| |
| |
| """Tenstorrent Blackhole port of the HaMeR per-frame regressor. |
| |
| Python API (see ``PYTHON.md``):: |
| |
| from hamer import HamerModel |
| |
| with HamerModel.from_pretrained(device_id=0) as model: |
| hand = model("frame.jpg", bbox=[x1, y1, x2, y2], is_right=True) |
| |
| Lower-level pieces (unchanged):: |
| |
| from hamer import Hamer, build_reference, build_from_reference, sample_input |
| from hamer import load_hamer_checkpoint |
| from hamer.preprocess import preprocess |
| |
| Importing the package does not import ``ttnn``; the device stack loads when a model is built. |
| """ |
| from __future__ import annotations |
|
|
| import importlib |
| from typing import Any |
|
|
| from .api import HamerModel, HandPrediction, apply_served_config, load_reference, open_device |
|
|
| __version__ = "0.1.0" |
|
|
| _LAZY = { |
| "Hamer": ".reference", |
| "HamerConfig": ".reference", |
| "build_reference": ".reference", |
| "sample_input": ".reference", |
| "TtHamer": ".model", |
| "build_from_reference": ".model", |
| "load_hamer_checkpoint": ".checkpoint", |
| } |
|
|
| __all__ = [ |
| "HamerModel", |
| "HandPrediction", |
| "open_device", |
| "load_reference", |
| "apply_served_config", |
| *_LAZY, |
| ] |
|
|
|
|
| def __getattr__(name: str) -> Any: |
| mod = _LAZY.get(name) |
| if mod is None: |
| raise AttributeError(f"module 'hamer' has no attribute {name!r}") |
| value = getattr(importlib.import_module(mod, __name__), name) |
| globals()[name] = value |
| return value |
|
|
|
|
| def __dir__(): |
| return sorted(set(globals()) | set(_LAZY)) |
|
|
