开发基于图片素材生成视频的webui功能
This commit is contained in:
puke
@@ -169,7 +169,7 @@ def render_content_input():
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}
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def render_bgm_section():
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def render_bgm_section(key_prefix=""):
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"""Render BGM selection section"""
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with st.container(border=True):
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st.markdown(f"**{tr('section.bgm')}**")
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@@ -204,7 +204,8 @@ def render_bgm_section():
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"BGM",
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bgm_options,
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index=default_index,
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label_visibility="collapsed"
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label_visibility="collapsed",
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key=f"{key_prefix}bgm_selector"
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)
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# BGM volume slider (only show when BGM is selected)
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@@ -216,7 +217,7 @@ def render_bgm_section():
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value=0.2,
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step=0.01,
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format="%.2f",
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key="bgm_volume_slider",
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key=f"{key_prefix}bgm_volume_slider",
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help=tr("bgm.volume_help")
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)
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else:
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@@ -224,7 +225,7 @@ def render_bgm_section():
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# BGM preview button (only if BGM is not "None")
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if bgm_choice != tr("bgm.none"):
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if st.button(tr("bgm.preview"), key="preview_bgm", use_container_width=True):
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if st.button(tr("bgm.preview"), key=f"{key_prefix}preview_bgm", use_container_width=True):
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from pixelle_video.utils.os_util import get_resource_path, resource_exists
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try:
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if resource_exists("bgm", bgm_choice):
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@@ -332,7 +332,44 @@
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"batch.error": "Error",
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"batch.error_detail": "View detailed error stack",
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"pipeline.standard.name": "Standard Video",
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"pipeline.demo.name": "Demo Feature",
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"pipeline.demo.description": "A demo pipeline with a custom layout"
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"pipeline.asset_based.name": "Asset-Based Video",
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"pipeline.asset_based.description": "Generate videos from user-provided assets",
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"asset_based.section.assets": "📦 Asset Upload",
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"asset_based.section.video_info": "📝 Video Information",
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"asset_based.section.source": "⚙️ Service Configuration",
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"asset_based.assets.what": "Upload your images or video assets, AI will automatically analyze them and generate a video script",
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"asset_based.assets.how": "Supports JPG/PNG/GIF/WebP images and MP4/MOV/AVI videos. Each asset should be clear and relevant",
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"asset_based.assets.upload": "Upload Assets",
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"asset_based.assets.upload_help": "Supports multiple image or video files",
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"asset_based.assets.count": "✅ Uploaded {count} assets",
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"asset_based.assets.preview": "📷 Asset Preview",
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"asset_based.assets.empty_hint": "💡 Please upload at least one image or video asset",
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"asset_based.video_title": "Video Title (Optional)",
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"asset_based.video_title_placeholder": "e.g., Pet Store Year-End Sale",
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"asset_based.video_title_help": "Main title for the video, leave empty to hide title",
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"asset_based.intent": "Video Intent",
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"asset_based.intent_placeholder": "e.g., Promote our pet store's year-end special offers to attract more customers, use a warm and friendly tone",
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"asset_based.intent_help": "Describe the purpose, message, and desired style of this video",
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"asset_based.duration": "Target Duration (seconds)",
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"asset_based.duration_help": "Expected video duration, AI will adjust based on asset count",
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"asset_based.duration_label": "Target Duration: {seconds}s",
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"asset_based.source.what": "Select the service provider for image analysis",
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"asset_based.source.how": "RunningHub is a cloud service requiring API Key; SelfHost uses local ComfyUI",
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"asset_based.source.select": "Select Service",
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"asset_based.source.runninghub": "☁️ RunningHub (Cloud)",
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"asset_based.source.selfhost": "🖥️ SelfHost (Local)",
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"asset_based.source.runninghub_hint": "💡 Using RunningHub cloud service for asset analysis",
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"asset_based.source.selfhost_hint": "💡 Using local ComfyUI service for asset analysis",
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"asset_based.source.runninghub_not_configured": "⚠️ RunningHub API Key not configured",
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"asset_based.source.selfhost_not_configured": "⚠️ Local ComfyUI URL not configured",
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"asset_based.output.no_assets": "💡 Please upload assets on the left first",
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"asset_based.output.ready": "📦 {count} assets ready, you can start generating",
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"asset_based.progress.analyzing": "🔍 Analyzing assets...",
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"asset_based.progress.analyzing_start": "🔍 Starting to analyze {total} assets...",
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"asset_based.progress.analyzing_asset": "🔍 Analyzing asset {current}/{total}: {name}",
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"asset_based.progress.analyzing_complete": "✅ Asset analysis complete ({count} total)",
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"asset_based.progress.generating_script": "📝 Generating video script...",
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"asset_based.progress.script_complete": "✅ Script generation complete",
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"asset_based.progress.concat_complete": "✅ Video concatenation complete"
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}
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}
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@@ -332,7 +332,44 @@
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"batch.error": "错误信息",
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"batch.error_detail": "查看详细错误堆栈",
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"pipeline.standard.name": "标准视频",
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"pipeline.demo.name": "演示功能",
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"pipeline.demo.description": "具有自定义布局的演示 Pipeline"
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"pipeline.asset_based.name": "素材视频",
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"pipeline.asset_based.description": "基于用户上传的素材生成视频",
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"asset_based.section.assets": "📦 素材上传",
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"asset_based.section.video_info": "📝 视频信息",
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"asset_based.section.source": "⚙️ 服务配置",
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"asset_based.assets.what": "上传您的图片或视频素材，AI 将自动分析并生成视频脚本",
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"asset_based.assets.how": "支持 JPG/PNG/GIF/WebP 图片和 MP4/MOV/AVI 等视频格式，建议每个素材清晰且内容相关",
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"asset_based.assets.upload": "上传素材",
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"asset_based.assets.upload_help": "支持多个图片或视频文件",
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"asset_based.assets.count": "✅ 已上传 {count} 个素材",
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"asset_based.assets.preview": "📷 素材预览",
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"asset_based.assets.empty_hint": "💡 请上传至少一个图片或视频素材",
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"asset_based.video_title": "视频标题（选填）",
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"asset_based.video_title_placeholder": "例如：宠物店年终大促",
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"asset_based.video_title_help": "视频的主标题，留空则不显示标题",
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"asset_based.intent": "视频意图",
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"asset_based.intent_placeholder": "例如：宣传我们的宠物店年终特惠活动，吸引更多客户到店消费，风格要温馨亲切",
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"asset_based.intent_help": "描述这个视频的目的、想传达的信息以及期望的风格",
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"asset_based.duration": "目标时长（秒）",
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"asset_based.duration_help": "视频的预期时长，AI 会根据素材数量和时长进行调整",
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"asset_based.duration_label": "目标时长：{seconds} 秒",
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"asset_based.source.what": "选择用于图像分析的服务提供商",
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"asset_based.source.how": "RunningHub 是云端服务，需配置 API Key；SelfHost 是本地 ComfyUI 服务",
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"asset_based.source.select": "选择服务",
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"asset_based.source.runninghub": "☁️ RunningHub（云端）",
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"asset_based.source.selfhost": "🖥️ SelfHost（本地）",
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"asset_based.source.runninghub_hint": "💡 使用 RunningHub 云端服务分析素材",
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"asset_based.source.selfhost_hint": "💡 使用本地 ComfyUI 服务分析素材",
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"asset_based.source.runninghub_not_configured": "⚠️ 未配置 RunningHub API Key",
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"asset_based.source.selfhost_not_configured": "⚠️ 未配置本地 ComfyUI 地址",
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"asset_based.output.no_assets": "💡 请先在左侧上传素材",
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"asset_based.output.ready": "📦 已准备好 {count} 个素材，可以开始生成",
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"asset_based.progress.analyzing": "🔍 正在分析素材...",
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"asset_based.progress.analyzing_start": "🔍 开始分析 {total} 个素材...",
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"asset_based.progress.analyzing_asset": "🔍 分析素材 {current}/{total}：{name}",
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"asset_based.progress.analyzing_complete": "✅ 素材分析完成（共 {count} 个）",
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"asset_based.progress.generating_script": "📝 正在生成视频脚本...",
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"asset_based.progress.script_complete": "✅ 脚本生成完成",
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"asset_based.progress.concat_complete": "✅ 视频合成完成"
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}
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}
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@@ -25,7 +25,7 @@ from web.pipelines.base import (
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# Import all pipeline UI modules to ensure they register themselves
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from web.pipelines import standard
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from web.pipelines import demo
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from web.pipelines import asset_based
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__all__ = [
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"PipelineUI",
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447
web/pipelines/asset_based.py
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447
web/pipelines/asset_based.py
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@@ -0,0 +1,447 @@
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# Copyright (C) 2025 AIDC-AI
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""
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Asset-Based Pipeline UI
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Implements the UI for generating videos from user-provided assets.
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"""
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import os
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import time
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from pathlib import Path
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from typing import Any
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import streamlit as st
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from loguru import logger
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from web.i18n import tr, get_language
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from web.pipelines.base import PipelineUI, register_pipeline_ui
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from web.components.content_input import render_bgm_section, render_version_info
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from web.utils.async_helpers import run_async
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from pixelle_video.config import config_manager
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from pixelle_video.models.progress import ProgressEvent
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class AssetBasedPipelineUI(PipelineUI):
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"""
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UI for the Asset-Based Video Generation Pipeline.
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Generates videos from user-provided assets (images/videos).
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"""
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name = "asset_based"
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icon = "📦"
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@property
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def display_name(self):
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return tr("pipeline.asset_based.name")
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@property
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def description(self):
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return tr("pipeline.asset_based.description")
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def render(self, pixelle_video: Any):
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# Three-column layout
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left_col, middle_col, right_col = st.columns([1, 1, 1])
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# ====================================================================
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# Left Column: Asset Upload & Video Info
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# ====================================================================
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with left_col:
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asset_params = self._render_asset_input()
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bgm_params = render_bgm_section(key_prefix="asset_")
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render_version_info()
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# ====================================================================
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# Middle Column: Video Configuration
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# ====================================================================
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with middle_col:
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config_params = self._render_video_config(pixelle_video)
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# ====================================================================
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# Right Column: Output Preview
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# ====================================================================
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with right_col:
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# Combine all parameters
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video_params = {
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"pipeline": self.name,
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**asset_params,
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**bgm_params,
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**config_params
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}
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self._render_output_preview(pixelle_video, video_params)
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def _render_asset_input(self) -> dict:
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"""Render asset upload section"""
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with st.container(border=True):
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st.markdown(f"**{tr('asset_based.section.assets')}**")
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with st.expander(tr("help.feature_description"), expanded=False):
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st.markdown(f"**{tr('help.what')}**")
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st.markdown(tr("asset_based.assets.what"))
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st.markdown(f"**{tr('help.how')}**")
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st.markdown(tr("asset_based.assets.how"))
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# File uploader for multiple files
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uploaded_files = st.file_uploader(
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tr("asset_based.assets.upload"),
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type=["jpg", "jpeg", "png", "gif", "webp", "mp4", "mov", "avi", "mkv", "webm"],
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accept_multiple_files=True,
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help=tr("asset_based.assets.upload_help"),
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key="asset_files"
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)
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# Save uploaded files to temp directory with unique session ID
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asset_paths = []
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if uploaded_files:
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import uuid
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session_id = str(uuid.uuid4()).replace('-', '')[:12]
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temp_dir = Path(f"temp/assets_{session_id}")
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temp_dir.mkdir(parents=True, exist_ok=True)
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for uploaded_file in uploaded_files:
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file_path = temp_dir / uploaded_file.name
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with open(file_path, "wb") as f:
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f.write(uploaded_file.getbuffer())
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asset_paths.append(str(file_path.absolute()))
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st.success(tr("asset_based.assets.count", count=len(asset_paths)))
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# Preview uploaded assets
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with st.expander(tr("asset_based.assets.preview"), expanded=True):
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# Show in a grid (3 columns)
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cols = st.columns(3)
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for i, (file, path) in enumerate(zip(uploaded_files, asset_paths)):
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with cols[i % 3]:
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# Check if image or video
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ext = Path(path).suffix.lower()
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if ext in [".jpg", ".jpeg", ".png", ".gif", ".webp"]:
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st.image(file, caption=file.name, use_container_width=True)
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elif ext in [".mp4", ".mov", ".avi", ".mkv", ".webm"]:
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st.video(file)
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st.caption(file.name)
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else:
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st.info(tr("asset_based.assets.empty_hint"))
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# Video title & intent
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with st.container(border=True):
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st.markdown(f"**{tr('asset_based.section.video_info')}**")
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video_title = st.text_input(
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tr("asset_based.video_title"),
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placeholder=tr("asset_based.video_title_placeholder"),
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help=tr("asset_based.video_title_help"),
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key="asset_video_title"
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)
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intent = st.text_area(
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tr("asset_based.intent"),
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placeholder=tr("asset_based.intent_placeholder"),
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help=tr("asset_based.intent_help"),
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height=100,
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key="asset_intent"
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)
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return {
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"assets": asset_paths,
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"video_title": video_title,
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"intent": intent if intent else None
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}
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def _render_video_config(self, pixelle_video: Any) -> dict:
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"""Render video configuration section"""
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# Duration configuration
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with st.container(border=True):
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st.markdown(f"**{tr('video.title')}**")
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# Duration slider
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duration = st.slider(
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tr("asset_based.duration"),
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min_value=15,
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max_value=120,
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value=30,
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step=5,
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help=tr("asset_based.duration_help"),
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key="asset_duration"
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)
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st.caption(tr("asset_based.duration_label", seconds=duration))
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# Workflow source selection
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with st.container(border=True):
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st.markdown(f"**{tr('asset_based.section.source')}**")
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with st.expander(tr("help.feature_description"), expanded=False):
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st.markdown(f"**{tr('help.what')}**")
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st.markdown(tr("asset_based.source.what"))
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st.markdown(f"**{tr('help.how')}**")
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st.markdown(tr("asset_based.source.how"))
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source_options = {
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"runninghub": tr("asset_based.source.runninghub"),
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"selfhost": tr("asset_based.source.selfhost")
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}
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# Check if RunningHub API key is configured
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comfyui_config = config_manager.get_comfyui_config()
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has_runninghub = bool(comfyui_config.get("runninghub_api_key"))
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has_selfhost = bool(comfyui_config.get("comfyui_url"))
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# Default to available source
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if has_runninghub:
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default_source_index = 0
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elif has_selfhost:
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default_source_index = 1
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else:
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default_source_index = 0
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source = st.radio(
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tr("asset_based.source.select"),
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options=list(source_options.keys()),
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format_func=lambda x: source_options[x],
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index=default_source_index,
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horizontal=True,
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key="asset_source",
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label_visibility="collapsed"
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)
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# Show hint based on selection
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if source == "runninghub":
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if not has_runninghub:
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st.warning(tr("asset_based.source.runninghub_not_configured"))
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else:
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st.info(tr("asset_based.source.runninghub_hint"))
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else:
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if not has_selfhost:
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st.warning(tr("asset_based.source.selfhost_not_configured"))
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else:
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st.info(tr("asset_based.source.selfhost_hint"))
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# TTS configuration
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with st.container(border=True):
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st.markdown(f"**{tr('section.tts')}**")
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# Import voice configuration
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from pixelle_video.tts_voices import EDGE_TTS_VOICES, get_voice_display_name
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# Get saved voice from config
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comfyui_config = config_manager.get_comfyui_config()
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tts_config = comfyui_config.get("tts", {})
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local_config = tts_config.get("local", {})
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saved_voice = local_config.get("voice", "zh-CN-YunjianNeural")
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saved_speed = local_config.get("speed", 1.2)
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# Build voice options with i18n
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voice_options = []
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voice_ids = []
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default_voice_index = 0
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|
||||
for idx, voice_config in enumerate(EDGE_TTS_VOICES):
|
||||
voice_id = voice_config["id"]
|
||||
display_name = get_voice_display_name(voice_id, tr, get_language())
|
||||
voice_options.append(display_name)
|
||||
voice_ids.append(voice_id)
|
||||
|
||||
if voice_id == saved_voice:
|
||||
default_voice_index = idx
|
||||
|
||||
# Two-column layout
|
||||
voice_col, speed_col = st.columns([1, 1])
|
||||
|
||||
with voice_col:
|
||||
selected_voice_display = st.selectbox(
|
||||
tr("tts.voice_selector"),
|
||||
voice_options,
|
||||
index=default_voice_index,
|
||||
key="asset_tts_voice"
|
||||
)
|
||||
selected_voice_index = voice_options.index(selected_voice_display)
|
||||
voice_id = voice_ids[selected_voice_index]
|
||||
|
||||
with speed_col:
|
||||
tts_speed = st.slider(
|
||||
tr("tts.speed"),
|
||||
min_value=0.5,
|
||||
max_value=2.0,
|
||||
value=saved_speed,
|
||||
step=0.1,
|
||||
format="%.1fx",
|
||||
key="asset_tts_speed"
|
||||
)
|
||||
st.caption(tr("tts.speed_label", speed=f"{tts_speed:.1f}"))
|
||||
|
||||
return {
|
||||
"duration": duration,
|
||||
"source": source,
|
||||
"voice_id": voice_id,
|
||||
"tts_speed": tts_speed
|
||||
}
|
||||
|
||||
def _render_output_preview(self, pixelle_video: Any, video_params: dict):
|
||||
"""Render output preview section"""
|
||||
with st.container(border=True):
|
||||
st.markdown(f"**{tr('section.video_generation')}**")
|
||||
|
||||
# Check configuration
|
||||
if not config_manager.validate():
|
||||
st.warning(tr("settings.not_configured"))
|
||||
|
||||
# Check if assets are provided
|
||||
assets = video_params.get("assets", [])
|
||||
if not assets:
|
||||
st.info(tr("asset_based.output.no_assets"))
|
||||
st.button(
|
||||
tr("btn.generate"),
|
||||
type="primary",
|
||||
use_container_width=True,
|
||||
disabled=True,
|
||||
key="asset_generate_disabled"
|
||||
)
|
||||
return
|
||||
|
||||
# Show asset summary
|
||||
st.info(tr("asset_based.output.ready", count=len(assets)))
|
||||
|
||||
# Generate button
|
||||
if st.button(tr("btn.generate"), type="primary", use_container_width=True, key="asset_generate"):
|
||||
# Validate
|
||||
if not config_manager.validate():
|
||||
st.error(tr("settings.not_configured"))
|
||||
st.stop()
|
||||
|
||||
# Show progress
|
||||
progress_bar = st.progress(0)
|
||||
status_text = st.empty()
|
||||
|
||||
start_time = time.time()
|
||||
|
||||
try:
|
||||
# Import pipeline
|
||||
from pixelle_video.pipelines.asset_based import AssetBasedPipeline
|
||||
|
||||
# Create pipeline
|
||||
pipeline = AssetBasedPipeline(pixelle_video)
|
||||
|
||||
# Progress callback
|
||||
def update_progress(event: ProgressEvent):
|
||||
if event.event_type == "analyzing_assets":
|
||||
if event.extra_info == "start":
|
||||
message = tr("asset_based.progress.analyzing_start", total=event.frame_total)
|
||||
else:
|
||||
message = tr("asset_based.progress.analyzing_complete", count=event.frame_total)
|
||||
elif event.event_type == "analyzing_asset":
|
||||
message = tr(
|
||||
"asset_based.progress.analyzing_asset",
|
||||
current=event.frame_current,
|
||||
total=event.frame_total,
|
||||
name=event.extra_info or ""
|
||||
)
|
||||
elif event.event_type == "generating_script":
|
||||
if event.extra_info == "complete":
|
||||
message = tr("asset_based.progress.script_complete")
|
||||
else:
|
||||
message = tr("asset_based.progress.generating_script")
|
||||
elif event.event_type == "frame_step":
|
||||
action_key = f"progress.step_{event.action}"
|
||||
action_text = tr(action_key)
|
||||
message = tr(
|
||||
"progress.frame_step",
|
||||
current=event.frame_current,
|
||||
total=event.frame_total,
|
||||
step=event.step,
|
||||
action=action_text
|
||||
)
|
||||
elif event.event_type == "processing_frame":
|
||||
message = tr(
|
||||
"progress.frame",
|
||||
current=event.frame_current,
|
||||
total=event.frame_total
|
||||
)
|
||||
elif event.event_type == "concatenating":
|
||||
if event.extra_info == "complete":
|
||||
message = tr("asset_based.progress.concat_complete")
|
||||
else:
|
||||
message = tr("progress.concatenating")
|
||||
elif event.event_type == "completed":
|
||||
message = tr("progress.completed")
|
||||
else:
|
||||
message = tr(f"progress.{event.event_type}")
|
||||
|
||||
status_text.text(message)
|
||||
progress_bar.progress(min(int(event.progress * 100), 99))
|
||||
|
||||
# Execute pipeline with progress callback
|
||||
ctx = run_async(pipeline(
|
||||
assets=video_params["assets"],
|
||||
video_title=video_params.get("video_title", ""),
|
||||
intent=video_params.get("intent"),
|
||||
duration=video_params.get("duration", 30),
|
||||
source=video_params.get("source", "runninghub"),
|
||||
bgm_path=video_params.get("bgm_path"),
|
||||
bgm_volume=video_params.get("bgm_volume", 0.2),
|
||||
bgm_mode=video_params.get("bgm_mode", "loop"),
|
||||
voice_id=video_params.get("voice_id", "zh-CN-YunjianNeural"),
|
||||
tts_speed=video_params.get("tts_speed", 1.2),
|
||||
progress_callback=update_progress
|
||||
))
|
||||
|
||||
total_time = time.time() - start_time
|
||||
|
||||
progress_bar.progress(100)
|
||||
status_text.text(tr("status.success"))
|
||||
|
||||
# Display result
|
||||
st.success(tr("status.video_generated", path=ctx.final_video_path))
|
||||
|
||||
st.markdown("---")
|
||||
|
||||
# Video info
|
||||
if os.path.exists(ctx.final_video_path):
|
||||
file_size_mb = os.path.getsize(ctx.final_video_path) / (1024 * 1024)
|
||||
n_scenes = len(ctx.storyboard.frames) if ctx.storyboard else 0
|
||||
|
||||
info_text = (
|
||||
f"⏱️ {tr('info.generation_time')} {total_time:.1f}s "
|
||||
f"📦 {file_size_mb:.2f}MB "
|
||||
f"🎬 {n_scenes}{tr('info.scenes_unit')}"
|
||||
)
|
||||
st.caption(info_text)
|
||||
|
||||
st.markdown("---")
|
||||
|
||||
# Video preview
|
||||
st.video(ctx.final_video_path)
|
||||
|
||||
# Download button
|
||||
with open(ctx.final_video_path, "rb") as video_file:
|
||||
video_bytes = video_file.read()
|
||||
video_filename = os.path.basename(ctx.final_video_path)
|
||||
st.download_button(
|
||||
label="⬇️ 下载视频" if get_language() == "zh_CN" else "⬇️ Download Video",
|
||||
data=video_bytes,
|
||||
file_name=video_filename,
|
||||
mime="video/mp4",
|
||||
use_container_width=True
|
||||
)
|
||||
else:
|
||||
st.error(tr("status.video_not_found", path=ctx.final_video_path))
|
||||
|
||||
except Exception as e:
|
||||
status_text.text("")
|
||||
progress_bar.empty()
|
||||
st.error(tr("status.error", error=str(e)))
|
||||
logger.exception(e)
|
||||
st.stop()
|
||||
|
||||
|
||||
# Register self
|
||||
register_pipeline_ui(AssetBasedPipelineUI)
|
||||
|
||||
@@ -1,69 +0,0 @@
|
||||
# Copyright (C) 2025 AIDC-AI
|
||||
#
|
||||
# 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.
|
||||
|
||||
"""
|
||||
Demo Pipeline UI
|
||||
|
||||
Implements a custom layout for the Demo Pipeline.
|
||||
"""
|
||||
|
||||
import streamlit as st
|
||||
from typing import Any
|
||||
from web.i18n import tr
|
||||
|
||||
from web.pipelines.base import PipelineUI, register_pipeline_ui
|
||||
|
||||
|
||||
class DemoPipelineUI(PipelineUI):
|
||||
"""
|
||||
Demo UI to verify the full-page plugin system.
|
||||
Uses a completely different layout (2 columns).
|
||||
"""
|
||||
name = "demo"
|
||||
icon = "✨"
|
||||
|
||||
@property
|
||||
def display_name(self):
|
||||
return tr("pipeline.demo.name")
|
||||
|
||||
@property
|
||||
def description(self):
|
||||
return tr("pipeline.demo.description")
|
||||
|
||||
def render(self, pixelle_video: Any):
|
||||
st.markdown("### ✨ Demo Pipeline Custom Layout")
|
||||
st.info("This pipeline uses a custom 2-column layout, demonstrating full UI control.")
|
||||
|
||||
col1, col2 = st.columns([2, 1])
|
||||
|
||||
with col1:
|
||||
with st.container(border=True):
|
||||
st.subheader("1. Input")
|
||||
topic = st.text_input("Enter Topic", placeholder="e.g. AI News")
|
||||
mood = st.selectbox("Mood", ["Happy", "Serious", "Funny"])
|
||||
|
||||
st.markdown("---")
|
||||
st.subheader("2. Settings")
|
||||
# Simplified settings for demo
|
||||
n_scenes = st.slider("Scenes", 3, 10, 5)
|
||||
|
||||
with col2:
|
||||
with st.container(border=True):
|
||||
st.subheader("3. Generate")
|
||||
if st.button("🚀 Generate Demo Video", type="primary", use_container_width=True):
|
||||
# Mock generation logic or call backend
|
||||
st.success(f"Generating video for '{topic}' ({mood}) with {n_scenes} scenes...")
|
||||
st.balloons()
|
||||
|
||||
|
||||
# Register self
|
||||
register_pipeline_ui(DemoPipelineUI)
|
||||
Reference in New Issue
Block a user