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chore(colors): removing unreliable colors

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CarolinePascal
2026-06-10 19:46:04 +02:00
parent 22991ed69a
commit 21d158e066
1 changed files with 3 additions and 14 deletions
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src/lerobot/scripts/lerobot_dataset_viz.py
+3 -14
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@@ -62,7 +62,6 @@ local$ rerun rerun+http://IP:GRPC_PORT/proxy
""" """
import argparse import argparse
import colorsys
import gc import gc
import logging import logging
import time import time
@@ -91,16 +90,6 @@ def get_feature_names(dataset: LeRobotDataset, key: str) -> list[str]:
return [f"{key}_{d}" for d in range(feature["shape"][-1])] return [f"{key}_{d}" for d in range(feature["shape"][-1])]
def get_sequential_colors(num_dims: int) -> list[list[int]]:
"""Return a deterministic list of distinct RGB colors, one per dimension."""
colors = []
for d in range(num_dims):
hue = d / max(num_dims, 1)
r, g, b = colorsys.hsv_to_rgb(hue, 0.7, 0.9)
colors.append([int(r * 255), int(g * 255), int(b * 255)])
return colors
def to_hwc_uint8_numpy(chw_float32_torch: torch.Tensor) -> np.ndarray: def to_hwc_uint8_numpy(chw_float32_torch: torch.Tensor) -> np.ndarray:
assert chw_float32_torch.dtype == torch.float32 assert chw_float32_torch.dtype == torch.float32
assert chw_float32_torch.ndim == 3 assert chw_float32_torch.ndim == 3
@@ -114,7 +103,7 @@ def build_blueprint_from_dataset(dataset: LeRobotDataset):
"""Build a Rerun blueprint laying out camera images and time series for the given dataset. """Build a Rerun blueprint laying out camera images and time series for the given dataset.
Camera images and scalar signals (action, state, reward, done, success) are arranged in a grid. Camera images and scalar signals (action, state, reward, done, success) are arranged in a grid.
The per-dimension series names and colors for ``action`` and ``state`` are applied directly The per-dimension series names for ``action`` and ``state`` are applied directly
via blueprint overrides. via blueprint overrides.
""" """
import rerun as rr import rerun as rr
@@ -122,11 +111,11 @@ def build_blueprint_from_dataset(dataset: LeRobotDataset):
views = [rrb.Spatial2DView(origin=key, name=key) for key in dataset.meta.camera_keys] views = [rrb.Spatial2DView(origin=key, name=key) for key in dataset.meta.camera_keys]
# Style multi-dimensional signals (action, state) with per-dimension names and colors. # Style multi-dimensional signals (action, state) with per-dimension names.
for origin, key in ((ACTION, ACTION), ("state", OBS_STATE)): for origin, key in ((ACTION, ACTION), ("state", OBS_STATE)):
if key in dataset.features: if key in dataset.features:
names = get_feature_names(dataset, key) names = get_feature_names(dataset, key)
styling = rr.SeriesLines(names=names, colors=get_sequential_colors(len(names))) styling = rr.SeriesLines(names=names)
views.append(rrb.TimeSeriesView(origin=origin, name=origin, overrides={origin: styling})) views.append(rrb.TimeSeriesView(origin=origin, name=origin, overrides={origin: styling}))
for key in (DONE, REWARD, "next.success"): for key in (DONE, REWARD, "next.success"):
if key in dataset.features: if key in dataset.features: