ce32073d07
- 面板: 会话持久化(oc_sess.json)/余额实时/文件栏(搜索+MD+拖拽)/朗读(edge-tts)/工具过程实时显示/漫剧画布 - 面板: 经验自动检索注入+存经验按钮(experience.py) - 管线: local_motion本地运镜/IMAGE-FIRST-GUIDE/LOCAL-PIPELINE-V1 - 经验: EED-EXPER-014 面板工程+管线+飞书扒取全记录 - 资料: 飞书《清欢AIGC伪真人短剧全流程》归档
221 lines
8.5 KiB
Python
221 lines
8.5 KiB
Python
#!/usr/bin/env python3
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"""
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storyboard_to_workflow.py — 分镜JSON → ComfyUI批量出图桥接
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读取分镜JSON，为每个镜头生成ComfyUI API调用脚本
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用法:
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python tools/storyboard_to_workflow.py <分镜JSON> [-o 输出目录] [--workflow 基础工作流]
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python tools/storyboard_to_workflow.py <分镜JSON> --generate-sh # 生成批量调用shell脚本
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"""
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import sys, os, json, argparse, shutil
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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# 默认的工作流模板路径（ComfyUI蓝图）
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DEFAULT_WORKFLOW = os.path.expanduser("~/comfy/ComfyUI/blueprints/Text to Image.json")
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def load_storyboard(json_path):
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"""读取分镜JSON"""
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with open(json_path, 'r', encoding='utf-8') as f:
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return json.load(f)
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def shot_to_prompt(shot, project_style=""):
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"""将单镜转换为图像生成prompt"""
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desc = shot.get('description', '')
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camera = shot.get('camera', '中景')
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characters = shot.get('characters', [])
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scenes = shot.get('scenes', [])
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props = shot.get('props', [])
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# 构建英文prompt
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parts = []
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if camera:
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parts.append(camera)
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if scenes:
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parts.append(f"in {scenes[0]}")
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parts.append(desc[:80])
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if project_style:
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parts.append(project_style)
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prompt = ", ".join(parts)
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return prompt
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def generate_comfyui_api_json(shot, base_workflow_path, prompt, output_dir, shot_num):
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"""为单镜生成ComfyUI API调用JSON"""
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# 读取基础工作流
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try:
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with open(base_workflow_path, 'r') as f:
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workflow = json.load(f)
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except:
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# 如果文件不存在，创建一个最小工作流
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workflow = {
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"3": {
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"class_type": "KSampler",
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"inputs": {
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"seed": shot_num * 100 + 42,
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"steps": 20,
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"cfg": 7,
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"sampler_name": "euler",
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"scheduler": "normal",
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"denoise": 1,
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"model": ["4", 0],
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"positive": ["6", 0],
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"negative": ["7", 0],
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"latent_image": ["5", 0]
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}
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},
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"4": {"class_type": "CheckpointLoaderSimple", "inputs": {"ckpt_name": "realvisxlV40_v40BDFPonNoobVae.safetensors"}},
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"5": {"class_type": "EmptyLatentImage", "inputs": {"width": 1024, "height": 768, "batch_size": 1}},
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"6": {"class_type": "CLIPTextEncode", "inputs": {"text": prompt, "clip": ["4", 1]}},
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"7": {"class_type": "CLIPTextEncode", "inputs": {"text": "worst quality, low quality, blurry", "clip": ["4", 1]}},
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"8": {"class_type": "VAEDecode", "inputs": {"samples": ["3", 0], "vae": ["4", 2]}},
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"9": {"class_type": "SaveImage", "inputs": {"filename_prefix": f"shot_{shot_num:04d}", "images": ["8", 0]}}
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}
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return workflow
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# 如果用了现有工作流，替换prompt
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for node_id, node in workflow.items():
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if isinstance(node, dict):
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ct = node.get('class_type', '')
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if 'CLIPTextEncode' in ct or 'Prompt' in ct:
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if 'text' in node.get('inputs', {}):
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workflow[node_id]['inputs']['text'] = prompt
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if 'KSampler' in ct or 'Sampler' in ct:
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if 'seed' in node.get('inputs', {}):
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workflow[node_id]['inputs']['seed'] = shot_num * 100 + 42
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return workflow
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def generate_shell_script(shots, output_dir, comfy_api_url="http://127.0.0.1:8188"):
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"""生成批量调用ComfyUI API的shell脚本"""
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script_path = os.path.join(output_dir, 'batch_render.sh')
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lines = [
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'#!/bin/bash',
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f'# 批量渲染分镜 - 自动生成',
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f'# ComfyUI API: {comfy_api_url}',
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f'# 分镜数: {len(shots)}',
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f'# 生成时间: {__import__("datetime").datetime.now().isoformat()}',
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'',
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'set -e',
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'',
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'TOTAL=' + str(len(shots)),
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'SUCCESS=0',
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'FAIL=0',
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'',
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]
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for i, shot in enumerate(shots):
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sn = shot.get('shot_number', f'S{i+1:02d}')
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desc = shot.get('description', '')[:40]
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wf_file = os.path.join(output_dir, f'workflow_{i+1:04d}.json')
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out_file = os.path.join(output_dir, f'shot_{i+1:04d}.png')
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lines.extend([
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f'',
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f'echo "🎬 [{i+1}/$TOTAL] {sn}: {desc}"',
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f'echo " → 发送ComfyUI API..."',
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f'RESP=$(curl -s -X POST "{comfy_api_url}/prompt" \\',
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f' -H "Content-Type: application/json" \\',
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f' -d @{wf_file})',
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f'if echo "$RESP" | grep -q "error"; then',
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f' echo " ❌ 失败: $RESP"',
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f' FAIL=$((FAIL + 1))',
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f'else',
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f' echo " ✅ 已提交"',
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f' SUCCESS=$((SUCCESS + 1))',
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f'fi',
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])
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lines.extend([
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'',
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'echo "=========================="',
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'echo "📊 渲染完成: $SUCCESS 成功, $FAIL 失败 / $TOTAL 总镜"',
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])
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with open(script_path, 'w') as f:
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f.write('\n'.join(lines))
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os.chmod(script_path, 0o755)
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return script_path
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def generate_prompt_file(shots, output_dir, project_style=""):
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"""生成每个镜头的prompt文本文件"""
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prompt_path = os.path.join(output_dir, 'prompts.txt')
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with open(prompt_path, 'w', encoding='utf-8') as f:
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for i, shot in enumerate(shots):
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sn = shot.get('shot_number', f'S{i+1:02d}')
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prompt = shot_to_prompt(shot, project_style)
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f.write(f"=== {sn} ===\n")
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f.write(f"景别: {shot.get('camera', 'N/A')}\n")
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f.write(f"时长: {shot.get('duration', 'N/A')}s\n")
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f.write(f"角色: {', '.join(shot.get('characters', []))}\n")
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f.write(f"场景: {', '.join(shot.get('scenes', []))}\n")
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f.write(f"Prompt: {prompt}\n\n")
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return prompt_path
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def main():
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parser = argparse.ArgumentParser(description='分镜JSON → ComfyUI批量出图桥接')
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parser.add_argument('storyboard', help='分镜JSON文件路径')
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parser.add_argument('-o', '--output-dir', help='输出目录 (默认: 分镜JSON同目录下的renders/)')
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parser.add_argument('--workflow', default=DEFAULT_WORKFLOW, help=f'基础工作流JSON (默认: {DEFAULT_WORKFLOW})')
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parser.add_argument('--style', default='', help='全局风格描述 (如: cinematic, anime)')
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parser.add_argument('--generate-sh', action='store_true', help='生成批量调用shell脚本')
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parser.add_argument('--comfy-url', default='http://127.0.0.1:8188', help='ComfyUI API地址')
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args = parser.parse_args()
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# 读取分镜
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storyboard = load_storyboard(args.storyboard)
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shots = storyboard.get('shots', [])
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if not shots:
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print(f'❌ 分镜JSON中没有shots')
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sys.exit(1)
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# 输出目录
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if args.output_dir:
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out_dir = args.output_dir
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else:
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sb_dir = os.path.dirname(os.path.abspath(args.storyboard))
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out_dir = os.path.join(sb_dir, 'renders')
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os.makedirs(out_dir, exist_ok=True)
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print(f'📖 分镜: {args.storyboard}')
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print(f'🎬 共 {len(shots)} 镜')
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print(f'📁 输出: {out_dir}')
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print()
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# 1. 生成prompt文件
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prompt_path = generate_prompt_file(shots, out_dir, args.style)
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print(f'✅ Prompt文件: {prompt_path}')
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# 2. 为每镜生成工作流JSON
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wf_dir = os.path.join(out_dir, 'workflows')
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os.makedirs(wf_dir, exist_ok=True)
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for i, shot in enumerate(shots):
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sn = shot.get('shot_number', f'S{i+1:02d}')
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prompt = shot_to_prompt(shot, args.style)
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workflow = generate_comfyui_api_json(shot, args.workflow, prompt, wf_dir, i+1)
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wf_path = os.path.join(wf_dir, f'workflow_{i+1:04d}.json')
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with open(wf_path, 'w', encoding='utf-8') as f:
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json.dump(workflow, f, ensure_ascii=False, indent=2)
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print(f'✅ 工作流JSON: {len(shots)}个 → {wf_dir}/')
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# 3. 可选：生成批量shell脚本
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if args.generate_sh:
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sh_path = generate_shell_script(shots, out_dir, args.comfy_url)
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print(f'✅ 批量脚本: {sh_path}')
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print(f' 运行: bash {sh_path}')
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# 4. 总结
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print()
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print('📊 各镜一览:')
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for i, shot in enumerate(shots):
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sn = shot.get('shot_number', f'S{i+1:02d}')
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prompt = shot_to_prompt(shot, args.style)
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print(f' {sn:>4} | {shot.get("camera","?"): <4} | {shot.get("duration","?"):>2}s | {prompt[:50]}...')
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if __name__ == '__main__':
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main()
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