# RetakePipeline: The LTX-2 Pipeline for Regenerating Specific Video Regions

> Discover the RetakePipeline in LTX-2 for regenerating specific video regions. Modify select time intervals without affecting surrounding content. Learn more about LTX-2's flexible video editing.

- Repository: [Lightricks/LTX-2](https://github.com/Lightricks/LTX-2)
- Tags: deep-dive
- Published: 2026-06-21

---

**The `RetakePipeline` is the dedicated LTX-2 component for regenerating specific video regions, enabling selective modification of a time interval while leaving the surrounding content untouched.**

The Lightricks/LTX-2 repository provides a specialized solution for **regenerating specific video regions** through the `RetakePipeline`. This component bridges the gap between full video generation and precise editing, allowing creators to modify selected temporal segments without re-rendering entire clips. By leveraging temporal masking and selective diffusion, the pipeline preserves the original video's integrity outside the specified window.

## How RetakePipeline Handles Region Regeneration

### Temporal Region Masking

At the core of selective regeneration lies the `TemporalRegionMask` class defined in [`packages/ltx-core/src/ltx_core/conditioning/types/noise_mask_cond.py`](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-core/src/ltx_core/conditioning/types/noise_mask_cond.py). This component creates a binary mask that identifies frames belonging to the target time interval, enabling the diffusion model to distinguish between regions slated for regeneration and those that should remain frozen.

### Selective Diffusion Process

The `DiffusionStage` component (located in [`packages/ltx-pipelines/src/ltx_pipelines/utils/blocks.py`](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-pipelines/src/ltx_pipelines/utils/blocks.py)) executes the LTX-2 diffusion process while respecting the temporal constraints. When processing a retake request, the pipeline encodes the text prompt through `PromptEncoder` and extracts latent representations via `ImageConditioner`, but only applies denoising operations to the masked temporal region. The `VideoDecoder` and `AudioDecoder` then convert the regenerated latents back to media format, stitching them seamlessly with the untouched original segments.

### Command-Line Interface Support

The `video_editing_arg_parser` in [`packages/ltx-pipelines/src/ltx_pipelines/utils/args.py`](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-pipelines/src/ltx_pipelines/utils/args.py) exposes the `--start-time` and `--end-time` flags, allowing users to define regeneration boundaries in seconds directly from the command line. These parameters pass through to `RetakePipeline.__call__`, where they transform into the `TemporalRegionMask` that governs the diffusion process.

## Implementing Video Region Regeneration

To regenerate a specific video region using the LTX-2 framework, initialize the `RetakePipeline` with the appropriate model checkpoints and invoke the pipeline with temporal boundaries:

```python
from ltx_pipelines.retake import RetakePipeline
from pathlib import Path

# Initialise the pipeline (provide paths to the model checkpoint and Gemma text encoder)

pipeline = RetakePipeline(
    checkpoint_path="models/ltx2.ckpt",
    gemma_root="models/gemma",
    loras=[],                # optional LoRA configs

    distilled=True,          # use distilled schedule (default)

)

# Regenerate 2-3 seconds of the source video

frames_iter, audio = pipeline(
    video_path=Path("input/video.mp4"),
    prompt="A sunset over a calm lake",
    start_time=2.0,          # seconds

    end_time=3.0,            # seconds

    seed=42,
)

# Encode and save the result

from ltx_pipelines.utils.media_io import encode_video
encode_video(frames_iter, audio, out_path=Path("output/retake.mp4"))

```

## Key Source Files and Components

The region regeneration capability relies on specific modules within the LTX-2 codebase:

- [`packages/ltx-pipelines/src/ltx_pipelines/retake.py`](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-pipelines/src/ltx_pipelines/retake.py): Contains the `RetakePipeline` class definition and its `__call__` implementation that orchestrates the regeneration workflow.
- [`packages/ltx-core/src/ltx_core/conditioning/types/noise_mask_cond.py`](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-core/src/ltx_core/conditioning/types/noise_mask_cond.py): Implements `TemporalRegionMask` for selective frame targeting.
- [`packages/ltx-pipelines/src/ltx_pipelines/utils/blocks.py`](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-pipelines/src/ltx_pipelines/utils/blocks.py): Houses core building blocks including `PromptEncoder`, `ImageConditioner`, and `DiffusionStage`.
- [`packages/ltx-pipelines/src/ltx_pipelines/utils/args.py`](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-pipelines/src/ltx_pipelines/utils/args.py): Provides the `video_editing_arg_parser` with `--start-time` and `--end-time` arguments.
- [`packages/ltx-pipelines/src/ltx_pipelines/utils/media_io.py`](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-pipelines/src/ltx_pipelines/utils/media_io.py): Includes `encode_video` for final output serialization.

## Summary

- The `RetakePipeline` is the specific LTX-2 solution for **regenerating specific video regions** without affecting the entire timeline.
- **TemporalRegionMask** creates binary masks that enable selective denoising of only the target time window.
- The pipeline accepts `start_time` and `end_time` parameters (in seconds) to define precise regeneration boundaries.
- Source files in `packages/ltx-pipelines/src/ltx_pipelines/` and `packages/ltx-core/` handle the masking, diffusion, and I/O operations required for seamless video retakes.

## Frequently Asked Questions

### Which LTX-2 pipeline allows regenerating specific video regions?

The `RetakePipeline` is the dedicated component in the Lightricks/LTX-2 repository designed specifically for regenerating specific video regions. Unlike full generation pipelines, it accepts `start_time` and `end_time` parameters to isolate and modify only the specified temporal segment.

### How does RetakePipeline preserve unmodified video regions?

The pipeline utilizes `TemporalRegionMask` (defined in [`packages/ltx-core/src/ltx_core/conditioning/types/noise_mask_cond.py`](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-core/src/ltx_core/conditioning/types/noise_mask_cond.py)) to create a binary mask that identifies frames outside the regeneration window. The `DiffusionStage` respects this mask, applying denoising operations only to the targeted frames while preserving the original content in the masked regions.

### What parameters define the regeneration window in RetakePipeline?

Users specify the regeneration boundaries through the `start_time` and `end_time` parameters (measured in seconds) when calling the pipeline. These values can also be passed via command-line arguments `--start-time` and `--end-time` provided by the `video_editing_arg_parser` in [`packages/ltx-pipelines/src/ltx_pipelines/utils/args.py`](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-pipelines/src/ltx_pipelines/utils/args.py).

### Can RetakePipeline regenerate audio along with video regions?

Yes, the `RetakePipeline` supports audio regeneration within the specified time window. The pipeline returns both frames and audio data, which are processed through `AudioDecoder` and combined with the original video content before final output via `encode_video` in [`packages/ltx-pipelines/src/ltx_pipelines/utils/media_io.py`](https://github.com/Lightricks/LTX-2/blob/main/packages/ltx-pipelines/src/ltx_pipelines/utils/media_io.py).