MoGe-3 (VITG) โ€” MLX

MLX port of MoGe-3: fine-detail monocular geometry estimation with self-guided sparse volumetric refinement. Predicts metric point maps, depth maps, normal maps, valid-pixel masks, and camera intrinsics from a single image.

Converted with mlx-vlm from the official model.pt checkpoint (fp32).

Usage

from mlx_vlm import load
from mlx_vlm.models.moge3.generate import MoGe3Predictor, read_image

model, processor = load("mlx-community/moge-3-vitg-mlx-fp32")
predictor = MoGe3Predictor(model, processor)
output = predictor.infer(read_image("image.jpg"), resolution_level=9)
points, depth, mask = output["points"], output["depth"], output["mask"]
normal, intrinsics = output["normal"], output["intrinsics"]

Validated against the torch reference (CPU, fp32): identical valid-pixel masks and <0.2% median relative depth error.

Downloads last month
1
Safetensors
Model size
1B params
Tensor type
F32
ยท
MLX
Hardware compatibility
Log In to add your hardware

Quantized

Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support