---
description: "Transcode clips with CPU or GPU encoders and tune for quality and performance"
categories: ["video-curation"]
tags: ["transcoding", "encoding", "ffmpeg", "nvenc", "h264"]
personas: ["data-scientist-focused", "mle-focused"]
difficulty: "intermediate"
content_type: "howto"
modality: "video-only"
---

# Clip Encoding

Convert extracted clip buffers into compressed media files suitable for storage and training workflows using encoders. NeMo Curator provides both CPU and GPU-based encoders.

## Use Cases

- Convert raw clip buffers into a standard format (such as H.264 in MP4) for portability.
- Normalize heterogeneous inputs (encoding formats, bit rates, containers) into a consistent output.
- Reduce storage footprint with controlled quality settings.

## Before You Start

If you only need embeddings or analysis and do not require saved media files, you can skip encoding. When writing clips, NeMo Curator produces `.mp4` by default.

---

## Quickstart

Use the pipeline stage or the example script flags to encode clips with CPU or GPU encoders.

<Tabs>
<Tab title="Pipeline Stage">

```python
from nemo_curator.pipeline import Pipeline
from nemo_curator.stages.video.clipping.clip_extraction_stages import FixedStrideExtractorStage, ClipTranscodingStage

pipe = Pipeline(name="transcode_example")
pipe.add_stage(FixedStrideExtractorStage(clip_len_s=10.0, clip_stride_s=10.0))
pipe.add_stage(ClipTranscodingStage(encoder="h264_nvenc", encode_batch_size=16, encoder_threads=1, verbose=True))
pipe.run()
```

</Tab>

<Tab title="Script Flags">

```bash
python -m ray_curator.examples.video.video_split_clip_example \
  ...
  --transcode-encoder h264_nvenc \
  --transcode-use-hwaccel \
```

</Tab>
</Tabs>

## Encoder Options

| Encoder | Hardware | Description |
| --- | --- | --- |
| `h264_nvenc` | NVIDIA GPU (NVENC) | Uses NVENC for high-throughput H.264 encoding on NVIDIA GPU hardware. |
| `libvpx-vp9` | CPU | VP9 software encoder. Use as a fallback on GPUs without NVENC silicon (such as A100/H100). Slower than NVENC; produces VP9 in `.mp4`. Emits a one-time performance advisory at construction. |
| `libopenh264` | CPU | H.264 software encoder. **Not bundled with Curator's default FFmpeg build** — opt-in by running `bash /opt/Curator/docker/common/install_h264_support.sh --with-libopenh264` inside the container, or providing a system FFmpeg that includes it. The stage probes at setup time and raises with a docs link if missing. See [Software H.264/HEVC/AV1 Codec Support](/get-started/installation#software-h264hevcav1-codec-support-advanced). |

<Tip>
On systems with supported NVIDIA GPU hardware and an `ffmpeg` build with NVENC, `h264_nvenc` can significantly increase throughput. Refer to the verification steps below to confirm NVENC availability. On GPUs without an NVENC encoder block (such as A100 and H100), use `libvpx-vp9` instead — it runs entirely on CPU and has no proprietary licensing constraints.
</Tip>

<Note>
**Need software H.264 (libopenh264 / libx264)?** Curator's default FFmpeg build excludes them for licensing reasons. The fastest path inside the container is the bundled installer:

```bash
bash /opt/Curator/docker/common/install_h264_support.sh --with-libopenh264
```

For other paths (system FFmpeg, custom image rebuild) see [Software H.264/HEVC/AV1 Codec Support](/get-started/installation#software-h264hevcav1-codec-support-advanced).
</Note>

<Note>
**Got `SoftwareCodecMissingError` on an h264 input?** Curator's CPU-only `VideoReader` and `ClipWriter` stages call `ffprobe`, which needs a software `h264` decoder — not available in the default NVDEC-only build. Install software decoder support with `bash /opt/Curator/docker/common/install_h264_support.sh`, or pick a transcode encoder whose output codec the system FFmpeg can software-decode (e.g., `--transcode-encoder libvpx-vp9`). See [Software H.264/HEVC/AV1 Codec Support](/get-started/installation#software-h264hevcav1-codec-support-advanced).
</Note>

### Verify `ffmpeg`/NVENC Support

To use `h264_nvenc`, confirm that your `ffmpeg` build includes NVENC support and install the GPU drivers:

```bash
ffmpeg -hide_banner -encoders | grep nvenc
ffmpeg -hide_banner -hwaccels | grep -i nv
nvidia-smi
```

Expected output includes entries like `V..... h264_nvenc` and `cuda` in the hardware accelerators list. If not present, install an `ffmpeg` build with NVENC and ensure NVIDIA drivers and CUDA are available.

## Configure

Use `ClipTranscodingStage` to control encoder choice, batching, and acceleration:

```python
from nemo_curator.stages.video.clipping.clip_extraction_stages import ClipTranscodingStage

transcode = ClipTranscodingStage(
    encoder="h264_nvenc",
    use_hwaccel=True,             # enable NVENC when using h264_nvenc
    encoder_threads=1,            # CPU thread count for CPU encoders
    encode_batch_size=16,         # number of clips per encode batch
    num_clips_per_chunk=32,       # chunking for downstream writing
    use_input_bit_rate=False,     # set True to preserve input bit rate when available
    num_cpus_per_worker=6.0,
    verbose=True,
)
```

### Parameters

| Parameter | Description |
| --- | --- |
| `encoder` | Selects the encoding backend. Supported values: `h264_nvenc` (GPU, requires NVENC), `libvpx-vp9` (CPU fallback for non-NVENC GPUs such as A100/H100), and `libopenh264` (CPU; opt-in via `install_h264_support.sh --with-libopenh264` — see [Software H.264/HEVC/AV1 Codec Support](/get-started/installation#software-h264hevcav1-codec-support-advanced)). |
| `use_hwaccel` | Enable when using `h264_nvenc`. Not valid with `libvpx-vp9` or `libopenh264`. |
| `encoder_threads` | CPU threads per worker for CPU encoders. Increase to use more CPU. |
| `encode_batch_size` | Batching size for clips; larger batches can improve throughput. |
| `use_input_bit_rate` | If True, attempts to reuse the input bit rate; otherwise, the encoder uses its default rate control. |

<Note>
Refer to the quickstart options in [Get Started with Video Curation](/get-started/video) for command-line flags `--transcode-encoder` and `--transcode-use-hwaccel`.

</Note>

## Troubleshooting

- "Encoder not found": Your `ffmpeg` build may lack the encoder; verify with `ffmpeg -encoders`.
- "No NVENC capable devices found": Install NVIDIA drivers/CUDA and ensure the GPU is visible in `nvidia-smi`.
- Output mismatch or low quality: Revisit encoder defaults; set explicit bit rate/quality settings as needed, or enable `use_input_bit_rate`.
