mirror of
https://github.com/comfyanonymous/ComfyUI.git
synced 2026-05-25 16:37:23 +08:00
Compare commits
No commits in common. "8ef7bb175b3da1d44ab626a15ce9bbdbdf16ed7e" and "6fa0488449c1c508320d95144e6a4eaa2318314b" have entirely different histories.
8ef7bb175b
...
6fa0488449
45
.github/workflows/tag-dispatch-cloud.yml
vendored
45
.github/workflows/tag-dispatch-cloud.yml
vendored
@ -1,45 +0,0 @@
|
||||
name: Tag Dispatch to Cloud
|
||||
|
||||
on:
|
||||
push:
|
||||
tags:
|
||||
- 'v*'
|
||||
|
||||
jobs:
|
||||
dispatch-cloud:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- name: Send repository dispatch to cloud
|
||||
env:
|
||||
DISPATCH_TOKEN: ${{ secrets.CLOUD_REPO_DISPATCH_TOKEN }}
|
||||
RELEASE_TAG: ${{ github.ref_name }}
|
||||
run: |
|
||||
set -euo pipefail
|
||||
|
||||
if [ -z "${DISPATCH_TOKEN:-}" ]; then
|
||||
echo "::error::CLOUD_REPO_DISPATCH_TOKEN is required but not set."
|
||||
exit 1
|
||||
fi
|
||||
|
||||
RELEASE_URL="https://github.com/${{ github.repository }}/releases/tag/${RELEASE_TAG}"
|
||||
|
||||
PAYLOAD="$(jq -n \
|
||||
--arg release_tag "$RELEASE_TAG" \
|
||||
--arg release_url "$RELEASE_URL" \
|
||||
'{
|
||||
event_type: "comfyui_tag_pushed",
|
||||
client_payload: {
|
||||
release_tag: $release_tag,
|
||||
release_url: $release_url
|
||||
}
|
||||
}')"
|
||||
|
||||
curl -fsSL \
|
||||
-X POST \
|
||||
-H "Accept: application/vnd.github+json" \
|
||||
-H "Content-Type: application/json" \
|
||||
-H "Authorization: Bearer ${DISPATCH_TOKEN}" \
|
||||
https://api.github.com/repos/Comfy-Org/cloud/dispatches \
|
||||
-d "$PAYLOAD"
|
||||
|
||||
echo "✅ Dispatched ComfyUI tag ${RELEASE_TAG} to Comfy-Org/cloud"
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@ -160,7 +160,7 @@
|
||||
},
|
||||
"revision": 0,
|
||||
"config": {},
|
||||
"name": "Depth to Image (Z-Image-Turbo)",
|
||||
"name": "local-Depth to Image (Z-Image-Turbo)",
|
||||
"inputNode": {
|
||||
"id": -10,
|
||||
"bounding": [
|
||||
@ -2482,4 +2482,4 @@
|
||||
"VHS_KeepIntermediate": true
|
||||
},
|
||||
"version": 0.4
|
||||
}
|
||||
}
|
||||
|
||||
@ -261,7 +261,7 @@
|
||||
},
|
||||
"revision": 0,
|
||||
"config": {},
|
||||
"name": "Depth to Video (LTX 2.0)",
|
||||
"name": "local-Depth to Video (LTX 2.0)",
|
||||
"inputNode": {
|
||||
"id": -10,
|
||||
"bounding": [
|
||||
@ -5208,4 +5208,4 @@
|
||||
"workflowRendererVersion": "LG"
|
||||
},
|
||||
"version": 0.4
|
||||
}
|
||||
}
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@ -128,7 +128,7 @@
|
||||
},
|
||||
"revision": 0,
|
||||
"config": {},
|
||||
"name": "Image Edit (Flux.2 Klein 4B)",
|
||||
"name": "local-Image Edit (Flux.2 Klein 4B)",
|
||||
"inputNode": {
|
||||
"id": -10,
|
||||
"bounding": [
|
||||
@ -1837,4 +1837,4 @@
|
||||
}
|
||||
},
|
||||
"version": 0.4
|
||||
}
|
||||
}
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@ -124,7 +124,7 @@
|
||||
},
|
||||
"revision": 0,
|
||||
"config": {},
|
||||
"name": "Image Inpainting (Qwen-image)",
|
||||
"name": "local-Image Inpainting (Qwen-image)",
|
||||
"inputNode": {
|
||||
"id": -10,
|
||||
"bounding": [
|
||||
@ -1923,4 +1923,4 @@
|
||||
"workflowRendererVersion": "LG"
|
||||
},
|
||||
"version": 0.4
|
||||
}
|
||||
}
|
||||
|
||||
@ -204,7 +204,7 @@
|
||||
},
|
||||
"revision": 0,
|
||||
"config": {},
|
||||
"name": "Image Outpainting (Qwen-Image)",
|
||||
"name": "local-Image Outpainting (Qwen-Image)",
|
||||
"inputNode": {
|
||||
"id": -10,
|
||||
"bounding": [
|
||||
@ -2749,4 +2749,4 @@
|
||||
}
|
||||
},
|
||||
"version": 0.4
|
||||
}
|
||||
}
|
||||
|
||||
@ -1,14 +1,15 @@
|
||||
{
|
||||
"id": "1a761372-7c82-4016-b9bf-fa285967e1e9",
|
||||
"revision": 0,
|
||||
"last_node_id": 176,
|
||||
"last_node_id": 83,
|
||||
"last_link_id": 0,
|
||||
"nodes": [
|
||||
{
|
||||
"id": 176,
|
||||
"type": "2d2e3c8e-53b3-4618-be52-6d1d99382f0e",
|
||||
"id": 83,
|
||||
"type": "f754a936-daaf-4b6e-9658-41fdc54d301d",
|
||||
"pos": [
|
||||
-1150,
|
||||
200
|
||||
61.999827823554256,
|
||||
153.3332507624185
|
||||
],
|
||||
"size": [
|
||||
400,
|
||||
@ -55,38 +56,6 @@
|
||||
"name": "layers"
|
||||
},
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"name": "seed",
|
||||
"type": "INT",
|
||||
"widget": {
|
||||
"name": "seed"
|
||||
},
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"name": "unet_name",
|
||||
"type": "COMBO",
|
||||
"widget": {
|
||||
"name": "unet_name"
|
||||
},
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"name": "clip_name",
|
||||
"type": "COMBO",
|
||||
"widget": {
|
||||
"name": "clip_name"
|
||||
},
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"name": "vae_name",
|
||||
"type": "COMBO",
|
||||
"widget": {
|
||||
"name": "vae_name"
|
||||
},
|
||||
"link": null
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
@ -97,41 +66,28 @@
|
||||
"links": []
|
||||
}
|
||||
],
|
||||
"title": "Image to Layers (Qwen-Image-Layered)",
|
||||
"properties": {
|
||||
"proxyWidgets": [
|
||||
[
|
||||
"6",
|
||||
"-1",
|
||||
"text"
|
||||
],
|
||||
[
|
||||
"3",
|
||||
"-1",
|
||||
"steps"
|
||||
],
|
||||
[
|
||||
"3",
|
||||
"-1",
|
||||
"cfg"
|
||||
],
|
||||
[
|
||||
"83",
|
||||
"-1",
|
||||
"layers"
|
||||
],
|
||||
[
|
||||
"3",
|
||||
"seed"
|
||||
],
|
||||
[
|
||||
"37",
|
||||
"unet_name"
|
||||
],
|
||||
[
|
||||
"38",
|
||||
"clip_name"
|
||||
],
|
||||
[
|
||||
"39",
|
||||
"vae_name"
|
||||
],
|
||||
[
|
||||
"3",
|
||||
"control_after_generate"
|
||||
@ -139,11 +95,6 @@
|
||||
],
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
@ -152,20 +103,25 @@
|
||||
"secondTabOffset": 80,
|
||||
"secondTabWidth": 65
|
||||
},
|
||||
"widgets_values": []
|
||||
"widgets_values": [
|
||||
"",
|
||||
20,
|
||||
2.5,
|
||||
2
|
||||
]
|
||||
}
|
||||
],
|
||||
"links": [],
|
||||
"version": 0.4,
|
||||
"groups": [],
|
||||
"definitions": {
|
||||
"subgraphs": [
|
||||
{
|
||||
"id": "2d2e3c8e-53b3-4618-be52-6d1d99382f0e",
|
||||
"id": "f754a936-daaf-4b6e-9658-41fdc54d301d",
|
||||
"version": 1,
|
||||
"state": {
|
||||
"lastGroupId": 8,
|
||||
"lastNodeId": 176,
|
||||
"lastLinkId": 380,
|
||||
"lastGroupId": 3,
|
||||
"lastNodeId": 83,
|
||||
"lastLinkId": 159,
|
||||
"lastRerouteId": 0
|
||||
},
|
||||
"revision": 0,
|
||||
@ -174,10 +130,10 @@
|
||||
"inputNode": {
|
||||
"id": -10,
|
||||
"bounding": [
|
||||
-720,
|
||||
720,
|
||||
-510,
|
||||
523,
|
||||
120,
|
||||
220
|
||||
140
|
||||
]
|
||||
},
|
||||
"outputNode": {
|
||||
@ -200,8 +156,8 @@
|
||||
],
|
||||
"localized_name": "image",
|
||||
"pos": [
|
||||
-620,
|
||||
740
|
||||
-410,
|
||||
543
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -212,8 +168,8 @@
|
||||
150
|
||||
],
|
||||
"pos": [
|
||||
-620,
|
||||
760
|
||||
-410,
|
||||
563
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -224,8 +180,8 @@
|
||||
153
|
||||
],
|
||||
"pos": [
|
||||
-620,
|
||||
780
|
||||
-410,
|
||||
583
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -236,8 +192,8 @@
|
||||
154
|
||||
],
|
||||
"pos": [
|
||||
-620,
|
||||
800
|
||||
-410,
|
||||
603
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -248,56 +204,8 @@
|
||||
159
|
||||
],
|
||||
"pos": [
|
||||
-620,
|
||||
820
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": "9f76338b-f4ca-4bb3-b61a-57b3f233061e",
|
||||
"name": "seed",
|
||||
"type": "INT",
|
||||
"linkIds": [
|
||||
377
|
||||
],
|
||||
"pos": [
|
||||
-620,
|
||||
840
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": "8d0422d5-5eee-4f7e-9817-dc613cc62eca",
|
||||
"name": "unet_name",
|
||||
"type": "COMBO",
|
||||
"linkIds": [
|
||||
378
|
||||
],
|
||||
"pos": [
|
||||
-620,
|
||||
860
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": "552eece2-a735-4d00-ae78-ded454622bc1",
|
||||
"name": "clip_name",
|
||||
"type": "COMBO",
|
||||
"linkIds": [
|
||||
379
|
||||
],
|
||||
"pos": [
|
||||
-620,
|
||||
880
|
||||
]
|
||||
},
|
||||
{
|
||||
"id": "1e6d141c-d0f9-4a2b-895c-b6780e57cfa0",
|
||||
"name": "vae_name",
|
||||
"type": "COMBO",
|
||||
"linkIds": [
|
||||
380
|
||||
],
|
||||
"pos": [
|
||||
-620,
|
||||
900
|
||||
-410,
|
||||
623
|
||||
]
|
||||
}
|
||||
],
|
||||
@ -323,14 +231,14 @@
|
||||
"type": "CLIPLoader",
|
||||
"pos": [
|
||||
-320,
|
||||
360
|
||||
310
|
||||
],
|
||||
"size": [
|
||||
350,
|
||||
150
|
||||
346.7470703125,
|
||||
106
|
||||
],
|
||||
"flags": {},
|
||||
"order": 5,
|
||||
"order": 0,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
@ -340,7 +248,7 @@
|
||||
"widget": {
|
||||
"name": "clip_name"
|
||||
},
|
||||
"link": 379
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"localized_name": "type",
|
||||
@ -375,14 +283,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "CLIPLoader",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "CLIPLoader",
|
||||
"models": [
|
||||
{
|
||||
"name": "qwen_2.5_vl_7b_fp8_scaled.safetensors",
|
||||
@ -409,14 +312,14 @@
|
||||
"type": "VAELoader",
|
||||
"pos": [
|
||||
-320,
|
||||
580
|
||||
460
|
||||
],
|
||||
"size": [
|
||||
350,
|
||||
110
|
||||
346.7470703125,
|
||||
58
|
||||
],
|
||||
"flags": {},
|
||||
"order": 6,
|
||||
"order": 1,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
@ -426,7 +329,7 @@
|
||||
"widget": {
|
||||
"name": "vae_name"
|
||||
},
|
||||
"link": 380
|
||||
"link": null
|
||||
}
|
||||
],
|
||||
"outputs": [
|
||||
@ -442,14 +345,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "VAELoader",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "VAELoader",
|
||||
"models": [
|
||||
{
|
||||
"name": "qwen_image_layered_vae.safetensors",
|
||||
@ -477,11 +375,11 @@
|
||||
420
|
||||
],
|
||||
"size": [
|
||||
430,
|
||||
190
|
||||
425.27801513671875,
|
||||
180.6060791015625
|
||||
],
|
||||
"flags": {},
|
||||
"order": 2,
|
||||
"order": 3,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
@ -513,14 +411,9 @@
|
||||
],
|
||||
"title": "CLIP Text Encode (Negative Prompt)",
|
||||
"properties": {
|
||||
"Node name for S&R": "CLIPTextEncode",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "CLIPTextEncode",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
@ -539,12 +432,12 @@
|
||||
"id": 70,
|
||||
"type": "ReferenceLatent",
|
||||
"pos": [
|
||||
140,
|
||||
700
|
||||
330,
|
||||
670
|
||||
],
|
||||
"size": [
|
||||
210,
|
||||
50
|
||||
204.1666717529297,
|
||||
46
|
||||
],
|
||||
"flags": {
|
||||
"collapsed": true
|
||||
@ -577,14 +470,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "ReferenceLatent",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "ReferenceLatent",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
@ -592,18 +480,19 @@
|
||||
"secondTabText": "Send Back",
|
||||
"secondTabOffset": 80,
|
||||
"secondTabWidth": 65
|
||||
}
|
||||
},
|
||||
"widgets_values": []
|
||||
},
|
||||
{
|
||||
"id": 69,
|
||||
"type": "ReferenceLatent",
|
||||
"pos": [
|
||||
160,
|
||||
820
|
||||
330,
|
||||
710
|
||||
],
|
||||
"size": [
|
||||
210,
|
||||
50
|
||||
204.1666717529297,
|
||||
46
|
||||
],
|
||||
"flags": {
|
||||
"collapsed": true
|
||||
@ -636,14 +525,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "ReferenceLatent",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "ReferenceLatent",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
@ -651,7 +535,8 @@
|
||||
"secondTabText": "Send Back",
|
||||
"secondTabOffset": 80,
|
||||
"secondTabWidth": 65
|
||||
}
|
||||
},
|
||||
"widgets_values": []
|
||||
},
|
||||
{
|
||||
"id": 66,
|
||||
@ -662,10 +547,10 @@
|
||||
],
|
||||
"size": [
|
||||
270,
|
||||
110
|
||||
58
|
||||
],
|
||||
"flags": {},
|
||||
"order": 7,
|
||||
"order": 4,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
@ -695,14 +580,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "ModelSamplingAuraFlow",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "ModelSamplingAuraFlow",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
@ -720,11 +600,11 @@
|
||||
"type": "LatentCutToBatch",
|
||||
"pos": [
|
||||
830,
|
||||
140
|
||||
160
|
||||
],
|
||||
"size": [
|
||||
270,
|
||||
140
|
||||
82
|
||||
],
|
||||
"flags": {},
|
||||
"order": 11,
|
||||
@ -766,14 +646,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "LatentCutToBatch",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "LatentCutToBatch",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
@ -791,12 +666,12 @@
|
||||
"id": 71,
|
||||
"type": "VAEEncode",
|
||||
"pos": [
|
||||
-280,
|
||||
780
|
||||
100,
|
||||
690
|
||||
],
|
||||
"size": [
|
||||
230,
|
||||
100
|
||||
140,
|
||||
46
|
||||
],
|
||||
"flags": {
|
||||
"collapsed": false
|
||||
@ -829,14 +704,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "VAEEncode",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "VAEEncode",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
@ -844,23 +714,24 @@
|
||||
"secondTabText": "Send Back",
|
||||
"secondTabOffset": 80,
|
||||
"secondTabWidth": 65
|
||||
}
|
||||
},
|
||||
"widgets_values": []
|
||||
},
|
||||
{
|
||||
"id": 8,
|
||||
"type": "VAEDecode",
|
||||
"pos": [
|
||||
850,
|
||||
370
|
||||
310
|
||||
],
|
||||
"size": [
|
||||
210,
|
||||
50
|
||||
46
|
||||
],
|
||||
"flags": {
|
||||
"collapsed": true
|
||||
},
|
||||
"order": 3,
|
||||
"order": 7,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
@ -888,14 +759,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "VAEDecode",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "VAEDecode",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
@ -903,7 +769,8 @@
|
||||
"secondTabText": "Send Back",
|
||||
"secondTabOffset": 80,
|
||||
"secondTabWidth": 65
|
||||
}
|
||||
},
|
||||
"widgets_values": []
|
||||
},
|
||||
{
|
||||
"id": 6,
|
||||
@ -913,11 +780,11 @@
|
||||
180
|
||||
],
|
||||
"size": [
|
||||
430,
|
||||
170
|
||||
422.84503173828125,
|
||||
164.31304931640625
|
||||
],
|
||||
"flags": {},
|
||||
"order": 1,
|
||||
"order": 6,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
@ -949,14 +816,9 @@
|
||||
],
|
||||
"title": "CLIP Text Encode (Positive Prompt)",
|
||||
"properties": {
|
||||
"Node name for S&R": "CLIPTextEncode",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "CLIPTextEncode",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
@ -976,14 +838,14 @@
|
||||
"type": "KSampler",
|
||||
"pos": [
|
||||
530,
|
||||
340
|
||||
280
|
||||
],
|
||||
"size": [
|
||||
270,
|
||||
400
|
||||
],
|
||||
"flags": {},
|
||||
"order": 0,
|
||||
"order": 5,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
@ -1017,7 +879,7 @@
|
||||
"widget": {
|
||||
"name": "seed"
|
||||
},
|
||||
"link": 377
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"localized_name": "steps",
|
||||
@ -1077,14 +939,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "KSampler",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "KSampler",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
@ -1107,12 +964,12 @@
|
||||
"id": 78,
|
||||
"type": "GetImageSize",
|
||||
"pos": [
|
||||
-280,
|
||||
930
|
||||
80,
|
||||
790
|
||||
],
|
||||
"size": [
|
||||
230,
|
||||
140
|
||||
210,
|
||||
136
|
||||
],
|
||||
"flags": {},
|
||||
"order": 12,
|
||||
@ -1150,14 +1007,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "GetImageSize",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "GetImageSize",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
@ -1165,23 +1017,23 @@
|
||||
"secondTabText": "Send Back",
|
||||
"secondTabOffset": 80,
|
||||
"secondTabWidth": 65
|
||||
}
|
||||
},
|
||||
"widgets_values": []
|
||||
},
|
||||
{
|
||||
"id": 83,
|
||||
"type": "EmptyQwenImageLayeredLatentImage",
|
||||
"pos": [
|
||||
-280,
|
||||
1120
|
||||
320,
|
||||
790
|
||||
],
|
||||
"size": [
|
||||
340,
|
||||
200
|
||||
330.9341796875,
|
||||
130
|
||||
],
|
||||
"flags": {},
|
||||
"order": 13,
|
||||
"mode": 0,
|
||||
"showAdvanced": true,
|
||||
"inputs": [
|
||||
{
|
||||
"localized_name": "width",
|
||||
@ -1231,14 +1083,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "EmptyQwenImageLayeredLatentImage",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "EmptyQwenImageLayeredLatentImage",
|
||||
"enableTabs": false,
|
||||
"tabWidth": 65,
|
||||
"tabXOffset": 10,
|
||||
@ -1262,11 +1109,11 @@
|
||||
180
|
||||
],
|
||||
"size": [
|
||||
350,
|
||||
110
|
||||
346.7470703125,
|
||||
82
|
||||
],
|
||||
"flags": {},
|
||||
"order": 4,
|
||||
"order": 2,
|
||||
"mode": 0,
|
||||
"inputs": [
|
||||
{
|
||||
@ -1276,7 +1123,7 @@
|
||||
"widget": {
|
||||
"name": "unet_name"
|
||||
},
|
||||
"link": 378
|
||||
"link": null
|
||||
},
|
||||
{
|
||||
"localized_name": "weight_dtype",
|
||||
@ -1300,14 +1147,9 @@
|
||||
}
|
||||
],
|
||||
"properties": {
|
||||
"Node name for S&R": "UNETLoader",
|
||||
"cnr_id": "comfy-core",
|
||||
"ver": "0.5.1",
|
||||
"ue_properties": {
|
||||
"widget_ue_connectable": {},
|
||||
"input_ue_unconnectable": {},
|
||||
"version": "7.7"
|
||||
},
|
||||
"Node name for S&R": "UNETLoader",
|
||||
"models": [
|
||||
{
|
||||
"name": "qwen_image_layered_bf16.safetensors",
|
||||
@ -1349,8 +1191,8 @@
|
||||
"bounding": [
|
||||
-330,
|
||||
110,
|
||||
370,
|
||||
610
|
||||
366.7470703125,
|
||||
421.6
|
||||
],
|
||||
"color": "#3f789e",
|
||||
"font_size": 24,
|
||||
@ -1549,38 +1391,6 @@
|
||||
"target_id": 83,
|
||||
"target_slot": 2,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 377,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 5,
|
||||
"target_id": 3,
|
||||
"target_slot": 4,
|
||||
"type": "INT"
|
||||
},
|
||||
{
|
||||
"id": 378,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 6,
|
||||
"target_id": 37,
|
||||
"target_slot": 0,
|
||||
"type": "COMBO"
|
||||
},
|
||||
{
|
||||
"id": 379,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 7,
|
||||
"target_id": 38,
|
||||
"target_slot": 0,
|
||||
"type": "COMBO"
|
||||
},
|
||||
{
|
||||
"id": 380,
|
||||
"origin_id": -10,
|
||||
"origin_slot": 8,
|
||||
"target_id": 39,
|
||||
"target_slot": 0,
|
||||
"type": "COMBO"
|
||||
}
|
||||
],
|
||||
"extra": {
|
||||
@ -1590,6 +1400,7 @@
|
||||
}
|
||||
]
|
||||
},
|
||||
"config": {},
|
||||
"extra": {
|
||||
"ds": {
|
||||
"scale": 1.14,
|
||||
@ -1598,6 +1409,7 @@
|
||||
6.855893974423647
|
||||
]
|
||||
},
|
||||
"ue_links": []
|
||||
}
|
||||
}
|
||||
"workflowRendererVersion": "LG"
|
||||
},
|
||||
"version": 0.4
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@ -663,7 +663,6 @@ def minimum_inference_memory():
|
||||
|
||||
def free_memory(memory_required, device, keep_loaded=[], for_dynamic=False, pins_required=0, ram_required=0):
|
||||
cleanup_models_gc()
|
||||
comfy.memory_management.extra_ram_release(max(pins_required, ram_required))
|
||||
unloaded_model = []
|
||||
can_unload = []
|
||||
unloaded_models = []
|
||||
|
||||
@ -31,7 +31,6 @@ import comfy.float
|
||||
import comfy.hooks
|
||||
import comfy.lora
|
||||
import comfy.model_management
|
||||
import comfy.ops
|
||||
import comfy.patcher_extension
|
||||
import comfy.utils
|
||||
from comfy.comfy_types import UnetWrapperFunction
|
||||
@ -857,9 +856,7 @@ class ModelPatcher:
|
||||
if m.comfy_patched_weights == True:
|
||||
continue
|
||||
|
||||
for param, param_value in params.items():
|
||||
if hasattr(m, "comfy_cast_weights") and getattr(param_value, "is_meta", False):
|
||||
comfy.ops.disable_weight_init._zero_init_parameter(m, param)
|
||||
for param in params:
|
||||
key = key_param_name_to_key(n, param)
|
||||
self.unpin_weight(key)
|
||||
self.patch_weight_to_device(key, device_to=device_to)
|
||||
|
||||
16
comfy/ops.py
16
comfy/ops.py
@ -79,21 +79,14 @@ def cast_to_input(weight, input, non_blocking=False, copy=True):
|
||||
return comfy.model_management.cast_to(weight, input.dtype, input.device, non_blocking=non_blocking, copy=copy)
|
||||
|
||||
|
||||
def materialize_meta_param(s, param_keys):
|
||||
for param_key in param_keys:
|
||||
param = getattr(s, param_key, None)
|
||||
if param is not None and getattr(param, "is_meta", False):
|
||||
setattr(s, param_key, torch.nn.Parameter(torch.zeros(param.shape, dtype=param.dtype), requires_grad=param.requires_grad))
|
||||
|
||||
|
||||
def cast_bias_weight_with_vbar(s, dtype, device, bias_dtype, non_blocking, compute_dtype, want_requant):
|
||||
|
||||
#vbar doesn't support CPU weights, but some custom nodes have weird paths
|
||||
#that might switch the layer to the CPU and expect it to work. We have to take
|
||||
#a clone conservatively as we are mmapped and some SFT files are packed misaligned
|
||||
#If you are a custom node author reading this, please move your layer to the GPU
|
||||
#or declare your ModelPatcher as CPU in the first place.
|
||||
if comfy.model_management.is_device_cpu(device):
|
||||
materialize_meta_param(s, ["weight", "bias"])
|
||||
weight = s.weight.to(dtype=dtype, copy=True)
|
||||
if isinstance(weight, QuantizedTensor):
|
||||
weight = weight.dequantize()
|
||||
@ -115,7 +108,6 @@ def cast_bias_weight_with_vbar(s, dtype, device, bias_dtype, non_blocking, compu
|
||||
xfer_dest = comfy_aimdo.torch.aimdo_to_tensor(s._v, device)
|
||||
|
||||
if not resident:
|
||||
materialize_meta_param(s, ["weight", "bias"])
|
||||
cast_geometry = comfy.memory_management.tensors_to_geometries([ s.weight, s.bias ])
|
||||
cast_dest = None
|
||||
|
||||
@ -314,12 +306,6 @@ class CastWeightBiasOp:
|
||||
bias_function = []
|
||||
|
||||
class disable_weight_init:
|
||||
@staticmethod
|
||||
def _zero_init_parameter(module, name):
|
||||
param = getattr(module, name)
|
||||
device = None if getattr(param, "is_meta", False) else param.device
|
||||
setattr(module, name, torch.nn.Parameter(torch.zeros(param.shape, device=device, dtype=param.dtype), requires_grad=False))
|
||||
|
||||
@staticmethod
|
||||
def _lazy_load_from_state_dict(module, state_dict, prefix, local_metadata,
|
||||
missing_keys, unexpected_keys, weight_shape,
|
||||
|
||||
@ -2,6 +2,7 @@ import comfy.model_management
|
||||
import comfy.memory_management
|
||||
import comfy_aimdo.host_buffer
|
||||
import comfy_aimdo.torch
|
||||
import psutil
|
||||
|
||||
from comfy.cli_args import args
|
||||
|
||||
@ -11,6 +12,11 @@ def get_pin(module):
|
||||
def pin_memory(module):
|
||||
if module.pin_failed or args.disable_pinned_memory or get_pin(module) is not None:
|
||||
return
|
||||
#FIXME: This is a RAM cache trigger event
|
||||
ram_headroom = comfy.memory_management.RAM_CACHE_HEADROOM
|
||||
#we split the difference and assume half the RAM cache headroom is for us
|
||||
if ram_headroom > 0 and psutil.virtual_memory().available < (ram_headroom * 0.5):
|
||||
comfy.memory_management.extra_ram_release(ram_headroom)
|
||||
|
||||
size = comfy.memory_management.vram_aligned_size([ module.weight, module.bias ])
|
||||
|
||||
|
||||
@ -12,7 +12,6 @@ import numpy as np
|
||||
import math
|
||||
import torch
|
||||
from .._util import VideoContainer, VideoCodec, VideoComponents
|
||||
import logging
|
||||
|
||||
|
||||
def container_to_output_format(container_format: str | None) -> str | None:
|
||||
@ -239,110 +238,64 @@ class VideoFromFile(VideoInput):
|
||||
start_time = max(self._get_raw_duration() + self.__start_time, 0)
|
||||
else:
|
||||
start_time = self.__start_time
|
||||
|
||||
# Get video frames
|
||||
frames = []
|
||||
audio_frames = []
|
||||
alphas = None
|
||||
start_pts = int(start_time / video_stream.time_base)
|
||||
end_pts = int((start_time + self.__duration) / video_stream.time_base)
|
||||
|
||||
if start_pts != 0:
|
||||
container.seek(start_pts, stream=video_stream)
|
||||
|
||||
image_format = 'gbrpf32le'
|
||||
audio = None
|
||||
|
||||
streams = [video_stream]
|
||||
has_first_audio_frame = False
|
||||
checked_alpha = False
|
||||
|
||||
# Default to False so we decode until EOF if duration is 0
|
||||
video_done = False
|
||||
audio_done = True
|
||||
|
||||
if len(container.streams.audio):
|
||||
audio_stream = container.streams.audio[-1]
|
||||
streams += [audio_stream]
|
||||
resampler = av.audio.resampler.AudioResampler(format='fltp')
|
||||
audio_done = False
|
||||
|
||||
for packet in container.demux(*streams):
|
||||
if video_done and audio_done:
|
||||
container.seek(start_pts, stream=video_stream)
|
||||
for frame in container.decode(video_stream):
|
||||
if frame.pts < start_pts:
|
||||
continue
|
||||
if self.__duration and frame.pts >= end_pts:
|
||||
break
|
||||
img = frame.to_ndarray(format='rgb24') # shape: (H, W, 3)
|
||||
img = torch.from_numpy(img) / 255.0 # shape: (H, W, 3)
|
||||
frames.append(img)
|
||||
|
||||
if packet.stream.type == "video":
|
||||
if video_done:
|
||||
continue
|
||||
try:
|
||||
for frame in packet.decode():
|
||||
if frame.pts < start_pts:
|
||||
continue
|
||||
if self.__duration and frame.pts >= end_pts:
|
||||
video_done = True
|
||||
break
|
||||
|
||||
if not checked_alpha:
|
||||
for comp in frame.format.components:
|
||||
if comp.is_alpha or frame.format.name == "pal8":
|
||||
alphas = []
|
||||
image_format = 'gbrapf32le'
|
||||
break
|
||||
checked_alpha = True
|
||||
|
||||
img = frame.to_ndarray(format=image_format) # shape: (H, W, 4)
|
||||
if frame.rotation != 0:
|
||||
k = int(round(frame.rotation // 90))
|
||||
img = np.rot90(img, k=k, axes=(0, 1)).copy()
|
||||
if alphas is None:
|
||||
frames.append(torch.from_numpy(img))
|
||||
else:
|
||||
frames.append(torch.from_numpy(img[..., :-1]))
|
||||
alphas.append(torch.from_numpy(img[..., -1:]))
|
||||
except av.error.InvalidDataError:
|
||||
logging.info("pyav decode error")
|
||||
|
||||
elif packet.stream.type == "audio":
|
||||
if audio_done:
|
||||
continue
|
||||
|
||||
aframes = itertools.chain.from_iterable(
|
||||
map(resampler.resample, packet.decode())
|
||||
)
|
||||
for frame in aframes:
|
||||
if self.__duration and frame.time > start_time + self.__duration:
|
||||
audio_done = True
|
||||
break
|
||||
|
||||
if not has_first_audio_frame:
|
||||
offset_seconds = start_time - frame.pts * audio_stream.time_base
|
||||
to_skip = max(0, int(offset_seconds * audio_stream.sample_rate))
|
||||
if to_skip < frame.samples:
|
||||
has_first_audio_frame = True
|
||||
audio_frames.append(frame.to_ndarray()[..., to_skip:])
|
||||
else:
|
||||
audio_frames.append(frame.to_ndarray())
|
||||
|
||||
images = torch.stack(frames) if len(frames) > 0 else torch.zeros(0, 0, 0, 3)
|
||||
if alphas is not None:
|
||||
alphas = torch.stack(alphas) if len(alphas) > 0 else torch.zeros(0, 0, 0, 1)
|
||||
images = torch.stack(frames) if len(frames) > 0 else torch.zeros(0, 3, 0, 0)
|
||||
|
||||
# Get frame rate
|
||||
frame_rate = Fraction(video_stream.average_rate) if video_stream.average_rate else Fraction(1)
|
||||
|
||||
if len(audio_frames) > 0:
|
||||
audio_data = np.concatenate(audio_frames, axis=1) # shape: (channels, total_samples)
|
||||
if self.__duration:
|
||||
audio_data = audio_data[..., :int(self.__duration * audio_stream.sample_rate)]
|
||||
# Get audio if available
|
||||
audio = None
|
||||
container.seek(start_pts, stream=video_stream)
|
||||
# Use last stream for consistency
|
||||
if len(container.streams.audio):
|
||||
audio_stream = container.streams.audio[-1]
|
||||
audio_frames = []
|
||||
resample = av.audio.resampler.AudioResampler(format='fltp').resample
|
||||
frames = itertools.chain.from_iterable(
|
||||
map(resample, container.decode(audio_stream))
|
||||
)
|
||||
|
||||
audio_tensor = torch.from_numpy(audio_data).unsqueeze(0) # shape: (1, channels, total_samples)
|
||||
audio = AudioInput({
|
||||
"waveform": audio_tensor,
|
||||
"sample_rate": int(audio_stream.sample_rate) if audio_stream.sample_rate else 1,
|
||||
})
|
||||
has_first_frame = False
|
||||
for frame in frames:
|
||||
offset_seconds = start_time - frame.pts * audio_stream.time_base
|
||||
to_skip = max(0, int(offset_seconds * audio_stream.sample_rate))
|
||||
if to_skip < frame.samples:
|
||||
has_first_frame = True
|
||||
break
|
||||
if has_first_frame:
|
||||
audio_frames.append(frame.to_ndarray()[..., to_skip:])
|
||||
|
||||
for frame in frames:
|
||||
if self.__duration and frame.time > start_time + self.__duration:
|
||||
break
|
||||
audio_frames.append(frame.to_ndarray()) # shape: (channels, samples)
|
||||
if len(audio_frames) > 0:
|
||||
audio_data = np.concatenate(audio_frames, axis=1) # shape: (channels, total_samples)
|
||||
if self.__duration:
|
||||
audio_data = audio_data[..., :int(self.__duration * audio_stream.sample_rate)]
|
||||
|
||||
audio_tensor = torch.from_numpy(audio_data).unsqueeze(0) # shape: (1, channels, total_samples)
|
||||
audio = AudioInput({
|
||||
"waveform": audio_tensor,
|
||||
"sample_rate": int(audio_stream.sample_rate) if audio_stream.sample_rate else 1,
|
||||
})
|
||||
|
||||
metadata = container.metadata
|
||||
return VideoComponents(images=images, alpha=alphas, audio=audio, frame_rate=frame_rate, metadata=metadata)
|
||||
return VideoComponents(images=images, audio=audio, frame_rate=frame_rate, metadata=metadata)
|
||||
|
||||
def get_components(self) -> VideoComponents:
|
||||
if isinstance(self.__file, io.BytesIO):
|
||||
|
||||
@ -3,7 +3,7 @@ from dataclasses import dataclass
|
||||
from enum import Enum
|
||||
from fractions import Fraction
|
||||
from typing import Optional
|
||||
from .._input import ImageInput, AudioInput, MaskInput
|
||||
from .._input import ImageInput, AudioInput
|
||||
|
||||
class VideoCodec(str, Enum):
|
||||
AUTO = "auto"
|
||||
@ -48,4 +48,5 @@ class VideoComponents:
|
||||
frame_rate: Fraction
|
||||
audio: Optional[AudioInput] = None
|
||||
metadata: Optional[dict] = None
|
||||
alpha: Optional[MaskInput] = None
|
||||
|
||||
|
||||
|
||||
@ -118,7 +118,7 @@ class Wan27ReferenceVideoInputField(BaseModel):
|
||||
class Wan27ReferenceVideoParametersField(BaseModel):
|
||||
resolution: str = Field(...)
|
||||
ratio: str | None = Field(None)
|
||||
duration: int = Field(5, ge=2, le=15)
|
||||
duration: int = Field(5, ge=2, le=10)
|
||||
watermark: bool = Field(False)
|
||||
seed: int = Field(..., ge=0, le=2147483647)
|
||||
|
||||
@ -157,7 +157,7 @@ class Wan27VideoEditInputField(BaseModel):
|
||||
class Wan27VideoEditParametersField(BaseModel):
|
||||
resolution: str = Field(...)
|
||||
ratio: str | None = Field(None)
|
||||
duration: int | None = Field(0)
|
||||
duration: int = Field(0)
|
||||
audio_setting: str = Field("auto")
|
||||
watermark: bool = Field(False)
|
||||
seed: int = Field(..., ge=0, le=2147483647)
|
||||
|
||||
@ -1646,557 +1646,6 @@ class Wan2ReferenceVideoApi(IO.ComfyNode):
|
||||
return IO.NodeOutput(await download_url_to_video_output(response.output.video_url))
|
||||
|
||||
|
||||
class HappyHorseTextToVideoApi(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="HappyHorseTextToVideoApi",
|
||||
display_name="HappyHorse Text to Video",
|
||||
category="api node/video/Wan",
|
||||
description="Generates a video based on a text prompt using the HappyHorse model.",
|
||||
inputs=[
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[
|
||||
IO.DynamicCombo.Option(
|
||||
"happyhorse-1.0-t2v",
|
||||
[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="Prompt describing the elements and visual features. "
|
||||
"Supports English and Chinese.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"resolution",
|
||||
options=["720P", "1080P"],
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"ratio",
|
||||
options=["16:9", "9:16", "1:1", "4:3", "3:4"],
|
||||
),
|
||||
IO.Int.Input(
|
||||
"duration",
|
||||
default=5,
|
||||
min=3,
|
||||
max=15,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=2147483647,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="Seed to use for generation.",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"watermark",
|
||||
default=False,
|
||||
tooltip="Whether to add an AI-generated watermark to the result.",
|
||||
advanced=True,
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Video.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model", "model.resolution", "model.duration"]),
|
||||
expr="""
|
||||
(
|
||||
$res := $lookup(widgets, "model.resolution");
|
||||
$dur := $lookup(widgets, "model.duration");
|
||||
$ppsTable := { "720p": 0.14, "1080p": 0.24 };
|
||||
$pps := $lookup($ppsTable, $res);
|
||||
{ "type": "usd", "usd": $pps * $dur }
|
||||
)
|
||||
""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
model: dict,
|
||||
seed: int,
|
||||
watermark: bool,
|
||||
):
|
||||
validate_string(model["prompt"], strip_whitespace=False, min_length=1)
|
||||
initial_response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(
|
||||
path="/proxy/wan/api/v1/services/aigc/video-generation/video-synthesis",
|
||||
method="POST",
|
||||
),
|
||||
response_model=TaskCreationResponse,
|
||||
data=Wan27Text2VideoTaskCreationRequest(
|
||||
model=model["model"],
|
||||
input=Text2VideoInputField(
|
||||
prompt=model["prompt"],
|
||||
negative_prompt=None,
|
||||
),
|
||||
parameters=Wan27Text2VideoParametersField(
|
||||
resolution=model["resolution"],
|
||||
ratio=model["ratio"],
|
||||
duration=model["duration"],
|
||||
seed=seed,
|
||||
watermark=watermark,
|
||||
),
|
||||
),
|
||||
)
|
||||
if not initial_response.output:
|
||||
raise Exception(f"An unknown error occurred: {initial_response.code} - {initial_response.message}")
|
||||
response = await poll_op(
|
||||
cls,
|
||||
ApiEndpoint(path=f"/proxy/wan/api/v1/tasks/{initial_response.output.task_id}"),
|
||||
response_model=VideoTaskStatusResponse,
|
||||
status_extractor=lambda x: x.output.task_status,
|
||||
poll_interval=7,
|
||||
)
|
||||
return IO.NodeOutput(await download_url_to_video_output(response.output.video_url))
|
||||
|
||||
|
||||
class HappyHorseImageToVideoApi(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="HappyHorseImageToVideoApi",
|
||||
display_name="HappyHorse Image to Video",
|
||||
category="api node/video/Wan",
|
||||
description="Generate a video from a first-frame image using the HappyHorse model.",
|
||||
inputs=[
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[
|
||||
IO.DynamicCombo.Option(
|
||||
"happyhorse-1.0-i2v",
|
||||
[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="Prompt describing the elements and visual features. "
|
||||
"Supports English and Chinese.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"resolution",
|
||||
options=["720P", "1080P"],
|
||||
),
|
||||
IO.Int.Input(
|
||||
"duration",
|
||||
default=5,
|
||||
min=3,
|
||||
max=15,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
),
|
||||
IO.Image.Input(
|
||||
"first_frame",
|
||||
tooltip="First frame image. The output aspect ratio is derived from this image.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=2147483647,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="Seed to use for generation.",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"watermark",
|
||||
default=False,
|
||||
tooltip="Whether to add an AI-generated watermark to the result.",
|
||||
advanced=True,
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Video.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model", "model.resolution", "model.duration"]),
|
||||
expr="""
|
||||
(
|
||||
$res := $lookup(widgets, "model.resolution");
|
||||
$dur := $lookup(widgets, "model.duration");
|
||||
$ppsTable := { "720p": 0.14, "1080p": 0.24 };
|
||||
$pps := $lookup($ppsTable, $res);
|
||||
{ "type": "usd", "usd": $pps * $dur }
|
||||
)
|
||||
""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
model: dict,
|
||||
first_frame: Input.Image,
|
||||
seed: int,
|
||||
watermark: bool,
|
||||
):
|
||||
media = [
|
||||
Wan27MediaItem(
|
||||
type="first_frame",
|
||||
url=await upload_image_to_comfyapi(cls, image=first_frame),
|
||||
)
|
||||
]
|
||||
initial_response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(
|
||||
path="/proxy/wan/api/v1/services/aigc/video-generation/video-synthesis",
|
||||
method="POST",
|
||||
),
|
||||
response_model=TaskCreationResponse,
|
||||
data=Wan27ImageToVideoTaskCreationRequest(
|
||||
model=model["model"],
|
||||
input=Wan27ImageToVideoInputField(
|
||||
prompt=model["prompt"] or None,
|
||||
negative_prompt=None,
|
||||
media=media,
|
||||
),
|
||||
parameters=Wan27ImageToVideoParametersField(
|
||||
resolution=model["resolution"],
|
||||
duration=model["duration"],
|
||||
seed=seed,
|
||||
watermark=watermark,
|
||||
),
|
||||
),
|
||||
)
|
||||
if not initial_response.output:
|
||||
raise Exception(f"An unknown error occurred: {initial_response.code} - {initial_response.message}")
|
||||
response = await poll_op(
|
||||
cls,
|
||||
ApiEndpoint(path=f"/proxy/wan/api/v1/tasks/{initial_response.output.task_id}"),
|
||||
response_model=VideoTaskStatusResponse,
|
||||
status_extractor=lambda x: x.output.task_status,
|
||||
poll_interval=7,
|
||||
)
|
||||
return IO.NodeOutput(await download_url_to_video_output(response.output.video_url))
|
||||
|
||||
|
||||
class HappyHorseVideoEditApi(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="HappyHorseVideoEditApi",
|
||||
display_name="HappyHorse Video Edit",
|
||||
category="api node/video/Wan",
|
||||
description="Edit a video using text instructions or reference images with the HappyHorse model. "
|
||||
"Output duration is 3-15s and matches the input video; inputs longer than 15s are truncated.",
|
||||
inputs=[
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[
|
||||
IO.DynamicCombo.Option(
|
||||
"happyhorse-1.0-video-edit",
|
||||
[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="Editing instructions or style transfer requirements.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"resolution",
|
||||
options=["720P", "1080P"],
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"ratio",
|
||||
options=["16:9", "9:16", "1:1", "4:3", "3:4"],
|
||||
tooltip="Aspect ratio. If not changed, approximates the input video ratio.",
|
||||
),
|
||||
IO.Autogrow.Input(
|
||||
"reference_images",
|
||||
template=IO.Autogrow.TemplateNames(
|
||||
IO.Image.Input("reference_image"),
|
||||
names=[
|
||||
"image1",
|
||||
"image2",
|
||||
"image3",
|
||||
"image4",
|
||||
"image5",
|
||||
],
|
||||
min=0,
|
||||
),
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
),
|
||||
IO.Video.Input(
|
||||
"video",
|
||||
tooltip="The video to edit.",
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=2147483647,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="Seed to use for generation.",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"watermark",
|
||||
default=False,
|
||||
tooltip="Whether to add an AI-generated watermark to the result.",
|
||||
advanced=True,
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Video.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model", "model.resolution"]),
|
||||
expr="""
|
||||
(
|
||||
$res := $lookup(widgets, "model.resolution");
|
||||
$ppsTable := { "720p": 0.14, "1080p": 0.24 };
|
||||
$pps := $lookup($ppsTable, $res);
|
||||
{ "type": "usd", "usd": $pps, "format": { "suffix": "/second" } }
|
||||
)
|
||||
""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
model: dict,
|
||||
video: Input.Video,
|
||||
seed: int,
|
||||
watermark: bool,
|
||||
):
|
||||
validate_string(model["prompt"], strip_whitespace=False, min_length=1)
|
||||
validate_video_duration(video, min_duration=3, max_duration=60)
|
||||
media = [Wan27MediaItem(type="video", url=await upload_video_to_comfyapi(cls, video))]
|
||||
reference_images = model.get("reference_images", {})
|
||||
for key in reference_images:
|
||||
media.append(
|
||||
Wan27MediaItem(
|
||||
type="reference_image", url=await upload_image_to_comfyapi(cls, image=reference_images[key])
|
||||
)
|
||||
)
|
||||
initial_response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(
|
||||
path="/proxy/wan/api/v1/services/aigc/video-generation/video-synthesis",
|
||||
method="POST",
|
||||
),
|
||||
response_model=TaskCreationResponse,
|
||||
data=Wan27VideoEditTaskCreationRequest(
|
||||
model=model["model"],
|
||||
input=Wan27VideoEditInputField(prompt=model["prompt"], media=media),
|
||||
parameters=Wan27VideoEditParametersField(
|
||||
resolution=model["resolution"],
|
||||
ratio=model["ratio"],
|
||||
duration=None,
|
||||
watermark=watermark,
|
||||
seed=seed,
|
||||
),
|
||||
),
|
||||
)
|
||||
if not initial_response.output:
|
||||
raise Exception(f"An unknown error occurred: {initial_response.code} - {initial_response.message}")
|
||||
response = await poll_op(
|
||||
cls,
|
||||
ApiEndpoint(path=f"/proxy/wan/api/v1/tasks/{initial_response.output.task_id}"),
|
||||
response_model=VideoTaskStatusResponse,
|
||||
status_extractor=lambda x: x.output.task_status,
|
||||
poll_interval=7,
|
||||
)
|
||||
return IO.NodeOutput(await download_url_to_video_output(response.output.video_url))
|
||||
|
||||
|
||||
class HappyHorseReferenceVideoApi(IO.ComfyNode):
|
||||
@classmethod
|
||||
def define_schema(cls):
|
||||
return IO.Schema(
|
||||
node_id="HappyHorseReferenceVideoApi",
|
||||
display_name="HappyHorse Reference to Video",
|
||||
category="api node/video/Wan",
|
||||
description="Generate a video featuring a person or object from reference materials with the HappyHorse "
|
||||
"model. Supports single-character performances and multi-character interactions.",
|
||||
inputs=[
|
||||
IO.DynamicCombo.Input(
|
||||
"model",
|
||||
options=[
|
||||
IO.DynamicCombo.Option(
|
||||
"happyhorse-1.0-r2v",
|
||||
[
|
||||
IO.String.Input(
|
||||
"prompt",
|
||||
multiline=True,
|
||||
default="",
|
||||
tooltip="Prompt describing the video. Use identifiers such as 'character1' and "
|
||||
"'character2' to refer to the reference characters.",
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"resolution",
|
||||
options=["720P", "1080P"],
|
||||
),
|
||||
IO.Combo.Input(
|
||||
"ratio",
|
||||
options=["16:9", "9:16", "1:1", "4:3", "3:4"],
|
||||
),
|
||||
IO.Int.Input(
|
||||
"duration",
|
||||
default=5,
|
||||
min=3,
|
||||
max=15,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
),
|
||||
IO.Autogrow.Input(
|
||||
"reference_images",
|
||||
template=IO.Autogrow.TemplateNames(
|
||||
IO.Image.Input("reference_image"),
|
||||
names=[
|
||||
"image1",
|
||||
"image2",
|
||||
"image3",
|
||||
"image4",
|
||||
"image5",
|
||||
"image6",
|
||||
"image7",
|
||||
"image8",
|
||||
"image9",
|
||||
],
|
||||
min=1,
|
||||
),
|
||||
),
|
||||
],
|
||||
),
|
||||
],
|
||||
),
|
||||
IO.Int.Input(
|
||||
"seed",
|
||||
default=0,
|
||||
min=0,
|
||||
max=2147483647,
|
||||
step=1,
|
||||
display_mode=IO.NumberDisplay.number,
|
||||
control_after_generate=True,
|
||||
tooltip="Seed to use for generation.",
|
||||
),
|
||||
IO.Boolean.Input(
|
||||
"watermark",
|
||||
default=False,
|
||||
tooltip="Whether to add an AI-generated watermark to the result.",
|
||||
advanced=True,
|
||||
),
|
||||
],
|
||||
outputs=[
|
||||
IO.Video.Output(),
|
||||
],
|
||||
hidden=[
|
||||
IO.Hidden.auth_token_comfy_org,
|
||||
IO.Hidden.api_key_comfy_org,
|
||||
IO.Hidden.unique_id,
|
||||
],
|
||||
is_api_node=True,
|
||||
price_badge=IO.PriceBadge(
|
||||
depends_on=IO.PriceBadgeDepends(widgets=["model", "model.resolution", "model.duration"]),
|
||||
expr="""
|
||||
(
|
||||
$res := $lookup(widgets, "model.resolution");
|
||||
$dur := $lookup(widgets, "model.duration");
|
||||
$ppsTable := { "720p": 0.14, "1080p": 0.24 };
|
||||
$pps := $lookup($ppsTable, $res);
|
||||
{ "type": "usd", "usd": $pps * $dur }
|
||||
)
|
||||
""",
|
||||
),
|
||||
)
|
||||
|
||||
@classmethod
|
||||
async def execute(
|
||||
cls,
|
||||
model: dict,
|
||||
seed: int,
|
||||
watermark: bool,
|
||||
):
|
||||
validate_string(model["prompt"], strip_whitespace=False, min_length=1)
|
||||
media = []
|
||||
reference_images = model.get("reference_images", {})
|
||||
for key in reference_images:
|
||||
media.append(
|
||||
Wan27MediaItem(
|
||||
type="reference_image",
|
||||
url=await upload_image_to_comfyapi(cls, image=reference_images[key]),
|
||||
)
|
||||
)
|
||||
if not media:
|
||||
raise ValueError("At least one reference reference image must be provided.")
|
||||
|
||||
initial_response = await sync_op(
|
||||
cls,
|
||||
ApiEndpoint(
|
||||
path="/proxy/wan/api/v1/services/aigc/video-generation/video-synthesis",
|
||||
method="POST",
|
||||
),
|
||||
response_model=TaskCreationResponse,
|
||||
data=Wan27ReferenceVideoTaskCreationRequest(
|
||||
model=model["model"],
|
||||
input=Wan27ReferenceVideoInputField(
|
||||
prompt=model["prompt"],
|
||||
negative_prompt=None,
|
||||
media=media,
|
||||
),
|
||||
parameters=Wan27ReferenceVideoParametersField(
|
||||
resolution=model["resolution"],
|
||||
ratio=model["ratio"],
|
||||
duration=model["duration"],
|
||||
watermark=watermark,
|
||||
seed=seed,
|
||||
),
|
||||
),
|
||||
)
|
||||
if not initial_response.output:
|
||||
raise Exception(f"An unknown error occurred: {initial_response.code} - {initial_response.message}")
|
||||
response = await poll_op(
|
||||
cls,
|
||||
ApiEndpoint(path=f"/proxy/wan/api/v1/tasks/{initial_response.output.task_id}"),
|
||||
response_model=VideoTaskStatusResponse,
|
||||
status_extractor=lambda x: x.output.task_status,
|
||||
poll_interval=7,
|
||||
)
|
||||
return IO.NodeOutput(await download_url_to_video_output(response.output.video_url))
|
||||
|
||||
|
||||
class WanApiExtension(ComfyExtension):
|
||||
@override
|
||||
async def get_node_list(self) -> list[type[IO.ComfyNode]]:
|
||||
@ -2211,10 +1660,6 @@ class WanApiExtension(ComfyExtension):
|
||||
Wan2VideoContinuationApi,
|
||||
Wan2VideoEditApi,
|
||||
Wan2ReferenceVideoApi,
|
||||
HappyHorseTextToVideoApi,
|
||||
HappyHorseImageToVideoApi,
|
||||
HappyHorseVideoEditApi,
|
||||
HappyHorseReferenceVideoApi,
|
||||
]
|
||||
|
||||
|
||||
|
||||
@ -5,7 +5,6 @@ import psutil
|
||||
import time
|
||||
import torch
|
||||
from typing import Sequence, Mapping, Dict
|
||||
from comfy.model_patcher import ModelPatcher
|
||||
from comfy_execution.graph import DynamicPrompt
|
||||
from abc import ABC, abstractmethod
|
||||
|
||||
@ -524,15 +523,13 @@ class RAMPressureCache(LRUCache):
|
||||
self.timestamps[self.cache_key_set.get_data_key(node_id)] = time.time()
|
||||
super().set_local(node_id, value)
|
||||
|
||||
def ram_release(self, target, free_active=False):
|
||||
def ram_release(self, target):
|
||||
if psutil.virtual_memory().available >= target:
|
||||
return
|
||||
|
||||
clean_list = []
|
||||
|
||||
for key, cache_entry in self.cache.items():
|
||||
if not free_active and self.used_generation[key] == self.generation:
|
||||
continue
|
||||
oom_score = RAM_CACHE_OLD_WORKFLOW_OOM_MULTIPLIER ** (self.generation - self.used_generation[key])
|
||||
|
||||
ram_usage = RAM_CACHE_DEFAULT_RAM_USAGE
|
||||
@ -545,9 +542,6 @@ class RAMPressureCache(LRUCache):
|
||||
scan_list_for_ram_usage(output)
|
||||
elif isinstance(output, torch.Tensor) and output.device.type == 'cpu':
|
||||
ram_usage += output.numel() * output.element_size()
|
||||
elif isinstance(output, ModelPatcher) and self.used_generation[key] != self.generation:
|
||||
#old ModelPatchers are the first to go
|
||||
ram_usage = 1e30
|
||||
scan_list_for_ram_usage(cache_entry.outputs)
|
||||
|
||||
oom_score *= ram_usage
|
||||
|
||||
@ -637,7 +637,7 @@ class SaveGLB(IO.ComfyNode):
|
||||
],
|
||||
tooltip="Mesh or 3D file to save",
|
||||
),
|
||||
IO.String.Input("filename_prefix", default="3d/ComfyUI"),
|
||||
IO.String.Input("filename_prefix", default="mesh/ComfyUI"),
|
||||
],
|
||||
hidden=[IO.Hidden.prompt, IO.Hidden.extra_pnginfo]
|
||||
)
|
||||
|
||||
@ -2,7 +2,6 @@ import numpy as np
|
||||
import scipy.ndimage
|
||||
import torch
|
||||
import comfy.utils
|
||||
import comfy.model_management
|
||||
import node_helpers
|
||||
from typing_extensions import override
|
||||
from comfy_api.latest import ComfyExtension, IO, UI
|
||||
@ -189,7 +188,7 @@ class SolidMask(IO.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
def execute(cls, value, width, height) -> IO.NodeOutput:
|
||||
out = torch.full((1, height, width), value, dtype=torch.float32, device=comfy.model_management.intermediate_device())
|
||||
out = torch.full((1, height, width), value, dtype=torch.float32, device="cpu")
|
||||
return IO.NodeOutput(out)
|
||||
|
||||
solid = execute # TODO: remove
|
||||
@ -263,7 +262,6 @@ class MaskComposite(IO.ComfyNode):
|
||||
def execute(cls, destination, source, x, y, operation) -> IO.NodeOutput:
|
||||
output = destination.reshape((-1, destination.shape[-2], destination.shape[-1])).clone()
|
||||
source = source.reshape((-1, source.shape[-2], source.shape[-1]))
|
||||
source = source.to(output.device)
|
||||
|
||||
left, top = (x, y,)
|
||||
right, bottom = (min(left + source.shape[-1], destination.shape[-1]), min(top + source.shape[-2], destination.shape[-2]))
|
||||
|
||||
@ -54,7 +54,7 @@ class EmptySD3LatentImage(io.ComfyNode):
|
||||
|
||||
@classmethod
|
||||
def execute(cls, width, height, batch_size=1) -> io.NodeOutput:
|
||||
latent = torch.zeros([batch_size, 16, height // 8, width // 8], device=comfy.model_management.intermediate_device(), dtype=comfy.model_management.intermediate_dtype())
|
||||
latent = torch.zeros([batch_size, 16, height // 8, width // 8], device=comfy.model_management.intermediate_device())
|
||||
return io.NodeOutput({"samples": latent, "downscale_ratio_spacial": 8})
|
||||
|
||||
generate = execute # TODO: remove
|
||||
|
||||
@ -1,3 +1,3 @@
|
||||
# This file is automatically generated by the build process when version is
|
||||
# updated in pyproject.toml.
|
||||
__version__ = "0.20.1"
|
||||
__version__ = "0.19.3"
|
||||
|
||||
@ -779,7 +779,7 @@ class PromptExecutor:
|
||||
|
||||
if self.cache_type == CacheType.RAM_PRESSURE:
|
||||
comfy.model_management.free_memory(0, None, pins_required=ram_headroom, ram_required=ram_headroom)
|
||||
ram_release_callback(ram_headroom, free_active=True)
|
||||
comfy.memory_management.extra_ram_release(ram_headroom)
|
||||
else:
|
||||
# Only execute when the while-loop ends without break
|
||||
# Send cached UI for intermediate output nodes that weren't executed
|
||||
|
||||
6
nodes.py
6
nodes.py
@ -32,7 +32,7 @@ import comfy.controlnet
|
||||
from comfy.comfy_types import IO, ComfyNodeABC, InputTypeDict, FileLocator
|
||||
from comfy_api.internal import register_versions, ComfyAPIWithVersion
|
||||
from comfy_api.version_list import supported_versions
|
||||
from comfy_api.latest import io, ComfyExtension, InputImpl
|
||||
from comfy_api.latest import io, ComfyExtension
|
||||
|
||||
import comfy.clip_vision
|
||||
|
||||
@ -1716,10 +1716,6 @@ class LoadImage:
|
||||
def load_image(self, image):
|
||||
image_path = folder_paths.get_annotated_filepath(image)
|
||||
|
||||
components = InputImpl.VideoFromFile(image_path).get_components()
|
||||
if components.images.shape[0] > 0:
|
||||
return (components.images, 1.0 - components.alpha[..., -1] if components.alpha is not None else torch.zeros((components.images.shape[0], 64, 64), dtype=torch.float32, device="cpu"))
|
||||
|
||||
img = node_helpers.pillow(Image.open, image_path)
|
||||
|
||||
output_images = []
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
[project]
|
||||
name = "ComfyUI"
|
||||
version = "0.20.1"
|
||||
version = "0.19.3"
|
||||
readme = "README.md"
|
||||
license = { file = "LICENSE" }
|
||||
requires-python = ">=3.10"
|
||||
|
||||
@ -1,5 +1,5 @@
|
||||
comfyui-frontend-package==1.42.15
|
||||
comfyui-workflow-templates==0.9.63
|
||||
comfyui-frontend-package==1.42.14
|
||||
comfyui-workflow-templates==0.9.62
|
||||
comfyui-embedded-docs==0.4.4
|
||||
torch
|
||||
torchsde
|
||||
@ -23,7 +23,7 @@ SQLAlchemy>=2.0
|
||||
filelock
|
||||
av>=14.2.0
|
||||
comfy-kitchen>=0.2.8
|
||||
comfy-aimdo==0.3.0
|
||||
comfy-aimdo==0.2.14
|
||||
requests
|
||||
simpleeval>=1.0.0
|
||||
blake3
|
||||
|
||||
Loading…
Reference in New Issue
Block a user