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fix(studio): harden runtime integration and dependency defaults

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Stabilize studio publish/visualization flow and tighten export behavior while aligning project dependencies with the monorepo runtime expectations.
This commit is contained in:
crosstyan
2026-03-03 17:59:56 +08:00
parent 00fcda4fe3
commit 967a10c10e
7 changed files with 122 additions and 87 deletions
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AGENTS.md
+2 -2
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@@ -11,7 +11,7 @@ Use it as the default playbook for commands, conventions, and safety checks.
- Package/runtime tool: `uv`
Critical source-of-truth rule:
- `opengait/demo` is an implementation layer and may contain project-specific behavior.
- `opengait-studio/opengait_studio` is an implementation layer and may contain project-specific behavior.
- When asked to “refer to the paper” or verify methodology, use the paper and official citations as ground truth.
- Do not treat demo/runtime behavior as proof of paper method unless explicitly cited by the paper.
@@ -20,7 +20,7 @@ Critical source-of-truth rule:
Install dependencies with uv:
```bash
uv sync --extra torch
uv sync
```
Notes from `pyproject.toml`:
README.md
+1 -1
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@@ -79,7 +79,7 @@ See [here](https://github.com/jdyjjj/All-in-One-Gait) for details.
### Quick Start (uv)
```bash
# Install dependencies
uv sync --extra torch
uv sync
# Train
CUDA_VISIBLE_DEVICES=0,1 uv run python -m torch.distributed.launch --nproc_per_node=2 opengait/main.py --cfgs ./configs/baseline/baseline.yaml --phase train
opengait-studio/opengait_studio/output.py
+54 -8
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@@ -9,6 +9,7 @@ Provides pluggable result publishing:
from __future__ import annotations
import asyncio
from concurrent.futures import CancelledError, Future
import json
import logging
import nats
@@ -181,10 +182,38 @@ class NatsPublisher:
def _stop_background_loop(self) -> None:
"""Stop the background event loop and thread."""
with self._lock:
if self._loop is not None and self._loop.is_running():
_ = self._loop.call_soon_threadsafe(self._loop.stop)
if self._thread is not None and self._thread.is_alive():
self._thread.join(timeout=2.0)
loop = self._loop
thread = self._thread
if loop is not None and loop.is_running():
try:
async def _cancel_pending_tasks() -> None:
current = asyncio.current_task()
pending = [
task
for task in asyncio.all_tasks()
if task is not current and not task.done()
]
for task in pending:
_ = task.cancel()
if pending:
_ = await asyncio.gather(*pending, return_exceptions=True)
cancel_future = asyncio.run_coroutine_threadsafe(
_cancel_pending_tasks(),
loop,
)
cancel_future.result(timeout=2.0)
except (RuntimeError, OSError, TimeoutError, CancelledError):
pass
finally:
_ = loop.call_soon_threadsafe(loop.stop)
if thread is not None and thread.is_alive():
thread.join(timeout=2.0)
with self._lock:
self._loop = None
self._thread = None
@@ -204,7 +233,12 @@ class NatsPublisher:
if not self._start_background_loop():
return False
future: Future[_NatsClient] | None = None
try:
loop = self._loop
if loop is None:
logger.warning("Background event loop unavailable for NATS connection")
return False
async def _connect() -> _NatsClient:
nc = await nats.connect(self._nats_url) # pyright: ignore[reportUnknownMemberType]
@@ -213,12 +247,21 @@ class NatsPublisher:
# Run connection in background loop
future = asyncio.run_coroutine_threadsafe(
_connect(),
self._loop, # pyright: ignore[reportArgumentType]
loop,
)
self._nc = future.result(timeout=10.0)
self._connected = True
logger.info(f"Connected to NATS at {self._nats_url}")
return True
except TimeoutError as e:
if future is not None:
_ = future.cancel()
try:
_ = future.result(timeout=1.0)
except (TimeoutError, CancelledError, RuntimeError, OSError):
pass
logger.warning("Timed out connecting to NATS at %s: %s", self._nats_url, e)
return False
except (RuntimeError, OSError, TimeoutError) as e:
logger.warning(f"Failed to connect to NATS at {self._nats_url}: {e}")
return False
@@ -260,16 +303,19 @@ class NatsPublisher:
exc = fut.exception()
except (RuntimeError, OSError) as callback_error:
logger.warning(f"NATS publish callback failed: {callback_error}")
self._connected = False
with self._lock:
self._connected = False
return
if exc is not None:
logger.warning(f"Failed to publish to NATS: {exc}")
self._connected = False
with self._lock:
self._connected = False
future.add_done_callback(_on_done)
except (RuntimeError, OSError, ValueError, TypeError) as e:
logger.warning(f"Failed to schedule NATS publish: {e}")
self._connected = False
with self._lock:
self._connected = False
def close(self) -> None:
"""Close NATS connection."""
opengait-studio/opengait_studio/pipeline.py
+37 -7
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@@ -1,7 +1,9 @@
from __future__ import annotations
from collections.abc import Callable
import copy
from contextlib import suppress
import inspect
import logging
from pathlib import Path
import time
@@ -146,6 +148,8 @@ class ScoliosisPipeline:
_visualizer: OpenCVVisualizer | None
_last_viz_payload: _VizPayload | None
_frame_pacer: _FramePacer | None
_visualizer_accepts_pose_data: bool | None
_visualizer_signature_owner: object | None
def __init__(
self,
@@ -205,6 +209,31 @@ class ScoliosisPipeline:
self._visualizer = None
self._last_viz_payload = None
self._frame_pacer = _FramePacer(target_fps) if target_fps is not None else None
self._visualizer_accepts_pose_data = None
self._visualizer_signature_owner = None
def _detect_visualizer_pose_kwarg(self) -> bool:
visualizer = self._visualizer
if visualizer is None:
return False
if (
self._visualizer_signature_owner is visualizer
and self._visualizer_accepts_pose_data is not None
):
return self._visualizer_accepts_pose_data
update_fn = getattr(visualizer, "update", None)
if update_fn is None or not callable(update_fn):
self._visualizer_signature_owner = visualizer
self._visualizer_accepts_pose_data = False
return False
try:
signature = inspect.signature(update_fn)
accepts_pose_data = "pose_data" in signature.parameters
except (ValueError, TypeError):
accepts_pose_data = False
self._visualizer_signature_owner = visualizer
self._visualizer_accepts_pose_data = accepts_pose_data
return accepts_pose_data
@staticmethod
def _extract_int(meta: dict[str, object], key: str, fallback: int) -> int:
@@ -459,7 +488,7 @@ class ScoliosisPipeline:
viz_payload = None
try:
viz_payload = self.process_frame(frame_u8, metadata)
except (RuntimeError, ValueError, TypeError, OSError) as frame_error:
except (RuntimeError, ValueError, OSError) as frame_error:
logger.warning(
"Skipping frame %d due to processing error: %s",
frame_idx,
@@ -474,6 +503,9 @@ class ScoliosisPipeline:
viz_payload_dict = cast(_VizPayload, viz_payload)
cached: _VizPayload = {}
for k, v in viz_payload_dict.items():
if k == "pose" and isinstance(v, dict):
cached[k] = cast(dict[str, object], copy.deepcopy(v))
continue
copy_method = cast(
Callable[[], object] | None, getattr(v, "copy", None)
)
@@ -531,8 +563,7 @@ class ScoliosisPipeline:
confidence = None
pose_data = None
# Try keyword arg for pose_data (backward compatible with old signatures)
try:
if self._detect_visualizer_pose_kwarg():
keep_running = self._visualizer.update(
frame_u8,
bbox,
@@ -546,8 +577,7 @@ class ScoliosisPipeline:
ema_fps,
pose_data=pose_data,
)
except TypeError:
# Fallback for legacy visualizers that don't accept pose_data
else:
keep_running = self._visualizer.update(
frame_u8,
bbox,
@@ -676,7 +706,7 @@ class ScoliosisPipeline:
"frame": pa.array(frames, type=pa.int64()),
"track_id": pa.array(track_ids, type=pa.int64()),
"timestamp_ns": pa.array(timestamps, type=pa.int64()),
"silhouette": pa.array(silhouettes, type=pa.list_(pa.float64())),
"silhouette": pa.array(silhouettes, type=pa.list_(pa.float32())),
}
)
@@ -746,7 +776,7 @@ class ScoliosisPipeline:
track_ids.append(result["track_id"])
labels.append(result["label"])
confidences.append(result["confidence"])
windows.append(result["window"])
windows.append(int(result["window"]))
timestamps.append(result["timestamp_ns"])
table = pa.table(
opengait-studio/opengait_studio/visualizer.py
+21 -55
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@@ -50,45 +50,24 @@ ImageArray = NDArray[np.uint8]
# COCO-format skeleton connections (17 keypoints)
# Connections are pairs of keypoint indices
SKELETON_CONNECTIONS: list[tuple[int, int]] = [
(0, 1), # nose -> left_eye
(0, 2), # nose -> right_eye
(1, 3), # left_eye -> left_ear
(2, 4), # right_eye -> right_ear
(5, 6), # left_shoulder -> right_shoulder
(5, 7), # left_shoulder -> left_elbow
(7, 9), # left_elbow -> left_wrist
(6, 8), # right_shoulder -> right_elbow
(0, 1), # nose -> left_eye
(0, 2), # nose -> right_eye
(1, 3), # left_eye -> left_ear
(2, 4), # right_eye -> right_ear
(5, 6), # left_shoulder -> right_shoulder
(5, 7), # left_shoulder -> left_elbow
(7, 9), # left_elbow -> left_wrist
(6, 8), # right_shoulder -> right_elbow
(8, 10), # right_elbow -> right_wrist
(11, 12), # left_hip -> right_hip
(11, 12), # left_hip -> right_hip
(5, 11), # left_shoulder -> left_hip
(6, 12), # right_shoulder -> right_hip
(11, 13), # left_hip -> left_knee
(13, 15), # left_knee -> left_ankle
(12, 14), # right_hip -> right_knee
(14, 16), # right_knee -> right_ankle
(11, 13), # left_hip -> left_knee
(13, 15), # left_knee -> left_ankle
(12, 14), # right_hip -> right_knee
(14, 16), # right_knee -> right_ankle
]
# Keypoint names for COCO format (17 keypoints)
KEYPOINT_NAMES: list[str] = [
"nose", "left_eye", "right_eye", "left_ear", "right_ear",
"left_shoulder", "right_shoulder", "left_elbow", "right_elbow",
"left_wrist", "right_wrist", "left_hip", "right_hip",
"left_knee", "right_knee", "left_ankle", "right_ankle"
]
# Joints where angles are typically calculated (for scoliosis/ gait analysis)
ANGLE_JOINTS: list[tuple[int, int, int]] = [
(5, 7, 9), # left_shoulder -> left_elbow -> left_wrist
(6, 8, 10), # right_shoulder -> right_elbow -> right_wrist
(7, 5, 11), # left_elbow -> left_shoulder -> left_hip
(8, 6, 12), # right_elbow -> right_shoulder -> right_hip
(5, 11, 13), # left_shoulder -> left_hip -> left_knee
(6, 12, 14), # right_shoulder -> right_hip -> right_knee
(11, 13, 15),# left_hip -> left_knee -> left_ankle
(12, 14, 16),# right_hip -> right_knee -> right_ankle
]
class OpenCVVisualizer:
def __init__(self) -> None:
@@ -210,7 +189,7 @@ class OpenCVVisualizer:
if pose_data is None:
return
keypoints_obj = pose_data.get('keypoints')
keypoints_obj = pose_data.get("keypoints")
if keypoints_obj is None:
return
@@ -222,7 +201,7 @@ class OpenCVVisualizer:
h, w = frame.shape[:2]
# Get confidence scores if available
confidence_obj = pose_data.get('confidence')
confidence_obj = pose_data.get("confidence")
confidences = (
np.asarray(confidence_obj, dtype=np.float32)
if confidence_obj is not None
@@ -267,7 +246,7 @@ class OpenCVVisualizer:
if pose_data is None:
return
angles_obj = pose_data.get('angles')
angles_obj = pose_data.get("angles")
if angles_obj is None:
return
@@ -467,12 +446,10 @@ class OpenCVVisualizer:
def _prepare_segmentation_view(
self,
mask_raw: ImageArray | None,
_mask_raw: ImageArray | None,
silhouette: NDArray[np.float32] | None,
bbox: BBoxXYXY | None,
_bbox: BBoxXYXY | None,
) -> ImageArray:
_ = mask_raw
_ = bbox
return self._prepare_normalized_view(silhouette)
def _fit_gray_to_display(
@@ -661,20 +638,7 @@ class OpenCVVisualizer:
y_pos = h - 8
y_top = max(0, h - MODE_LABEL_PAD)
_ = cv2.rectangle(
image,
(0, y_top),
(w, h),
COLOR_DARK_GRAY,
-1,
)
_ = cv2.rectangle(
image,
(x_pos - 6, y_pos - text_height - 6),
(x_pos + text_width + 8, y_pos + 6),
COLOR_DARK_GRAY,
-1,
)
_ = cv2.rectangle(image, (0, y_top), (w, h), COLOR_DARK_GRAY, -1)
# Draw text
_ = cv2.putText(
@@ -706,9 +670,11 @@ class OpenCVVisualizer:
Args:
frame: Input frame (H, W, C) uint8
bbox: Bounding box in XYXY format (x1, y1, x2, y2) or None
bbox_mask: Bounding box in mask coordinates (x1, y1, x2, y2) or None
track_id: Tracking ID
mask_raw: Raw binary mask (H, W) uint8 or None
silhouette: Normalized silhouette (64, 44) float32 [0,1] or None
segmentation_input: Windowed silhouette stack for model input visualization
label: Classification label or None
confidence: Classification confidence [0,1] or None
fps: Current FPS
pyproject.toml
+2 -5
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@@ -7,6 +7,8 @@ name = "opengait"
version = "0.0.0"
requires-python = ">=3.10"
dependencies = [
"torch>=2.0",
"torchvision",
"pyyaml",
"tensorboard",
"opencv-python",
@@ -24,10 +26,6 @@ dependencies = [
]
[project.optional-dependencies]
torch = [
"torch>=1.10",
"torchvision",
]
parquet = [
"pyarrow",
]
@@ -45,7 +43,6 @@ include = ["opengait", "opengait.*", "opengait_studio", "opengait_studio.*"]
dev = [
"basedpyright>=1.38.1",
"pytest",
"nats-py",
"ultralytics",
"jaxtyping",
"beartype",
uv.lock
Generated
+5 -9
View File
@@ -1747,6 +1747,8 @@ dependencies = [
{ name = "scikit-learn", version = "1.7.2", source = { registry = "https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/" }, marker = "python_full_version < '3.11'" },
{ name = "scikit-learn", version = "1.8.0", source = { registry = "https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/" }, marker = "python_full_version >= '3.11'" },
{ name = "tensorboard" },
{ name = "torch" },
{ name = "torchvision" },
{ name = "tqdm" },
]
@@ -1754,10 +1756,6 @@ dependencies = [
parquet = [
{ name = "pyarrow" },
]
torch = [
{ name = "torch" },
{ name = "torchvision" },
]
wandb = [
{ name = "wandb" },
]
@@ -1769,7 +1767,6 @@ dev = [
{ name = "click" },
{ name = "jaxtyping", version = "0.3.7", source = { registry = "https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/" }, marker = "python_full_version < '3.11'" },
{ name = "jaxtyping", version = "0.3.9", source = { registry = "https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple/" }, marker = "python_full_version >= '3.11'" },
{ name = "nats-py" },
{ name = "pytest" },
{ name = "ultralytics" },
]
@@ -1790,12 +1787,12 @@ requires-dist = [
{ name = "pyyaml" },
{ name = "scikit-learn" },
{ name = "tensorboard" },
{ name = "torch", marker = "extra == 'torch'", specifier = ">=1.10" },
{ name = "torchvision", marker = "extra == 'torch'" },
{ name = "torch", specifier = ">=2.0" },
{ name = "torchvision" },
{ name = "tqdm" },
{ name = "wandb", marker = "extra == 'wandb'" },
]
provides-extras = ["torch", "parquet", "wandb"]
provides-extras = ["parquet", "wandb"]
[package.metadata.requires-dev]
dev = [
@@ -1803,7 +1800,6 @@ dev = [
{ name = "beartype" },
{ name = "click" },
{ name = "jaxtyping" },
{ name = "nats-py" },
{ name = "pytest" },
{ name = "ultralytics" },
]