asset: 归档第一集已生成镜头与测试素材，排除可再生缓存
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# 泉堂夜景 · 第一条视频测试
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2026-09-29 · REVIEW · 仅用于看动态氛围，不是第一集完成片。
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## 先看视频
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[播放／下载 V02 测试片](V02_5B/2026-09-29_EP01_CHAPEL_NIGHT_WAN22_TEST_V02_5B_00001.mp4)
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[六帧审看图](V02_5B/2026-09-29_EP01_CHAPEL_NIGHT_WAN22_TEST_V02_5B_00001_sheet.png)
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- 实测：5.041667 秒，121 帧，768×448，24 fps，H.264／yuv420p，BT.709，无音轨、无字幕。
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- 这不是标准 16:9 正式交付画幅；5B 测试沿用模型的 32 像素尺寸步长。正式镜头需重新规划画幅，不能直接拉伸。
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- 内容：泉堂夜间空景、烛火／炉火轻晃、克制的镜头运动。神像不说话、不显灵，不增加小说设定。
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- 原图：第一集 V05 制作包中的 `BG-EP01-CHAPEL-NIGHT-V01-REVIEW.png`，本身尚未定稿；北窗与神像旧裂等原有问题仍待修订。
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## 生成与检查
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使用本地已安装的动漫制作、ComfyUI 与视频审看技能：限制动作幅度，保留原图作首帧约束，真实运行后抽帧检查，不将文件存在等同于视觉合格。
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1. V01：Wan 2.2 I2V 双 14B FP8 + 官方 4 步 LoRA。768×432、81 帧、16 fps；在低噪模型加载／LoRA 重量再量化时发生显存不足。未生成视频；根目录保留工作流、任务和错误记录供排查。
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2. V02：使用服务器现有的 `wan2.2_ti2v_5B_fp16.safetensors`，配套 `wan2.2_vae.safetensors`、UMT5；20 步、CFG 5、uni_pc/simple、shift 8、随机种子 2879138632582。任务成功，提交到下载约 105 秒。
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3. 六帧抽查：保留了冷窗光与暖火光关系，未见明显神像肢体变形或建筑大幅漂移；细节偏软。期望的向前推进不明显，尚不能视为运镜验收通过，也不能证明人物表演质量。
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4. 格式／内容检查：8 项，0 失败，2 项警告（无音轨、无字幕，均为本次纯视觉测试的有意选择）；未检出黑场或整段冻结。抽帧检查不是逐帧验收。
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参考：[ComfyUI 官方 Wan 2.2 工作流说明](https://docs.comfy.org/tutorials/video/wan/wan2_2)。实际源模板副本与精确参数保存在各版本目录中。
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## 在自己的 ComfyUI 打开
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打开 `http://192.168.10.51:8188`，在 Workflows 中找到：
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`hearthfire_tests/2026-09-29_EP01_CHAPEL_NIGHT_WAN22_TEST_V02_5B.json`
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工作流已通过 userdata 写入并回读核验；布局检查 11 节点、12 连线、0 重叠。对应本地文件：
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- [GUI 工作流（拖入 ComfyUI）](V02_5B/workflow_gui.json)
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- [API 工作流（执行参数）](V02_5B/workflow_api.json)
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- [任务记录](V02_5B/job.json)
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- [执行历史](V02_5B/history.json)
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服务器视频：`output/hearthfire_tests/2026-09-29_EP01_CHAPEL_NIGHT_WAN22_TEST_V02_5B_00001.mp4`。
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运行脚本 `render_test.py --variant 5b --collect` 只回收既有任务结果；去掉 `--collect` 遇到已有 job.json 会拒绝重复提交。本次没有重启服务器、修改模型／节点或覆盖原有模板，也没有提交或推送 Git。
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## 你现在主要看什么
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先判断氛围是否对、画面是否太暗、动态是否太轻。下一条若测试人物，应先把角色参考表转成真正的单镜头首帧，再做抬眼／眨眼等简单表演；本片无法验证角色一致性和口型。
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"## Model Links\n\n- [Hugging Face:Comfy-Org/Wan_2.2_ComfyUI_Repackaged](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged)\n- [ModelScope:Comfy-Org/Wan_2.2_ComfyUI_Repackaged](https://modelscope.cn/models/Comfy-Org/Wan_2.2_ComfyUI_Repackaged)\n- [Hugging Face:Comfy-Org/Wan_2.1_ComfyUI_repackaged](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged)\n- [ModelScope:Comfy-Org/Wan_2.1_ComfyUI_repackaged](https://modelscope.cn/models/Comfy-Org/Wan_2.1_ComfyUI_repackaged)\n\n[Tutorial](https://docs.comfy.org/tutorials/video/wan/wan2_2\n) \n\n**Diffusion Model**\n- [wan2.2_ti2v_5B_fp16.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/diffusion_models/wan2.2_ti2v_5B_fp16.safetensors) (9.31 GB)\n\n**VAE**\n- [wan2.2_vae.safetensors](https://huggingface.co/Comfy-Org/Wan_2.2_ComfyUI_Repackaged/resolve/main/split_files/vae/wan2.2_vae.safetensors) (1.31 GB)\n\n**Text Encoder** \n- [umt5_xxl_fp8_e4m3fn_scaled.safetensors](https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/resolve/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors) (6.27 GB)\n\n\nFile save location\n\n```\nComfyUI/\n├───📂 models/\n│ ├───📂 diffusion_models/\n│ │ └───wan2.2_ti2v_5B_fp16.safetensors\n│ ├───📂 text_encoders/\n│ │ └─── umt5_xxl_fp8_e4m3fn_scaled.safetensors \n│ └───📂 vae/\n│ └── wan2.2_vae.safetensors\n```\n"
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|
||||
"outputs": [
|
||||
{
|
||||
"name": "LATENT",
|
||||
"type": "LATENT",
|
||||
"links": [
|
||||
12
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "Wan22ImageToVideoLatent"
|
||||
},
|
||||
"widgets_values": [
|
||||
768,
|
||||
448,
|
||||
121,
|
||||
1
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 14,
|
||||
"type": "KSampler",
|
||||
"pos": [
|
||||
960,
|
||||
691
|
||||
],
|
||||
"size": [
|
||||
340,
|
||||
370
|
||||
],
|
||||
"flags": {},
|
||||
"order": 13,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "model",
|
||||
"type": "MODEL",
|
||||
"link": 9
|
||||
},
|
||||
{
|
||||
"name": "positive",
|
||||
"type": "CONDITIONING",
|
||||
"link": 10
|
||||
},
|
||||
{
|
||||
"name": "negative",
|
||||
"type": "CONDITIONING",
|
||||
"link": 11
|
||||
},
|
||||
{
|
||||
"name": "latent_image",
|
||||
"type": "LATENT",
|
||||
"link": 12
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "LATENT",
|
||||
"type": "LATENT",
|
||||
"links": [
|
||||
3
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "KSampler"
|
||||
},
|
||||
"widgets_values": [
|
||||
2879138632582,
|
||||
"fixed",
|
||||
20,
|
||||
5.0,
|
||||
"uni_pc",
|
||||
"simple",
|
||||
1.0
|
||||
]
|
||||
}
|
||||
],
|
||||
"links": [
|
||||
[
|
||||
1,
|
||||
8,
|
||||
0,
|
||||
10,
|
||||
0,
|
||||
"CLIP"
|
||||
],
|
||||
[
|
||||
2,
|
||||
8,
|
||||
0,
|
||||
11,
|
||||
0,
|
||||
"CLIP"
|
||||
],
|
||||
[
|
||||
3,
|
||||
14,
|
||||
0,
|
||||
15,
|
||||
0,
|
||||
"LATENT"
|
||||
],
|
||||
[
|
||||
4,
|
||||
9,
|
||||
0,
|
||||
15,
|
||||
1,
|
||||
"VAE"
|
||||
],
|
||||
[
|
||||
5,
|
||||
15,
|
||||
0,
|
||||
16,
|
||||
0,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
6,
|
||||
2,
|
||||
0,
|
||||
6,
|
||||
0,
|
||||
"MODEL"
|
||||
],
|
||||
[
|
||||
7,
|
||||
9,
|
||||
0,
|
||||
12,
|
||||
0,
|
||||
"VAE"
|
||||
],
|
||||
[
|
||||
8,
|
||||
1,
|
||||
0,
|
||||
12,
|
||||
1,
|
||||
"IMAGE"
|
||||
],
|
||||
[
|
||||
9,
|
||||
6,
|
||||
0,
|
||||
14,
|
||||
0,
|
||||
"MODEL"
|
||||
],
|
||||
[
|
||||
10,
|
||||
10,
|
||||
0,
|
||||
14,
|
||||
1,
|
||||
"CONDITIONING"
|
||||
],
|
||||
[
|
||||
11,
|
||||
11,
|
||||
0,
|
||||
14,
|
||||
2,
|
||||
"CONDITIONING"
|
||||
],
|
||||
[
|
||||
12,
|
||||
12,
|
||||
0,
|
||||
14,
|
||||
3,
|
||||
"LATENT"
|
||||
]
|
||||
],
|
||||
"groups": [
|
||||
{
|
||||
"title": "EP01 chapel - Wan 2.2 - 5s visual test",
|
||||
"bounding": [
|
||||
-5,
|
||||
-51,
|
||||
2270,
|
||||
1597
|
||||
],
|
||||
"color": "#335159",
|
||||
"font_size": 24
|
||||
}
|
||||
],
|
||||
"config": {},
|
||||
"extra": {
|
||||
"ds": {
|
||||
"scale": 0.4,
|
||||
"offset": [
|
||||
0,
|
||||
0
|
||||
]
|
||||
}
|
||||
},
|
||||
"version": 0.4
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
@@ -0,0 +1,18 @@
|
||||
{
|
||||
"prompt_id": "182e26dd-a53c-4643-8c88-1a26fbc62674",
|
||||
"number": 0,
|
||||
"node_errors": {},
|
||||
"seed": 57865289174425,
|
||||
"workflow": "workflows/hearthfire_tests/2026-09-29_EP01_CHAPEL_NIGHT_WAN22_TEST_V01.json",
|
||||
"source": "F:\\project\\小说设计\\06_AI动漫制作\\03_分镜与镜头\\S01E01_V05_制作包\\06_参考图\\BG-EP01-CHAPEL-NIGHT-V01-REVIEW.png",
|
||||
"input": {
|
||||
"name": "2026-09-29_EP01_CHAPEL_NIGHT_WAN22_TEST_V01.png",
|
||||
"subfolder": "hearthfire_tests",
|
||||
"type": "input"
|
||||
},
|
||||
"width": 768,
|
||||
"height": 432,
|
||||
"frames": 81,
|
||||
"fps": 16,
|
||||
"submitted_at": 1790626832.4024146
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"summary": "nodes=16 edges=21 overlaps=0 crossings=7 bounds=[40, 40, 3140, 1792]",
|
||||
"overlaps": [],
|
||||
"crossings": 7,
|
||||
"bounds": [
|
||||
40.0,
|
||||
40.0,
|
||||
3140.0,
|
||||
1792.0
|
||||
],
|
||||
"n_nodes": 16,
|
||||
"n_edges": 21
|
||||
}
|
||||
@@ -0,0 +1,229 @@
|
||||
"""One-shot Wan 2.2 test on the owner's existing ComfyUI. No server installs."""
|
||||
import argparse
|
||||
import copy
|
||||
import json
|
||||
import secrets
|
||||
import sys
|
||||
import time
|
||||
from pathlib import Path
|
||||
from urllib.parse import quote
|
||||
|
||||
import requests
|
||||
|
||||
BASE = 'http://192.168.10.51:8188'
|
||||
HERE = Path(__file__).resolve().parent
|
||||
ROOT = HERE.parents[2]
|
||||
SOURCE = ROOT / '03_分镜与镜头/S01E01_V05_制作包/06_参考图/BG-EP01-CHAPEL-NIGHT-V01-REVIEW.png'
|
||||
TEMPLATE = 'workflows/production_pack_20260904/03_generation_cinematic/09_wan22_i2v.json'
|
||||
NAME = '2026-09-29_EP01_CHAPEL_NIGHT_WAN22_TEST_V01'
|
||||
POSITIVE = ('A single uninterrupted wide establishing shot. The camera makes a very slow, '
|
||||
'gentle dolly forward down the central aisle, keeping the stone statue centered. '
|
||||
'The small candle flames and the distant hearth fire flicker softly, casting faint '
|
||||
'warm moving light on the stone. The statue is inanimate stone and stays completely '
|
||||
'rigid, with an unchanged face and hands. Wooden pews, masonry and hanging cloth remain '
|
||||
'stable. Preserve the reference image composition, delicate drawn contours, richly '
|
||||
'hand-painted anime background, muted colors, cool blue window light and warm amber '
|
||||
'candlelight. Restrained movement, quiet nighttime atmosphere, stable exposure.')
|
||||
NEGATIVE = ('people, living statue, blinking statue, moving statue, speaking, supernatural glow, '
|
||||
'magic particles, new objects, flickering geometry, morphing, melting, warped architecture, '
|
||||
'camera shake, fast zoom, orbit, cuts, oversaturated, overexposed, photorealistic, '
|
||||
'3d render, text, subtitles, watermark, blurry, low quality')
|
||||
|
||||
|
||||
def get(path):
|
||||
r = requests.get(BASE + path, timeout=30)
|
||||
r.raise_for_status()
|
||||
return r.json()
|
||||
|
||||
|
||||
def save(name, obj):
|
||||
(HERE / name).write_text(json.dumps(obj, ensure_ascii=False, indent=2), encoding='utf-8')
|
||||
|
||||
|
||||
def build():
|
||||
assert SOURCE.is_file(), SOURCE
|
||||
if (HERE / 'job.json').exists():
|
||||
raise RuntimeError('Job already exists. Use --collect; do not accidentally submit twice.')
|
||||
q = get('/queue')
|
||||
if q['queue_running'] or q['queue_pending']:
|
||||
raise RuntimeError('Server is busy; no job submitted.')
|
||||
stats = get('/system_stats')
|
||||
save('server_stats.json', stats)
|
||||
if VARIANT == '5b':
|
||||
r = requests.get('https://raw.githubusercontent.com/Comfy-Org/workflow_templates/main/templates/video_wan2_2_5B_ti2v.json', timeout=30)
|
||||
r.raise_for_status()
|
||||
source_template = r.json()
|
||||
else:
|
||||
source_template = get('/userdata/' + quote(TEMPLATE, safe=''))
|
||||
save('source_template.json', source_template)
|
||||
schema = get('/object_info')
|
||||
seed = secrets.randbelow(2**48)
|
||||
with SOURCE.open('rb') as f:
|
||||
r = requests.post(BASE + '/upload/image', files={'image': (NAME + '.png', f, 'image/png')},
|
||||
data={'type': 'input', 'subfolder': 'hearthfire_tests', 'overwrite': 'false'}, timeout=60)
|
||||
r.raise_for_status()
|
||||
uploaded = r.json()
|
||||
input_name = '/'.join(filter(None, [uploaded.get('subfolder'), uploaded['name']]))
|
||||
graph = {}
|
||||
|
||||
def node(i, cls, **inputs):
|
||||
graph[str(i)] = {'class_type': cls, 'inputs': inputs}
|
||||
|
||||
node(1, 'LoadImage', image=input_name)
|
||||
node(2, 'UNETLoader', unet_name='wan2.2_i2v_high_noise_14B_fp8_scaled.safetensors', weight_dtype='default')
|
||||
node(3, 'UNETLoader', unet_name='wan2.2_i2v_low_noise_14B_fp8_scaled.safetensors', weight_dtype='default')
|
||||
node(4, 'LoraLoaderModelOnly', model=['2', 0], lora_name='wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors', strength_model=1.0)
|
||||
node(5, 'LoraLoaderModelOnly', model=['3', 0], lora_name='wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors', strength_model=1.0)
|
||||
node(6, 'ModelSamplingSD3', model=['4', 0], shift=5.0)
|
||||
node(7, 'ModelSamplingSD3', model=['5', 0], shift=5.0)
|
||||
node(8, 'CLIPLoader', clip_name='umt5_xxl_fp8_e4m3fn_scaled.safetensors', type='wan', device='default')
|
||||
node(9, 'VAELoader', vae_name='wan_2.1_vae.safetensors')
|
||||
node(10, 'CLIPTextEncode', clip=['8', 0], text=POSITIVE)
|
||||
node(11, 'CLIPTextEncode', clip=['8', 0], text=NEGATIVE)
|
||||
node(12, 'WanImageToVideo', positive=['10', 0], negative=['11', 0], vae=['9', 0],
|
||||
start_image=['1', 0], width=768, height=432, length=81, batch_size=1)
|
||||
common = dict(positive=['12', 0], negative=['12', 1], steps=4, cfg=1.0, sampler_name='euler', scheduler='simple')
|
||||
node(13, 'KSamplerAdvanced', model=['6', 0], latent_image=['12', 2], add_noise='enable', noise_seed=seed,
|
||||
start_at_step=0, end_at_step=2, return_with_leftover_noise='enable', **common)
|
||||
node(14, 'KSamplerAdvanced', model=['7', 0], latent_image=['13', 0], add_noise='disable', noise_seed=0,
|
||||
start_at_step=2, end_at_step=4, return_with_leftover_noise='disable', **common)
|
||||
node(15, 'VAEDecode', samples=['14', 0], vae=['9', 0])
|
||||
node(16, 'VHS_VideoCombine', images=['15', 0], frame_rate=16.0, loop_count=0,
|
||||
filename_prefix='hearthfire_tests/' + NAME, format='video/h264-mp4', pingpong=False,
|
||||
save_output=True, pix_fmt='yuv420p', crf=18, save_metadata=True, trim_to_audio=False)
|
||||
|
||||
if VARIANT == '5b':
|
||||
graph = {k: v for k, v in graph.items() if k in ('1', '8', '10', '11', '15', '16')}
|
||||
node(2, 'UNETLoader', unet_name='wan2.2_ti2v_5B_fp16.safetensors', weight_dtype='default')
|
||||
node(6, 'ModelSamplingSD3', model=['2', 0], shift=8.0)
|
||||
node(9, 'VAELoader', vae_name='wan2.2_vae.safetensors')
|
||||
node(12, 'Wan22ImageToVideoLatent', vae=['9', 0], start_image=['1', 0],
|
||||
width=768, height=448, length=121, batch_size=1)
|
||||
node(14, 'KSampler', model=['6', 0], positive=['10', 0], negative=['11', 0],
|
||||
latent_image=['12', 0], seed=seed, steps=20, cfg=5.0,
|
||||
sampler_name='uni_pc', scheduler='simple', denoise=1.0)
|
||||
graph['16']['inputs']['frame_rate'] = 24.0
|
||||
|
||||
# Live type, required-input, model-name and connection validation.
|
||||
for nid, n in graph.items():
|
||||
s = schema[n['class_type']]
|
||||
assert not s.get('api_node'), 'Paid/API nodes are out of scope'
|
||||
specs = {**s['input'].get('required', {}), **s['input'].get('optional', {})}
|
||||
assert set(s['input'].get('required', {})) <= n['inputs'].keys()
|
||||
for key, value in n['inputs'].items():
|
||||
if key not in specs:
|
||||
assert n['class_type'] == 'VHS_VideoCombine'
|
||||
continue
|
||||
kind = specs[key][0]
|
||||
if isinstance(value, list):
|
||||
origin, slot = value
|
||||
assert schema[graph[origin]['class_type']]['output'][slot] == kind, (nid, key)
|
||||
elif isinstance(kind, list) and key != 'image':
|
||||
assert value in kind, (nid, key, value)
|
||||
|
||||
# Emit a flat GUI graph from the exact API graph, retaining widget order.
|
||||
ui = {'last_node_id': 16, 'last_link_id': 0, 'nodes': [], 'links': [], 'groups': [], 'config': {},
|
||||
'extra': {'ds': {'scale': 0.4, 'offset': [0, 0]}}, 'version': 0.4}
|
||||
for nid, n in graph.items():
|
||||
s = schema[n['class_type']]
|
||||
slots, widgets = [], []
|
||||
specs = {**s['input'].get('required', {}), **s['input'].get('optional', {})}
|
||||
for key, spec in specs.items():
|
||||
val = n['inputs'].get(key)
|
||||
kind = spec[0]
|
||||
if isinstance(val, list) or (isinstance(kind, str) and kind not in ('INT', 'FLOAT', 'BOOLEAN', 'STRING', 'COMBO')):
|
||||
slots.append({'name': key, 'type': kind, 'link': None})
|
||||
elif key in n['inputs']:
|
||||
widgets.append(val)
|
||||
if len(spec) > 1 and spec[1].get('control_after_generate'):
|
||||
widgets.append('fixed')
|
||||
if n['class_type'] == 'LoadImage':
|
||||
widgets.append('image')
|
||||
if n['class_type'] == 'VHS_VideoCombine':
|
||||
widgets = {k: v for k, v in n['inputs'].items() if not isinstance(v, list)}
|
||||
ui['nodes'].append({'id': int(nid), 'type': n['class_type'], 'pos': [0, 0], 'size': [340, 260],
|
||||
'flags': {}, 'order': int(nid)-1, 'mode': 0, 'inputs': slots,
|
||||
'outputs': [{'name': name, 'type': typ, 'links': []} for name, typ in zip(s['output_name'], s['output'])],
|
||||
'properties': {'Node name for S&R': n['class_type']}, 'widgets_values': widgets})
|
||||
indexed = {str(n['id']): n for n in ui['nodes']}
|
||||
for nid, n in graph.items():
|
||||
for key, val in n['inputs'].items():
|
||||
if not isinstance(val, list):
|
||||
continue
|
||||
origin, oslot = val
|
||||
slot = next(i for i, item in enumerate(indexed[nid]['inputs']) if item['name'] == key)
|
||||
ui['last_link_id'] += 1
|
||||
link = ui['last_link_id']
|
||||
kind = indexed[origin]['outputs'][oslot]['type']
|
||||
ui['links'].append([link, int(origin), oslot, int(nid), slot, kind])
|
||||
indexed[nid]['inputs'][slot]['link'] = link
|
||||
indexed[origin]['outputs'][oslot]['links'].append(link)
|
||||
sys.path.insert(0, 'C:/Users/zhang/.codex/skills/comfyui')
|
||||
from workflow_layout import auto_layout, inspect, fit_group
|
||||
ui = auto_layout(ui)
|
||||
fit_group(ui, 'EP01 chapel - Wan 2.2 - 5s visual test')
|
||||
layout = inspect(ui)
|
||||
save('layout_check.json', layout)
|
||||
print('Layout:', layout['summary'], flush=True)
|
||||
save('workflow_api.json', graph)
|
||||
save('workflow_gui.json', ui)
|
||||
target = 'workflows/hearthfire_tests/' + NAME + '.json'
|
||||
r = requests.post(BASE + '/userdata/' + quote(target, safe='') + '?overwrite=false', json=ui, timeout=30)
|
||||
r.raise_for_status()
|
||||
assert get('/userdata/' + quote(target, safe='')) == ui
|
||||
r = requests.post(BASE + '/prompt', json={'prompt': graph, 'client_id': NAME,
|
||||
'extra_data': {'extra_pnginfo': {'workflow': ui}}}, timeout=30)
|
||||
save('submission.json', r.json())
|
||||
r.raise_for_status()
|
||||
job = {**r.json(), 'seed': seed, 'workflow': target, 'source': str(SOURCE), 'input': uploaded,
|
||||
'width': 768, 'height': 448 if VARIANT == '5b' else 432,
|
||||
'frames': 121 if VARIANT == '5b' else 81, 'fps': 24 if VARIANT == '5b' else 16,
|
||||
'variant': VARIANT, 'submitted_at': time.time()}
|
||||
save('job.json', job)
|
||||
print(json.dumps(job, ensure_ascii=False), flush=True)
|
||||
|
||||
|
||||
def collect():
|
||||
job = json.loads((HERE / 'job.json').read_text(encoding='utf-8'))
|
||||
pid = job['prompt_id']
|
||||
for attempt in range(160):
|
||||
history = get('/history/' + pid).get(pid)
|
||||
if history:
|
||||
save('history.json', history)
|
||||
if history['status']['status_str'] != 'success':
|
||||
errors = [data for kind, data in history['status']['messages'] if kind == 'execution_error']
|
||||
print(json.dumps([{k: e.get(k) for k in ('node_id', 'node_type', 'exception_type', 'exception_message')} for e in errors], ensure_ascii=False), flush=True)
|
||||
raise RuntimeError('Generation failed; inspect history.json')
|
||||
outputs = []
|
||||
for result in history.get('outputs', {}).values():
|
||||
for entry in result.get('gifs', []) + result.get('videos', []) + result.get('images', []):
|
||||
if not entry.get('filename', '').endswith('.mp4'):
|
||||
continue
|
||||
r = requests.get(BASE + '/view', params={k: entry[k] for k in ('filename', 'subfolder', 'type')}, timeout=90)
|
||||
r.raise_for_status()
|
||||
dest = HERE / entry['filename']
|
||||
dest.write_bytes(r.content)
|
||||
outputs.append(str(dest))
|
||||
assert outputs, 'Successful job has no MP4 output'
|
||||
save('outputs.json', outputs)
|
||||
print(json.dumps({'outputs': outputs, 'elapsed_s': round(time.time()-job['submitted_at'])}, ensure_ascii=False), flush=True)
|
||||
return
|
||||
if attempt % 2 == 0:
|
||||
print('Waiting for job', pid, 'elapsed', round(time.time()-job['submitted_at']), 'seconds', flush=True)
|
||||
time.sleep(15)
|
||||
raise TimeoutError('Job retained on server; run --collect to resume waiting.')
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
p = argparse.ArgumentParser()
|
||||
p.add_argument('--collect', action='store_true')
|
||||
p.add_argument('--variant', choices=['14b', '5b'], default='14b')
|
||||
args = p.parse_args()
|
||||
VARIANT = args.variant
|
||||
if VARIANT == '5b':
|
||||
HERE = HERE / 'V02_5B'
|
||||
HERE.mkdir(exist_ok=True)
|
||||
NAME = NAME.replace('V01', 'V02_5B')
|
||||
if not args.collect:
|
||||
build()
|
||||
collect()
|
||||
@@ -0,0 +1,65 @@
|
||||
{
|
||||
"system": {
|
||||
"os": "linux",
|
||||
"ram_total": 269958979584,
|
||||
"ram_free": 259108089856,
|
||||
"comfyui_version": "0.34.2",
|
||||
"required_frontend_version": "1.49.6",
|
||||
"installed_templates_version": "0.11.50",
|
||||
"required_templates_version": "0.11.50",
|
||||
"comfy_package_versions": [
|
||||
{
|
||||
"name": "comfyui-frontend-package",
|
||||
"installed": "1.49.6",
|
||||
"required": "1.49.6"
|
||||
},
|
||||
{
|
||||
"name": "comfyui-workflow-templates",
|
||||
"installed": "0.11.50",
|
||||
"required": "0.11.50"
|
||||
},
|
||||
{
|
||||
"name": "comfyui-embedded-docs",
|
||||
"installed": "0.5.10",
|
||||
"required": "0.5.10"
|
||||
},
|
||||
{
|
||||
"name": "comfy-kitchen",
|
||||
"installed": "0.2.31",
|
||||
"required": "0.2.31"
|
||||
},
|
||||
{
|
||||
"name": "comfy-aimdo",
|
||||
"installed": "0.4.15",
|
||||
"required": "0.4.15"
|
||||
}
|
||||
],
|
||||
"python_version": "3.10.12 (main, Aug 31 2026, 10:18:17) [GCC 11.4.0]",
|
||||
"pytorch_version": "2.7.1+cu126",
|
||||
"embedded_python": false,
|
||||
"deploy_environment": "local-git",
|
||||
"argv": [
|
||||
"/opt/services/comfyui/main.py",
|
||||
"--listen",
|
||||
"192.168.10.51",
|
||||
"--port",
|
||||
"8188",
|
||||
"--reserve-vram",
|
||||
"4",
|
||||
"--async-offload",
|
||||
"--preview-method",
|
||||
"none"
|
||||
]
|
||||
},
|
||||
"devices": [
|
||||
{
|
||||
"name": "cuda:0 NVIDIA GeForce RTX 4090 : cudaMallocAsync",
|
||||
"type": "cuda",
|
||||
"index": 0,
|
||||
"vram_total": 50864390144,
|
||||
"vram_free": 50450071552,
|
||||
"torch_vram_total": 0,
|
||||
"torch_vram_free": 0
|
||||
}
|
||||
]
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
@@ -0,0 +1,5 @@
|
||||
{
|
||||
"prompt_id": "182e26dd-a53c-4643-8c88-1a26fbc62674",
|
||||
"number": 0,
|
||||
"node_errors": {}
|
||||
}
|
||||
@@ -0,0 +1,215 @@
|
||||
{
|
||||
"1": {
|
||||
"class_type": "LoadImage",
|
||||
"inputs": {
|
||||
"image": "hearthfire_tests/2026-09-29_EP01_CHAPEL_NIGHT_WAN22_TEST_V01.png"
|
||||
}
|
||||
},
|
||||
"2": {
|
||||
"class_type": "UNETLoader",
|
||||
"inputs": {
|
||||
"unet_name": "wan2.2_i2v_high_noise_14B_fp8_scaled.safetensors",
|
||||
"weight_dtype": "default"
|
||||
}
|
||||
},
|
||||
"3": {
|
||||
"class_type": "UNETLoader",
|
||||
"inputs": {
|
||||
"unet_name": "wan2.2_i2v_low_noise_14B_fp8_scaled.safetensors",
|
||||
"weight_dtype": "default"
|
||||
}
|
||||
},
|
||||
"4": {
|
||||
"class_type": "LoraLoaderModelOnly",
|
||||
"inputs": {
|
||||
"model": [
|
||||
"2",
|
||||
0
|
||||
],
|
||||
"lora_name": "wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors",
|
||||
"strength_model": 1.0
|
||||
}
|
||||
},
|
||||
"5": {
|
||||
"class_type": "LoraLoaderModelOnly",
|
||||
"inputs": {
|
||||
"model": [
|
||||
"3",
|
||||
0
|
||||
],
|
||||
"lora_name": "wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors",
|
||||
"strength_model": 1.0
|
||||
}
|
||||
},
|
||||
"6": {
|
||||
"class_type": "ModelSamplingSD3",
|
||||
"inputs": {
|
||||
"model": [
|
||||
"4",
|
||||
0
|
||||
],
|
||||
"shift": 5.0
|
||||
}
|
||||
},
|
||||
"7": {
|
||||
"class_type": "ModelSamplingSD3",
|
||||
"inputs": {
|
||||
"model": [
|
||||
"5",
|
||||
0
|
||||
],
|
||||
"shift": 5.0
|
||||
}
|
||||
},
|
||||
"8": {
|
||||
"class_type": "CLIPLoader",
|
||||
"inputs": {
|
||||
"clip_name": "umt5_xxl_fp8_e4m3fn_scaled.safetensors",
|
||||
"type": "wan",
|
||||
"device": "default"
|
||||
}
|
||||
},
|
||||
"9": {
|
||||
"class_type": "VAELoader",
|
||||
"inputs": {
|
||||
"vae_name": "wan_2.1_vae.safetensors"
|
||||
}
|
||||
},
|
||||
"10": {
|
||||
"class_type": "CLIPTextEncode",
|
||||
"inputs": {
|
||||
"clip": [
|
||||
"8",
|
||||
0
|
||||
],
|
||||
"text": "A single uninterrupted wide establishing shot. The camera makes a very slow, gentle dolly forward down the central aisle, keeping the stone statue centered. The small candle flames and the distant hearth fire flicker softly, casting faint warm moving light on the stone. The statue is inanimate stone and stays completely rigid, with an unchanged face and hands. Wooden pews, masonry and hanging cloth remain stable. Preserve the reference image composition, delicate drawn contours, richly hand-painted anime background, muted colors, cool blue window light and warm amber candlelight. Restrained movement, quiet nighttime atmosphere, stable exposure."
|
||||
}
|
||||
},
|
||||
"11": {
|
||||
"class_type": "CLIPTextEncode",
|
||||
"inputs": {
|
||||
"clip": [
|
||||
"8",
|
||||
0
|
||||
],
|
||||
"text": "people, living statue, blinking statue, moving statue, speaking, supernatural glow, magic particles, new objects, flickering geometry, morphing, melting, warped architecture, camera shake, fast zoom, orbit, cuts, oversaturated, overexposed, photorealistic, 3d render, text, subtitles, watermark, blurry, low quality"
|
||||
}
|
||||
},
|
||||
"12": {
|
||||
"class_type": "WanImageToVideo",
|
||||
"inputs": {
|
||||
"positive": [
|
||||
"10",
|
||||
0
|
||||
],
|
||||
"negative": [
|
||||
"11",
|
||||
0
|
||||
],
|
||||
"vae": [
|
||||
"9",
|
||||
0
|
||||
],
|
||||
"start_image": [
|
||||
"1",
|
||||
0
|
||||
],
|
||||
"width": 768,
|
||||
"height": 432,
|
||||
"length": 81,
|
||||
"batch_size": 1
|
||||
}
|
||||
},
|
||||
"13": {
|
||||
"class_type": "KSamplerAdvanced",
|
||||
"inputs": {
|
||||
"model": [
|
||||
"6",
|
||||
0
|
||||
],
|
||||
"latent_image": [
|
||||
"12",
|
||||
2
|
||||
],
|
||||
"add_noise": "enable",
|
||||
"noise_seed": 57865289174425,
|
||||
"start_at_step": 0,
|
||||
"end_at_step": 2,
|
||||
"return_with_leftover_noise": "enable",
|
||||
"positive": [
|
||||
"12",
|
||||
0
|
||||
],
|
||||
"negative": [
|
||||
"12",
|
||||
1
|
||||
],
|
||||
"steps": 4,
|
||||
"cfg": 1.0,
|
||||
"sampler_name": "euler",
|
||||
"scheduler": "simple"
|
||||
}
|
||||
},
|
||||
"14": {
|
||||
"class_type": "KSamplerAdvanced",
|
||||
"inputs": {
|
||||
"model": [
|
||||
"7",
|
||||
0
|
||||
],
|
||||
"latent_image": [
|
||||
"13",
|
||||
0
|
||||
],
|
||||
"add_noise": "disable",
|
||||
"noise_seed": 0,
|
||||
"start_at_step": 2,
|
||||
"end_at_step": 4,
|
||||
"return_with_leftover_noise": "disable",
|
||||
"positive": [
|
||||
"12",
|
||||
0
|
||||
],
|
||||
"negative": [
|
||||
"12",
|
||||
1
|
||||
],
|
||||
"steps": 4,
|
||||
"cfg": 1.0,
|
||||
"sampler_name": "euler",
|
||||
"scheduler": "simple"
|
||||
}
|
||||
},
|
||||
"15": {
|
||||
"class_type": "VAEDecode",
|
||||
"inputs": {
|
||||
"samples": [
|
||||
"14",
|
||||
0
|
||||
],
|
||||
"vae": [
|
||||
"9",
|
||||
0
|
||||
]
|
||||
}
|
||||
},
|
||||
"16": {
|
||||
"class_type": "VHS_VideoCombine",
|
||||
"inputs": {
|
||||
"images": [
|
||||
"15",
|
||||
0
|
||||
],
|
||||
"frame_rate": 16.0,
|
||||
"loop_count": 0,
|
||||
"filename_prefix": "hearthfire_tests/2026-09-29_EP01_CHAPEL_NIGHT_WAN22_TEST_V01",
|
||||
"format": "video/h264-mp4",
|
||||
"pingpong": false,
|
||||
"save_output": true,
|
||||
"pix_fmt": "yuv420p",
|
||||
"crf": 18,
|
||||
"save_metadata": true,
|
||||
"trim_to_audio": false
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,888 @@
|
||||
{
|
||||
"last_node_id": 16,
|
||||
"last_link_id": 21,
|
||||
"nodes": [
|
||||
{
|
||||
"id": 1,
|
||||
"type": "LoadImage",
|
||||
"pos": [
|
||||
40,
|
||||
1030
|
||||
],
|
||||
"size": [
|
||||
340,
|
||||
432
|
||||
],
|
||||
"flags": {},
|
||||
"order": 0,
|
||||
"mode": 0,
|
||||
"inputs": [],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "IMAGE",
|
||||
"type": "IMAGE",
|
||||
"links": [
|
||||
10
|
||||
]
|
||||
},
|
||||
{
|
||||
"name": "MASK",
|
||||
"type": "MASK",
|
||||
"links": []
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "LoadImage"
|
||||
},
|
||||
"widgets_values": [
|
||||
"hearthfire_tests/2026-09-29_EP01_CHAPEL_NIGHT_WAN22_TEST_V01.png",
|
||||
"image"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 2,
|
||||
"type": "UNETLoader",
|
||||
"pos": [
|
||||
40,
|
||||
40
|
||||
],
|
||||
"size": [
|
||||
340,
|
||||
260
|
||||
],
|
||||
"flags": {},
|
||||
"order": 1,
|
||||
"mode": 0,
|
||||
"inputs": [],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "MODEL",
|
||||
"type": "MODEL",
|
||||
"links": [
|
||||
1
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "UNETLoader"
|
||||
},
|
||||
"widgets_values": [
|
||||
"wan2.2_i2v_high_noise_14B_fp8_scaled.safetensors",
|
||||
"default"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 3,
|
||||
"type": "UNETLoader",
|
||||
"pos": [
|
||||
40,
|
||||
370
|
||||
],
|
||||
"size": [
|
||||
340,
|
||||
260
|
||||
],
|
||||
"flags": {},
|
||||
"order": 2,
|
||||
"mode": 0,
|
||||
"inputs": [],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "MODEL",
|
||||
"type": "MODEL",
|
||||
"links": [
|
||||
2
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "UNETLoader"
|
||||
},
|
||||
"widgets_values": [
|
||||
"wan2.2_i2v_low_noise_14B_fp8_scaled.safetensors",
|
||||
"default"
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 4,
|
||||
"type": "LoraLoaderModelOnly",
|
||||
"pos": [
|
||||
500,
|
||||
254
|
||||
],
|
||||
"size": [
|
||||
340,
|
||||
260
|
||||
],
|
||||
"flags": {},
|
||||
"order": 3,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "model",
|
||||
"type": "MODEL",
|
||||
"link": 1
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "MODEL",
|
||||
"type": "MODEL",
|
||||
"links": [
|
||||
3
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "LoraLoaderModelOnly"
|
||||
},
|
||||
"widgets_values": [
|
||||
"wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors",
|
||||
1.0
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 5,
|
||||
"type": "LoraLoaderModelOnly",
|
||||
"pos": [
|
||||
500,
|
||||
584
|
||||
],
|
||||
"size": [
|
||||
340,
|
||||
260
|
||||
],
|
||||
"flags": {},
|
||||
"order": 4,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "model",
|
||||
"type": "MODEL",
|
||||
"link": 2
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "MODEL",
|
||||
"type": "MODEL",
|
||||
"links": [
|
||||
4
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "LoraLoaderModelOnly"
|
||||
},
|
||||
"widgets_values": [
|
||||
"wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors",
|
||||
1.0
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 6,
|
||||
"type": "ModelSamplingSD3",
|
||||
"pos": [
|
||||
960,
|
||||
325
|
||||
],
|
||||
"size": [
|
||||
340,
|
||||
260
|
||||
],
|
||||
"flags": {},
|
||||
"order": 5,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
"name": "model",
|
||||
"type": "MODEL",
|
||||
"link": 3
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "MODEL",
|
||||
"type": "MODEL",
|
||||
"links": [
|
||||
11
|
||||
]
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "ModelSamplingSD3"
|
||||
},
|
||||
"widgets_values": [
|
||||
5.0
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": 7,
|
||||
"type": "ModelSamplingSD3",
|
||||
"pos": [
|
||||
960,
|
||||
655
|
||||
],
|
||||
"size": [
|
||||
340,
|
||||
260
|
||||
],
|
||||
"flags": {},
|
||||
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||||
"extra": {
|
||||
"ds": {
|
||||
"scale": 0.4,
|
||||
"offset": [
|
||||
0,
|
||||
0
|
||||
]
|
||||
}
|
||||
},
|
||||
"version": 0.4
|
||||
}
|
||||
Reference in New Issue
Block a user