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Handle videos with begin_stream_seconds > 0 #345

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Handle videos with begin_stream_seconds > 0 #345

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7 changes: 6 additions & 1 deletion benchmarks/decoders/benchmark_decoders_library.py
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Original file line number Diff line number Diff line change
Expand Up @@ -494,7 +494,12 @@ def run_benchmarks(
metadata_label = f"{metadata.codec} {metadata.width}x{metadata.height}, {metadata.duration_seconds}s {metadata.average_fps}fps"

duration = metadata.duration_seconds
uniform_pts_list = [i * duration / num_samples for i in range(num_samples)]
# The epislon of 1e-6 is added to avoid floating point issues. Otherwise I see error messages like:
# RuntimeError: frame pts is 0.015999; must be in range [0.015999, 5.004316).
begin = metadata.begin_stream_seconds + 1e-6
uniform_pts_list = [
i * duration / num_samples + begin for i in range(num_samples)
]
Comment on lines +497 to +502
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Suggestion: try to rely on torch.arange instead, like we do in the samplers

torchcodec/src/torchcodec/samplers/_time_based.py

Line 198 in c2bea4b

clip_start_seconds = torch.arange(
. It should start exactly at begin which hopefully wouldn't cause the error we're seeing.

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I had the same thought when I was refactoring things, and I can't remember why I didn't do it. :) I'll dig in later.

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Seems like arange doesn't work here, possibly due to rounding:

        uniform_pts_list = list(
            torch.arange(
                metadata.begin_stream_seconds,
                metadata.end_stream_seconds,
                (metadata.end_stream_seconds - metadata.begin_stream_seconds)
                / num_samples,
            )
        )

Gives me the same error:

RuntimeError: frame pts is 0.015999; must be in range [0.015999, 5.004316).


# Note that we are using the same random pts values for all decoders for the same
# video. However, because we use the duration as part of this calculation, we
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