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# Copyright 2026 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Tests for streaming video encoding and hardware-accelerated encoding."""
import queue
import threading
from unittest.mock import patch
import av
import numpy as np
import pytest
from lerobot.datasets.video_utils import (
VALID_VIDEO_CODECS,
StreamingVideoEncoder,
_CameraEncoderThread,
_get_codec_options,
detect_available_hw_encoders,
resolve_vcodec,
)
from lerobot.utils.constants import OBS_IMAGES
# βββ _get_codec_options tests βββ
class TestGetCodecOptions:
def test_libsvtav1_defaults(self):
opts = _get_codec_options("libsvtav1")
assert opts["g"] == "2"
assert opts["crf"] == "30"
assert opts["preset"] == "12"
def test_libsvtav1_custom_preset(self):
opts = _get_codec_options("libsvtav1", preset=8)
assert opts["preset"] == "8"
def test_h264_options(self):
opts = _get_codec_options("h264", g=10, crf=23)
assert opts["g"] == "10"
assert opts["crf"] == "23"
assert "preset" not in opts
def test_videotoolbox_options(self):
opts = _get_codec_options("h264_videotoolbox", g=2, crf=30)
assert opts["g"] == "2"
# CRF 30 maps to quality = max(1, min(100, 100 - 30*2)) = 40
assert opts["q:v"] == "40"
assert "crf" not in opts
def test_nvenc_options(self):
opts = _get_codec_options("h264_nvenc", g=2, crf=25)
assert opts["rc"] == "constqp"
assert opts["qp"] == "25"
assert "crf" not in opts
# NVENC doesn't support g
assert "g" not in opts
def test_vaapi_options(self):
opts = _get_codec_options("h264_vaapi", crf=28)
assert opts["qp"] == "28"
def test_qsv_options(self):
opts = _get_codec_options("h264_qsv", crf=25)
assert opts["global_quality"] == "25"
def test_no_g_no_crf(self):
opts = _get_codec_options("h264", g=None, crf=None)
assert "g" not in opts
assert "crf" not in opts
# βββ HW encoder detection tests βββ
class TestHWEncoderDetection:
def test_detect_available_hw_encoders_returns_list(self):
result = detect_available_hw_encoders()
assert isinstance(result, list)
def test_detect_available_hw_encoders_only_valid(self):
from lerobot.datasets.video_utils import HW_ENCODERS
result = detect_available_hw_encoders()
for encoder in result:
assert encoder in HW_ENCODERS
def test_resolve_vcodec_passthrough(self):
assert resolve_vcodec("libsvtav1") == "libsvtav1"
assert resolve_vcodec("h264") == "h264"
def test_resolve_vcodec_auto_fallback(self):
"""When no HW encoders are available, auto should fall back to libsvtav1."""
with patch("lerobot.datasets.video_utils.detect_available_hw_encoders", return_value=[]):
assert resolve_vcodec("auto") == "libsvtav1"
def test_resolve_vcodec_auto_picks_hw(self):
"""When a HW encoder is available, auto should pick it."""
with patch(
"lerobot.datasets.video_utils.detect_available_hw_encoders",
return_value=["h264_videotoolbox"],
):
assert resolve_vcodec("auto") == "h264_videotoolbox"
def test_resolve_vcodec_auto_returns_valid(self):
"""Test that resolve_vcodec('auto') returns a known valid codec."""
result = resolve_vcodec("auto")
assert result in VALID_VIDEO_CODECS
def test_hw_encoder_names_accepted_in_validation(self):
"""Test that HW encoder names pass validation in VALID_VIDEO_CODECS."""
assert "auto" in VALID_VIDEO_CODECS
assert "h264_videotoolbox" in VALID_VIDEO_CODECS
assert "h264_nvenc" in VALID_VIDEO_CODECS
def test_resolve_vcodec_invalid_raises(self):
"""Test that resolve_vcodec raises ValueError for invalid codecs."""
with pytest.raises(ValueError, match="Invalid vcodec"):
resolve_vcodec("not_a_real_codec")
# βββ _CameraEncoderThread tests βββ
class TestCameraEncoderThread:
def test_encodes_valid_mp4(self, tmp_path):
"""Test that the encoder thread creates a valid MP4 file with correct frame count."""
num_frames = 30
height, width = 64, 96
fps = 30
video_path = tmp_path / "test_output" / "test.mp4"
frame_queue: queue.Queue = queue.Queue(maxsize=60)
result_queue: queue.Queue = queue.Queue(maxsize=1)
stop_event = threading.Event()
encoder_thread = _CameraEncoderThread(
video_path=video_path,
fps=fps,
vcodec="libsvtav1",
pix_fmt="yuv420p",
g=2,
crf=30,
preset=13,
frame_queue=frame_queue,
result_queue=result_queue,
stop_event=stop_event,
)
encoder_thread.start()
# Feed frames (HWC uint8)
for _ in range(num_frames):
frame = np.random.randint(0, 255, (height, width, 3), dtype=np.uint8)
frame_queue.put(frame)
# Send sentinel
frame_queue.put(None)
encoder_thread.join(timeout=60)
assert not encoder_thread.is_alive()
# Check result
status, data = result_queue.get(timeout=5)
assert status == "ok"
assert data is not None # Stats should be returned
assert "mean" in data
assert "std" in data
assert "min" in data
assert "max" in data
assert "count" in data
# Verify the MP4 file is valid
assert video_path.exists()
with av.open(str(video_path)) as container:
stream = container.streams.video[0]
# The frame count should match
total_frames = sum(1 for _ in container.decode(stream))
assert total_frames == num_frames
def test_handles_chw_input(self, tmp_path):
"""Test that CHW format input is handled correctly."""
num_frames = 5
fps = 30
video_path = tmp_path / "test_chw" / "test.mp4"
frame_queue: queue.Queue = queue.Queue(maxsize=60)
result_queue: queue.Queue = queue.Queue(maxsize=1)
stop_event = threading.Event()
encoder_thread = _CameraEncoderThread(
video_path=video_path,
fps=fps,
vcodec="libsvtav1",
pix_fmt="yuv420p",
g=2,
crf=30,
preset=13,
frame_queue=frame_queue,
result_queue=result_queue,
stop_event=stop_event,
)
encoder_thread.start()
# Feed CHW frames
for _ in range(num_frames):
frame = np.random.randint(0, 255, (3, 64, 96), dtype=np.uint8)
frame_queue.put(frame)
frame_queue.put(None)
encoder_thread.join(timeout=60)
status, _ = result_queue.get(timeout=5)
assert status == "ok"
assert video_path.exists()
def test_stop_event_cancellation(self, tmp_path):
"""Test that setting the stop event causes the thread to exit."""
fps = 30
video_path = tmp_path / "test_cancel" / "test.mp4"
frame_queue: queue.Queue = queue.Queue(maxsize=60)
result_queue: queue.Queue = queue.Queue(maxsize=1)
stop_event = threading.Event()
encoder_thread = _CameraEncoderThread(
video_path=video_path,
fps=fps,
vcodec="libsvtav1",
pix_fmt="yuv420p",
g=2,
crf=30,
preset=13,
frame_queue=frame_queue,
result_queue=result_queue,
stop_event=stop_event,
)
encoder_thread.start()
# Feed a few frames
for _ in range(3):
frame = np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8)
frame_queue.put(frame)
# Signal stop instead of sending sentinel
stop_event.set()
encoder_thread.join(timeout=10)
assert not encoder_thread.is_alive()
# βββ StreamingVideoEncoder tests βββ
class TestStreamingVideoEncoder:
def test_single_camera_episode(self, tmp_path):
"""Test encoding a single camera episode."""
encoder = StreamingVideoEncoder(fps=30, vcodec="libsvtav1", pix_fmt="yuv420p", g=2, crf=30, preset=13)
video_keys = [f"{OBS_IMAGES}.laptop"]
encoder.start_episode(video_keys, tmp_path)
num_frames = 20
for _ in range(num_frames):
frame = np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8)
encoder.feed_frame(f"{OBS_IMAGES}.laptop", frame)
results = encoder.finish_episode()
assert f"{OBS_IMAGES}.laptop" in results
mp4_path, stats = results[f"{OBS_IMAGES}.laptop"]
assert mp4_path.exists()
assert stats is not None
# Verify frame count
with av.open(str(mp4_path)) as container:
stream = container.streams.video[0]
total_frames = sum(1 for _ in container.decode(stream))
assert total_frames == num_frames
encoder.close()
def test_multi_camera_episode(self, tmp_path):
"""Test encoding multiple cameras simultaneously."""
encoder = StreamingVideoEncoder(fps=30, vcodec="libsvtav1", pix_fmt="yuv420p", g=2, crf=30)
video_keys = [f"{OBS_IMAGES}.laptop", f"{OBS_IMAGES}.phone"]
encoder.start_episode(video_keys, tmp_path)
num_frames = 15
for _ in range(num_frames):
frame0 = np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8)
frame1 = np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8)
encoder.feed_frame(video_keys[0], frame0)
encoder.feed_frame(video_keys[1], frame1)
results = encoder.finish_episode()
for key in video_keys:
assert key in results
mp4_path, stats = results[key]
assert mp4_path.exists()
assert stats is not None
encoder.close()
def test_sequential_episodes(self, tmp_path):
"""Test that multiple sequential episodes work correctly."""
encoder = StreamingVideoEncoder(fps=30, vcodec="libsvtav1", pix_fmt="yuv420p", g=2, crf=30)
video_keys = [f"{OBS_IMAGES}.cam"]
for ep in range(3):
encoder.start_episode(video_keys, tmp_path)
num_frames = 10 + ep * 5
for _ in range(num_frames):
frame = np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8)
encoder.feed_frame(f"{OBS_IMAGES}.cam", frame)
results = encoder.finish_episode()
mp4_path, stats = results[f"{OBS_IMAGES}.cam"]
assert mp4_path.exists()
with av.open(str(mp4_path)) as container:
stream = container.streams.video[0]
total_frames = sum(1 for _ in container.decode(stream))
assert total_frames == num_frames
encoder.close()
def test_cancel_episode(self, tmp_path):
"""Test that canceling an episode cleans up properly."""
encoder = StreamingVideoEncoder(fps=30, vcodec="libsvtav1", pix_fmt="yuv420p", g=2, crf=30)
video_keys = [f"{OBS_IMAGES}.cam"]
encoder.start_episode(video_keys, tmp_path)
for _ in range(5):
frame = np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8)
encoder.feed_frame(f"{OBS_IMAGES}.cam", frame)
encoder.cancel_episode()
# Should be able to start a new episode after cancel
encoder.start_episode(video_keys, tmp_path)
for _ in range(5):
frame = np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8)
encoder.feed_frame(f"{OBS_IMAGES}.cam", frame)
results = encoder.finish_episode()
assert f"{OBS_IMAGES}.cam" in results
encoder.close()
def test_feed_without_start_raises(self, tmp_path):
"""Test that feeding frames without starting an episode raises."""
encoder = StreamingVideoEncoder(fps=30, vcodec="libsvtav1", pix_fmt="yuv420p")
with pytest.raises(RuntimeError, match="No active episode"):
encoder.feed_frame("cam", np.zeros((64, 96, 3), dtype=np.uint8))
encoder.close()
def test_finish_without_start_raises(self, tmp_path):
"""Test that finishing without starting raises."""
encoder = StreamingVideoEncoder(fps=30, vcodec="libsvtav1", pix_fmt="yuv420p")
with pytest.raises(RuntimeError, match="No active episode"):
encoder.finish_episode()
encoder.close()
def test_close_is_idempotent(self, tmp_path):
"""Test that close() can be called multiple times safely."""
encoder = StreamingVideoEncoder(fps=30, vcodec="libsvtav1", pix_fmt="yuv420p")
encoder.close()
encoder.close() # Should not raise
def test_video_duration_matches_frame_count(self, tmp_path):
"""Test that encoded video duration matches num_frames / fps."""
encoder = StreamingVideoEncoder(fps=30, vcodec="libsvtav1", pix_fmt="yuv420p", g=2, crf=30, preset=13)
video_keys = [f"{OBS_IMAGES}.cam"]
encoder.start_episode(video_keys, tmp_path)
num_frames = 90 # 3 seconds at 30fps
for _ in range(num_frames):
frame = np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8)
encoder.feed_frame(f"{OBS_IMAGES}.cam", frame)
results = encoder.finish_episode()
mp4_path, _ = results[f"{OBS_IMAGES}.cam"]
expected_duration = num_frames / 30.0 # 3.0 seconds
with av.open(str(mp4_path)) as container:
stream = container.streams.video[0]
total_frames = sum(1 for _ in container.decode(stream))
if stream.duration is not None:
actual_duration = float(stream.duration * stream.time_base)
else:
actual_duration = float(container.duration / av.time_base)
assert total_frames == num_frames
# Allow small tolerance for duration due to codec framing
assert abs(actual_duration - expected_duration) < 0.5, (
f"Video duration {actual_duration:.2f}s != expected {expected_duration:.2f}s"
)
encoder.close()
def test_multi_camera_start_episode_called_once(self, tmp_path):
"""Test that with multiple cameras, no frames are lost due to double start_episode."""
encoder = StreamingVideoEncoder(fps=30, vcodec="libsvtav1", pix_fmt="yuv420p", g=2, crf=30)
video_keys = [f"{OBS_IMAGES}.cam1", f"{OBS_IMAGES}.cam2"]
encoder.start_episode(video_keys, tmp_path)
num_frames = 30
for _ in range(num_frames):
frame0 = np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8)
frame1 = np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8)
encoder.feed_frame(video_keys[0], frame0)
encoder.feed_frame(video_keys[1], frame1)
results = encoder.finish_episode()
# Both cameras should have all frames
for key in video_keys:
mp4_path, stats = results[key]
assert mp4_path.exists()
with av.open(str(mp4_path)) as container:
stream = container.streams.video[0]
total_frames = sum(1 for _ in container.decode(stream))
assert total_frames == num_frames, (
f"Camera {key}: expected {num_frames} frames, got {total_frames}"
)
encoder.close()
def test_encoder_threads_passed_to_thread(self, tmp_path):
"""Test that encoder_threads is stored and passed through to encoder threads."""
encoder = StreamingVideoEncoder(
fps=30, vcodec="libsvtav1", pix_fmt="yuv420p", g=2, crf=30, encoder_threads=2
)
assert encoder.encoder_threads == 2
video_keys = [f"{OBS_IMAGES}.cam"]
encoder.start_episode(video_keys, tmp_path)
# Verify the thread received the encoder_threads value
thread = encoder._threads[f"{OBS_IMAGES}.cam"]
assert thread.encoder_threads == 2
# Feed some frames and finish to ensure it works end-to-end
num_frames = 10
for _ in range(num_frames):
frame = np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8)
encoder.feed_frame(f"{OBS_IMAGES}.cam", frame)
results = encoder.finish_episode()
mp4_path, stats = results[f"{OBS_IMAGES}.cam"]
assert mp4_path.exists()
assert stats is not None
with av.open(str(mp4_path)) as container:
stream = container.streams.video[0]
total_frames = sum(1 for _ in container.decode(stream))
assert total_frames == num_frames
encoder.close()
def test_encoder_threads_none_by_default(self, tmp_path):
"""Test that encoder_threads defaults to None (codec auto-detect)."""
encoder = StreamingVideoEncoder(fps=30, vcodec="libsvtav1", pix_fmt="yuv420p")
assert encoder.encoder_threads is None
encoder.close()
def test_graceful_frame_dropping(self, tmp_path):
"""Test that full queue drops frames instead of crashing."""
encoder = StreamingVideoEncoder(
fps=30, vcodec="libsvtav1", pix_fmt="yuv420p", g=2, crf=30, preset=13, queue_maxsize=1
)
video_keys = [f"{OBS_IMAGES}.cam"]
encoder.start_episode(video_keys, tmp_path)
# Feed many frames quickly - with queue_maxsize=1, some will be dropped
num_frames = 50
for _ in range(num_frames):
frame = np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8)
encoder.feed_frame(f"{OBS_IMAGES}.cam", frame)
# Should not raise - frames are dropped gracefully
results = encoder.finish_episode()
assert f"{OBS_IMAGES}.cam" in results
mp4_path, _ = results[f"{OBS_IMAGES}.cam"]
assert mp4_path.exists()
# Some frames should have been dropped (queue was tiny)
dropped = encoder._dropped_frames.get(f"{OBS_IMAGES}.cam", 0)
# We can't guarantee drops but can verify no crash occurred
assert dropped >= 0
encoder.close()
# βββ Integration tests with LeRobotDataset βββ
class TestStreamingEncoderIntegration:
def test_add_frame_save_episode_streaming(self, tmp_path):
"""Full integration test: add_frame -> save_episode with streaming encoding."""
from lerobot.datasets.lerobot_dataset import LeRobotDataset
features = {
"observation.images.cam": {
"dtype": "video",
"shape": (64, 96, 3),
"names": ["height", "width", "channels"],
},
"action": {"dtype": "float32", "shape": (6,), "names": ["j1", "j2", "j3", "j4", "j5", "j6"]},
}
dataset = LeRobotDataset.create(
repo_id="test/streaming",
fps=30,
features=features,
root=tmp_path / "streaming_test",
use_videos=True,
streaming_encoding=True,
)
assert dataset._streaming_encoder is not None
num_frames = 20
for _ in range(num_frames):
frame = {
"observation.images.cam": np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8),
"action": np.random.randn(6).astype(np.float32),
"task": "test task",
}
dataset.add_frame(frame)
dataset.save_episode()
# Verify dataset metadata
assert dataset.meta.total_episodes == 1
assert dataset.meta.total_frames == num_frames
# Verify stats exist for the video key
assert dataset.meta.stats is not None
assert "observation.images.cam" in dataset.meta.stats
assert "action" in dataset.meta.stats
dataset.finalize()
def test_streaming_disabled_creates_pngs(self, tmp_path):
"""Test that disabling streaming encoding falls back to PNG path."""
from lerobot.datasets.lerobot_dataset import LeRobotDataset
features = {
"observation.images.cam": {
"dtype": "video",
"shape": (64, 96, 3),
"names": ["height", "width", "channels"],
},
"action": {"dtype": "float32", "shape": (6,), "names": ["j1", "j2", "j3", "j4", "j5", "j6"]},
}
dataset = LeRobotDataset.create(
repo_id="test/no_streaming",
fps=30,
features=features,
root=tmp_path / "no_streaming_test",
use_videos=True,
streaming_encoding=False,
)
assert dataset._streaming_encoder is None
num_frames = 5
for _ in range(num_frames):
frame = {
"observation.images.cam": np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8),
"action": np.random.randn(6).astype(np.float32),
"task": "test task",
}
dataset.add_frame(frame)
# With streaming disabled, PNG files should be written
images_dir = dataset.root / "images"
assert images_dir.exists()
dataset.save_episode()
dataset.finalize()
def test_multi_episode_streaming(self, tmp_path):
"""Test recording multiple episodes with streaming encoding."""
from lerobot.datasets.lerobot_dataset import LeRobotDataset
features = {
"observation.images.cam": {
"dtype": "video",
"shape": (64, 96, 3),
"names": ["height", "width", "channels"],
},
"action": {"dtype": "float32", "shape": (2,), "names": ["j1", "j2"]},
}
dataset = LeRobotDataset.create(
repo_id="test/multi_ep",
fps=30,
features=features,
root=tmp_path / "multi_ep_test",
use_videos=True,
streaming_encoding=True,
)
for ep in range(3):
num_frames = 10 + ep * 5
for _ in range(num_frames):
frame = {
"observation.images.cam": np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8),
"action": np.random.randn(2).astype(np.float32),
"task": f"task_{ep}",
}
dataset.add_frame(frame)
dataset.save_episode()
assert dataset.meta.total_episodes == 3
assert dataset.meta.total_frames == 10 + 15 + 20
dataset.finalize()
def test_clear_episode_buffer_cancels_streaming(self, tmp_path):
"""Test that clearing episode buffer cancels streaming encoding."""
from lerobot.datasets.lerobot_dataset import LeRobotDataset
features = {
"observation.images.cam": {
"dtype": "video",
"shape": (64, 96, 3),
"names": ["height", "width", "channels"],
},
"action": {"dtype": "float32", "shape": (2,), "names": ["j1", "j2"]},
}
dataset = LeRobotDataset.create(
repo_id="test/cancel",
fps=30,
features=features,
root=tmp_path / "cancel_test",
use_videos=True,
streaming_encoding=True,
)
# Add some frames
for _ in range(5):
frame = {
"observation.images.cam": np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8),
"action": np.random.randn(2).astype(np.float32),
"task": "task",
}
dataset.add_frame(frame)
# Cancel and re-record
dataset.clear_episode_buffer()
# Record a new episode
for _ in range(10):
frame = {
"observation.images.cam": np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8),
"action": np.random.randn(2).astype(np.float32),
"task": "task",
}
dataset.add_frame(frame)
dataset.save_episode()
assert dataset.meta.total_episodes == 1
assert dataset.meta.total_frames == 10
dataset.finalize()
def test_multi_camera_add_frame_streaming(self, tmp_path):
"""Test that start_episode is called once with multiple video keys."""
from lerobot.datasets.lerobot_dataset import LeRobotDataset
features = {
"observation.images.cam1": {
"dtype": "video",
"shape": (64, 96, 3),
"names": ["height", "width", "channels"],
},
"observation.images.cam2": {
"dtype": "video",
"shape": (64, 96, 3),
"names": ["height", "width", "channels"],
},
"action": {"dtype": "float32", "shape": (2,), "names": ["j1", "j2"]},
}
dataset = LeRobotDataset.create(
repo_id="test/multi_cam",
fps=30,
features=features,
root=tmp_path / "multi_cam_test",
use_videos=True,
streaming_encoding=True,
)
num_frames = 15
for _ in range(num_frames):
frame = {
"observation.images.cam1": np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8),
"observation.images.cam2": np.random.randint(0, 255, (64, 96, 3), dtype=np.uint8),
"action": np.random.randn(2).astype(np.float32),
"task": "test task",
}
dataset.add_frame(frame)
dataset.save_episode()
assert dataset.meta.total_episodes == 1
assert dataset.meta.total_frames == num_frames
dataset.finalize()
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