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dpp-pipelinedpp 管道

Agent Skill

dpp-pipeline 用于处理图像、截图、视觉识别或图片素材相关工作,适合在 OpenClaw 中需要让 Agent 分析图片、整理视觉素材或辅助图像流程时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

2,496

周安装

112

GitHub Stars

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下载量

808
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:dpp-pipeline(dpp 管道)
来源仓库:https://github.com/kotot/dpp-pipeline
安装命令:
openclaw skills install dpp-pipeline
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install dpp-pipeline

简介

将本地源视频与产品图合成为植入式营销视频。

  • 适用于电商产品展示与广告素材制作。dpp-pipeline 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 支持自动化流程减少手动剪辑工作量。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 使用前需准备符合尺寸要求的源文件。
  • 注意版权归属,确保所用素材拥有合法使用权。

SKILL.md

name
dpp-pipeline
description
Use when you need to turn a local source video and one product image into a single-product placement video with the DPP pipeline.
license
UNLICENSED
allowed-tools
Bash Read Glob Grep
metadata
openclaw
version
0.1.0
primaryEnv
ARK_API_KEY
user-invocable
true
compatibility
Requires Python 3.11+, ffmpeg, network access, Ark credentials, and optional TOS credentials when compose-best must auto-upload reference media. Reads and writes in the caller workspace or DPP_WORKDIR.
requires
env
bins

DPP Pipeline

Run the DPP storyboard, placement, and compose-best flow from a local workspace.

The skill bundles its Python runtime under runtime/, but it does not treat the installed skill directory as the project workspace. Inputs and outputs live under the caller's current working directory by default. Override that with DPP_WORKDIR when needed.

When to Use

  • Generate storyboard.json from a local video with dpp-storyboard.
  • Generate a single-product material config from one product image under assets/.
  • Select the best storyboard segment for one product image with dpp-placement.
  • Run the final best-segment composition flow with dpp-compose-best.
  • Replace the best segment in the original video with the generated clip using dpp-final-cut.

Do not use this skill for multi-product batch processing. This skill handles one local video and one product image at a time.

Dependencies

  • Python 3.11+
  • ffmpeg
  • Network access to Ark and TOS
  • Ark environment variables in the target workspace .env
  • TOS_BUCKET, TOS_AK, TOS_SK, TOS_ENDPOINT, and TOS_REGION when compose-best must auto-upload the reference clip or image
  • TOS_OBJECT_PREFIX, TOS_ENABLE_HTTPS, and TOS_FORCE_ENDPOINT are optional TOS tuning variables

Install Python dependencies by running:

scripts/bootstrap_runtime.sh

Workspace Layout

The runtime lives inside the installed skill. The caller workspace holds inputs, configs, logs, and outputs:

<workspace>/
  .env
  assets/
    <single product image>
  video/
    demo.mp4
  configs/
    placement_material.json
  log/
  output/
    <video_stem>/
      finalCut/

Initialize a new workspace with:

scripts/init_workspace.sh

That command creates assets/, video/, configs/, and output/, and copies sample files into place.

Workflow

  1. Run scripts/bootstrap_runtime.sh.
  2. If the target workspace is empty, run scripts/init_workspace.sh.
  3. Ensure the workspace .env contains Ark credentials and defaults.
  4. Ensure video/demo.mp4 exists before storyboard, unless the user will pass --video.
  5. Ensure assets/ contains exactly one product image before material generation, unless the user will pass --image.
  6. Run scripts/run_storyboard.sh.
  7. Run scripts/run_generate_material.sh.
  8. Run scripts/run_placement.sh.
  9. Run scripts/run_compose_best.sh.
  10. Run scripts/run_final_cut.sh.

Do not skip stage ordering unless the user explicitly asks to reuse an existing artifact.

Review Pauses

Do not pause by default.

  • If the user wants review pauses, stop after each requested stage and report the artifact path.
  • If the user asks to continue, move directly to the next stage when the required inputs already exist.
  • If the user asks to rerun a later stage, reuse earlier artifacts unless the input changed.

Typical checkpoints:

  • After storyboard: review segmentation quality and thumbnail coverage.
  • After placement: review best_segment_index, ranking, and placement rationale.
  • After compose-best: review composition_result.json, prompt quality, and reference-media URL status.
  • After final-cut: review finalcut_result.json and verify the output video at output/<video_stem>/finalCut/final_cut.mp4.

Execution Rules

  • Run the stage scripts from the caller workspace, or set DPP_WORKDIR to the target workspace path.
  • Keep the installed skill directory immutable except for .venv/ and the generated runtime/ bundle.
  • Always bootstrap the runtime before the first stage command.
  • dpp-storyboard, dpp-placement, and dpp-compose-best can each take more than 10 minutes. Do not assume the process is hung just because it is quiet for a while; warn the user that the stage is long-running and let it complete naturally.
  • After each stage, report the main artifact path.
  • Before compose-best auto-upload, verify TOS_BUCKET, TOS_AK, TOS_SK, TOS_ENDPOINT, and TOS_REGION if the user did not provide --reference-video-url or DPP_REFERENCE_VIDEO_URL.
  • This skill sends prompts and media metadata to Ark. Compose-best may also upload the reference clip and product image to TOS.

Detailed commands live in references/commands.md.

Scripts

  • scripts/bootstrap_runtime.sh
  • scripts/init_workspace.sh
  • scripts/run_storyboard.sh
  • scripts/run_generate_material.sh
  • scripts/run_placement.sh
  • scripts/run_compose_best.sh
  • scripts/run_final_cut.sh

Each script forwards all CLI arguments to the underlying Python module.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

72.59%
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敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

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