LICENSE.
Weights licensed apache-2.0 — see the bundled LICENSE. This artifact is a converted derivative of the base model: its
weights were converted to Apple Core AI format. The conversion itself is
community work.
depth-anything-v2-small.aimodel pipeline that produced this asset.Community conversion. Not produced, hosted, or endorsed by Apple. Apple and Core AI are trademarks of Apple Inc., used here only to describe the target runtime/format.