工作流 /
产品与广告 /
用你的产品生成海报/广告素材

用你的产品生成海报/广告素材
Generate Poster/Ad Asset with your Product
上传您的产品和一个简单的文本提示词,用于海报或广告设计。在将产品放入生成的布局之前,迭代调整外观。
产品与广告
10 个节点 1 个输入 28 次使用 ComfyUI ≥ 0.35.2 hellorob 28 KB
节点构成
Reroute
× 2
SaveImage
× 2
ByteDanceSeedreamNode
× 2
PreviewAny
× 1
GeminiNode
× 1
LoadImage
× 1
62df1500-5aa3-4efd-95e7-cd3db70f1ded
× 1
官方标注的模型
ByteDanceGoogle GeminiSeedream
工作流 JSON
和上面「下载工作流 JSON」是同一份文件。
1{
2 "id": "78d65a1a-02c1-4110-a553-0dcb04018754",
3 "revision": 0,
4 "last_node_id": 45,
5 "last_link_id": 52,
6 "nodes": [
7 {
8 "id": 27,
9 "type": "Reroute",
10 "pos": [
11 1370,
12 30
13 ],
14 "size": [
15 75,
16 26
17 ],
18 "flags": [],
19 "order": 6,
20 "mode": 0,
21 "inputs": [
22 {
23 "name": "",
24 "type": "*",
25 "link": 29
26 }
27 ],
28 "outputs": [
29 {
30 "name": "",
31 "type": "IMAGE",
32 "links": [
33 32
34 ]
35 }
36 ],
37 "properties": {
38 "showOutputText": false,
39 "horizontal": false
40 }
41 },
42 {
43 "id": 26,
44 "type": "Reroute",
45 "pos": [
46 1370,
47 960
48 ],
49 "size": [
50 75,
51 26
52 ],
53 "flags": [],
54 "order": 1,
55 "mode": 0,
56 "inputs": [
57 {
58 "name": "",
59 "type": "*",
60 "link": 27
61 }
62 ],
63 "outputs": [
64 {
65 "name": "",
66 "type": "IMAGE",
67 "links": [
68 33
69 ]
70 }
71 ],
72 "properties": {
73 "showOutputText": false,
74 "horizontal": false
75 }
76 },
77 {
78 "id": 24,
79 "type": "PreviewAny",
80 "pos": [
81 -120,
82 120
83 ],
84 "size": [
85 460,
86 770
87 ],
88 "flags": [],
89 "order": 3,
90 "mode": 0,
91 "inputs": [
92 {
93 "name": "source",
94 "type": "*",
95 "link": 24
96 }
97 ],
98 "outputs": [],
99 "title": "Preview Prompt as Text",
100 "properties": {
101 "Node name for S&R": "PreviewAny",
102 "cnr_id": "comfy-core",
103 "ver": "0.4.0"
104 },
105 "widgets_values": [
106 null,
107 null,
108 null
109 ]
110 },
111 {
112 "id": 10,
113 "type": "SaveImage",
114 "pos": [
115 825,
116 120
117 ],
118 "size": [
119 620,
120 770
121 ],
122 "flags": {
123 "collapsed": false
124 },
125 "order": 5,
126 "mode": 0,
127 "inputs": [
128 {
129 "name": "images",
130 "type": "IMAGE",
131 "link": 10
132 }
133 ],
134 "outputs": [],
135 "properties": {
136 "Node name for S&R": "SaveImage",
137 "cnr_id": "comfy-core",
138 "ver": "0.3.64",
139 "enableTabs": false,
140 "tabWidth": 65,
141 "tabXOffset": 10,
142 "hasSecondTab": false,
143 "secondTabText": "Send Back",
144 "secondTabOffset": 80,
145 "secondTabWidth": 65
146 },
147 "widgets_values": [
148 "ComfyUI-poster"
149 ]
150 },
151 {
152 "id": 13,
153 "type": "SaveImage",
154 "pos": [
155 2230,
156 120
157 ],
158 "size": [
159 620,
160 770
161 ],
162 "flags": [],
163 "order": 9,
164 "mode": 0,
165 "inputs": [
166 {
167 "name": "images",
168 "type": "IMAGE",
169 "link": 12
170 }
171 ],
172 "outputs": [],
173 "properties": {
174 "Node name for S&R": "SaveImage",
175 "cnr_id": "comfy-core",
176 "ver": "0.3.64",
177 "enableTabs": false,
178 "tabWidth": 65,
179 "tabXOffset": 10,
180 "hasSecondTab": false,
181 "secondTabText": "Send Back",
182 "secondTabOffset": 80,
183 "secondTabWidth": 65
184 },
185 "widgets_values": [
186 "ComfyUI-poster_product"
187 ]
188 },
189 {
190 "id": 23,
191 "type": "GeminiNode",
192 "pos": [
193 -610,
194 120
195 ],
196 "size": [
197 460,
198 770.0000000000001
199 ],
200 "flags": [],
201 "order": 2,
202 "mode": 0,
203 "inputs": [
204 {
205 "name": "images",
206 "shape": 7,
207 "type": "IMAGE",
208 "link": 47
209 },
210 {
211 "name": "audio",
212 "shape": 7,
213 "type": "AUDIO",
214 "link": null
215 },
216 {
217 "name": "video",
218 "shape": 7,
219 "type": "VIDEO",
220 "link": null
221 },
222 {
223 "name": "files",
224 "shape": 7,
225 "type": "GEMINI_INPUT_FILES",
226 "link": null
227 }
228 ],
229 "outputs": [
230 {
231 "name": "STRING",
232 "type": "STRING",
233 "links": [
234 24,
235 25
236 ]
237 }
238 ],
239 "title": "Prompt + Google Gemini Prompt Enhancer",
240 "properties": {
241 "Node name for S&R": "GeminiNode",
242 "cnr_id": "comfy-core",
243 "ver": "0.4.0"
244 },
245 "widgets_values": [
246 "The canned product sits on a reflective glass table, faintly reflecting the sky, liquid water textures sit on the table, small silicon computer chips are scattered around. In the blue sky, clouds form as text that says \"Comfy Cloud\" amongst scattered clouds. Realistic product photography.",
247 "gemini-3-pro-preview",
248 12345,
249 "randomize",
250 "# Role: Prompt Architect & Creative Director\n\n## 1. Core Objective\n\nYou are an expert **Prompt Engineer and Commercial Art Director**. Your mission is to transform natural language user requests—ranging from simple object/product names, mandatory H1 header titles, typography fonts styles to use, taglines phrases, to specific hex color codes, detailed brand briefs—into a **structured, detailed, and execution-ready English prompt**.\n\nYou must seamlessly integrate user-provided details (brand names, specific color codes, product features) while creatively \"gap-filling\" any missing aesthetic details to ensure a high-quality, cohesive visual output.\n\n\n## 2. Input Processing & Adaptation Strategy\n\nBefore generating the output, analyze the user's input against these three levels of granularity:\n\n* **Level 1: Sparse (e.g., \"a coffee poster\").**\n\n * *Action:* You must invent a cohesive brand identity, mood, and style. Infer a suitable context (e.g., a cozy morning or a high-energy workspace).\n\n* **Level 2: Hybrid (e.g., \"Retro sci-fi poster for a sleek energy drink\").**\n\n * *Action:* Adopt the requested style (\"Retro sci-fi\"). Create a visual scene that highlights the \"sleekness\" of the product. Invent a brand name if none is provided.\n\n* **Level 3: Specific (e.g., \"Rolex Submariner, underwater scene, emerald green and gold palette, Title: 'Deep Dive'\").**\n\n * *Action:* strictly adhere to the brand name, color palette, and specific product details provided. Do not deviate from these constraints.\n\n\n## 3. Output Structure Requirements\n\nYou must organize the final prompt into **five distinct dimensions**. Do not use bullet points within the sections; instead, write coherent, descriptive paragraphs for each dimension.\n\n\n### Dimension 1: Poster Content & Hero Object\n\n* **Goal:** Define the visual reality and the Product/Subject placement.\n\n* **Instruction:** clearly describe the main visual elements. If a product is mentioned, treat it as the \"Hero Object\"—describe its lighting, material qualities (e.g., condensation on a can, sheen on leather), and interaction with the environment.\n\n* **Example logic:** Instead of \"a shoe,\" write \"a floating high-top sneaker with reflective holographic panels, surrounded by shattered concrete debris suspended in mid-air.\"\n\n\n### Dimension 2: Aesthetic Style & Brand Identity\n\n* **Goal:** Define the artistic lens and color strategy.\n\n* **Instruction:** Describe the visual tone (e.g., cinematic, minimalist, brutalist, ethereal). **Crucial:** If the user provided brand colors, explicitly mandate them here. Describe the hex code colors into natural english, DO NOT output the actual hex code #. If no colors are provided, define a sophisticated palette that compliments the subject. Mention textures (e.g., matte finish, film grain, glossy plastic) and lighting style (e.g., volumetric god-rays, neon rim lighting).\n\n\n### Dimension 3: Poster Text\n\n* **Goal:** Define the exact strings to render.\n\n* **Instruction:** Provide **only** the exact text content to appear on the poster.\n\n 1. If the user provides a Brand Name/Title, use it exactly.\n\n 2. If the user provides *no* text, you **must** invent a short, punchy, thematic title or brand name that fits the vibe.\n\n 3. Maintain exact spelling and capitalization.\n\n\n### Dimension 4: Text Style and Position\n\n* **Goal:** Define typography and hierarchy.\n\n* **Instruction:**\n\n * **Font:** Describe the font family (e.g., bold sans-serif, elegant serif, handwritten marker, futuristic digital display).\n\n * **Attributes:** Specify material effects on the text (e.g., metallic gold, glowing neon, negative space cutout).\n\n * **Placement:** Describe the layout of the text relative to the image (e.g., bold header centered at the top, small legal text at the bottom, vertical tagline interlaced with the main subject).\n\n\n### Dimension 5: Layout\n\n* **Goal:** Define composition and flow.\n\n* **Instruction:** Describe how elements are arranged to guide the viewer's eye. Explain the relationship between the background and the foreground. Define the camera angle (e.g., low-angle hero shot, top-down flat lay, macro close-up). Ensure there is clear \"safe space\" for the text defined in Dimension 4 so it does not clash with the busy parts of the image.\n\n\n## 4. Strict Constraints\n\n1. **Language:** The final output must be in **English only**.\n\n2. **Purity:** Output **only** the structured prompt content. Do not include conversational fillers (e.g., \"Here is your prompt\"), explanations, or markdown code block fences (like ```).\n\n3. **Format:** Strictly follow the header structure shown in the \"Output Structure Requirements\"."
251 ],
252 "color": "#432",
253 "bgcolor": "#653"
254 },
255 {
256 "id": 14,
257 "type": "ByteDanceSeedreamNode",
258 "pos": [
259 370,
260 120
261 ],
262 "size": [
263 400,
264 450
265 ],
266 "flags": [],
267 "order": 4,
268 "mode": 0,
269 "inputs": [
270 {
271 "name": "image",
272 "shape": 7,
273 "type": "IMAGE",
274 "link": null
275 },
276 {
277 "name": "prompt",
278 "type": "STRING",
279 "widget": {
280 "name": "prompt"
281 },
282 "link": 25
283 }
284 ],
285 "outputs": [
286 {
287 "name": "IMAGE",
288 "type": "IMAGE",
289 "links": [
290 10,
291 29
292 ]
293 }
294 ],
295 "properties": {
296 "Node name for S&R": "ByteDanceSeedreamNode",
297 "cnr_id": "comfy-core",
298 "ver": "0.3.76"
299 },
300 "widgets_values": [
301 "seedream-4-5-251128",
302 "## Dimension 1: Poster Content Description\nThe central subject is an energetic, glossy-coated Fox Terrier with perked ears and a joyful expression, captured mid-leap or sitting attentively with a wagging tail. Beside the dog, in the lower foreground, sits a realistic open tin can of dog food with the lid peeled back, revealing hearty meat chunks, next to a ceramic yellow bowl filled to the brim. The background features a subtle, stylized sunburst pattern radiating from behind the dog to emphasize vitality and energy.\n\n## Dimension 2: Aesthetic Style Optimization\nThe image utilizes a vintage 1940s American advertising illustration style, characterized by a soft lithographic texture and visible halftone patterns. The color palette is nostalgic and warm, dominated by creamy off-whites, patriotic reds, mustard yellows, and muted navy blues. The overall finish mimics the look of aged paper or cardboard with slightly distressed edges and a matte, hand-painted quality typical of mid-century commercial art.\n\n## Dimension 3: Poster Text\nFIDELITY\nPREMIUM DOG RATION\nKeeps Him Full of Pep!\nRich in Vitamins\n10¢\n\n## Dimension 4: Text Style and Position\nThe brand name \"FIDELITY\" is rendered in massive, blocky, all-caps sans-serif typography with a slight 3D drop shadow, colored in vibrant red to command attention at the very top of the poster. The slogan \"Keeps Him Full of Pep!\" is written in a fluid, enthusiastic navy blue brush script, slanted upward to imply motion. The words \"PREMIUM DOG RATION\" and \"Rich in Vitamins\" appear in smaller, sturdy serif fonts near the bottom, while the price \"10¢\" is enclosed in a jagged starburst graphic near the product can.\n\n## Dimension 5: Layout\nThe composition follows a classic hierarchical vertical alignment. The large brand title arches across the top third, framing the dog's head. The dog serves as the central focal point, drawing the eye down toward the product placement in the lower left and right corners. The slogan cuts across the middle section to bridge the gap between the animal and the food, guiding the viewer's gaze in a smooth Z-pattern from the headline, through the dog, to the product details at the bottom.",
303 "1664x2496 (2:3)",
304 2048,
305 2048,
306 "auto",
307 1,
308 123,
309 "randomize",
310 false,
311 true
312 ],
313 "color": "#432",
314 "bgcolor": "#653"
315 },
316 {
317 "id": 19,
318 "type": "ByteDanceSeedreamNode",
319 "pos": [
320 1780,
321 120
322 ],
323 "size": [
324 400,
325 440
326 ],
327 "flags": [],
328 "order": 8,
329 "mode": 0,
330 "inputs": [
331 {
332 "name": "image",
333 "shape": 7,
334 "type": "IMAGE",
335 "link": 34
336 }
337 ],
338 "outputs": [
339 {
340 "name": "IMAGE",
341 "type": "IMAGE",
342 "links": [
343 12
344 ]
345 }
346 ],
347 "properties": {
348 "Node name for S&R": "ByteDanceSeedreamNode",
349 "cnr_id": "comfy-core",
350 "ver": "0.3.76"
351 },
352 "widgets_values": [
353 "seedream-4-5-251128",
354 "Replace the product from image 1 with the product from image 2. Ensure the products dimensions stay consistent with input image 2.",
355 "1664x2496 (2:3)",
356 2048,
357 2048,
358 "disabled",
359 1,
360 321,
361 "randomize",
362 false,
363 true
364 ],
365 "color": "#432",
366 "bgcolor": "#653"
367 },
368 {
369 "id": 15,
370 "type": "LoadImage",
371 "pos": [
372 -610,
373 960
374 ],
375 "size": [
376 460,
377 520
378 ],
379 "flags": [],
380 "order": 0,
381 "mode": 0,
382 "inputs": [],
383 "outputs": [
384 {
385 "name": "IMAGE",
386 "type": "IMAGE",
387 "links": [
388 27,
389 47
390 ]
391 },
392 {
393 "name": "MASK",
394 "type": "MASK",
395 "links": null
396 }
397 ],
398 "title": "Load Product Image",
399 "properties": {
400 "Node name for S&R": "LoadImage",
401 "cnr_id": "comfy-core",
402 "ver": "0.3.76"
403 },
404 "widgets_values": [
405 "comfy_cloud_water_can.jpg",
406 "image"
407 ],
408 "color": "#232",
409 "bgcolor": "#353"
410 },
411 {
412 "id": 29,
413 "type": "62df1500-5aa3-4efd-95e7-cd3db70f1ded",
414 "pos": [
415 1550,
416 120
417 ],
418 "size": [
419 170,
420 46
421 ],
422 "flags": {
423 "collapsed": false
424 },
425 "order": 7,
426 "mode": 0,
427 "inputs": [
428 {
429 "name": "image",
430 "type": "IMAGE",
431 "link": 32
432 },
433 {
434 "name": "image_1",
435 "type": "IMAGE",
436 "link": 33
437 }
438 ],
439 "outputs": [
440 {
441 "name": "IMAGE",
442 "type": "IMAGE",
443 "links": [
444 34
445 ]
446 }
447 ],
448 "properties": {
449 "proxyWidgets": [],
450 "cnr_id": "comfy-core",
451 "ver": "0.4.0"
452 },
453 "widgets_values": []
454 }
455 ],
456 "links": [
457 [
458 10,
459 14,
460 0,
461 10,
462 0,
463 "IMAGE"
464 ],
465 [
466 12,
467 19,
468 0,
469 13,
470 0,
471 "IMAGE"
472 ],
473 [
474 24,
475 23,
476 0,
477 24,
478 0,
479 "STRING"
480 ],
481 [
482 25,
483 23,
484 0,
485 14,
486 1,
487 "STRING"
488 ],
489 [
490 27,
491 15,
492 0,
493 26,
494 0,
495 "IMAGE"
496 ],
497 [
498 29,
499 14,
500 0,
501 27,
502 0,
503 "IMAGE"
504 ],
505 [
506 32,
507 27,
508 0,
509 29,
510 0,
511 "IMAGE"
512 ],
513 [
514 33,
515 26,
516 0,
517 29,
518 1,
519 "IMAGE"
520 ],
521 [
522 34,
523 29,
524 0,
525 19,
526 0,
527 "IMAGE"
528 ],
529 [
530 47,
531 15,
532 0,
533 23,
534 0,
535 "IMAGE"
536 ]
537 ],
538 "groups": [],
539 "definitions": {
540 "subgraphs": [
541 {
542 "id": "62df1500-5aa3-4efd-95e7-cd3db70f1ded",
543 "version": 1,
544 "state": {
545 "lastGroupId": 0,
546 "lastNodeId": 33,
547 "lastLinkId": 40,
548 "lastRerouteId": 0
549 },
550 "revision": 0,
551 "config": [],
552 "name": "Batch Images",
553 "inputNode": {
554 "id": -10,
555 "bounding": [
556 900,
557 150,
558 120,
559 80
560 ]
561 },
562 "outputNode": {
563 "id": -20,
564 "bounding": [
565 2720,
566 30,
567 120,
568 60
569 ]
570 },
571 "inputs": [
572 {
573 "id": "f7970979-e6f4-4ffa-ad60-c56de4393974",
574 "name": "image",
575 "type": "IMAGE",
576 "linkIds": [
577 30,
578 39
579 ],
580 "localized_name": "image",
581 "pos": [
582 1000,
583 170
584 ]
585 },
586 {
587 "id": "6c09881b-7313-4498-8614-6c2ac60945dc",
588 "name": "image_1",
589 "type": "IMAGE",
590 "linkIds": [
591 33
592 ],
593 "localized_name": "image_1",
594 "pos": [
595 1000,
596 190
597 ]
598 }
599 ],
600 "outputs": [
601 {
602 "id": "a3134f7e-4b22-49aa-9843-1f99a89677dc",
603 "name": "IMAGE",
604 "type": "IMAGE",
605 "linkIds": [
606 37
607 ],
608 "localized_name": "IMAGE",
609 "pos": [
610 2740,
611 50
612 ]
613 }
614 ],
615 "widgets": [],
616 "nodes": [
617 {
618 "id": 17,
619 "type": "ResizeAndPadImage",
620 "pos": [
621 1820,
622 260
623 ],
624 "size": [
625 270,
626 130
627 ],
628 "flags": {
629 "collapsed": false
630 },
631 "order": 2,
632 "mode": 0,
633 "inputs": [
634 {
635 "localized_name": "image",
636 "name": "image",
637 "type": "IMAGE",
638 "link": 35
639 },
640 {
641 "localized_name": "target_width",
642 "name": "target_width",
643 "type": "INT",
644 "widget": {
645 "name": "target_width"
646 },
647 "link": 16
648 },
649 {
650 "localized_name": "target_height",
651 "name": "target_height",
652 "type": "INT",
653 "widget": {
654 "name": "target_height"
655 },
656 "link": 17
657 }
658 ],
659 "outputs": [
660 {
661 "localized_name": "IMAGE",
662 "name": "IMAGE",
663 "type": "IMAGE",
664 "links": [
665 40
666 ]
667 }
668 ],
669 "properties": {
670 "Node name for S&R": "ResizeAndPadImage",
671 "cnr_id": "comfy-core",
672 "ver": "0.3.76"
673 },
674 "widgets_values": [
675 512,
676 512,
677 "black",
678 "area"
679 ]
680 },
681 {
682 "id": 16,
683 "type": "GetImageSize",
684 "pos": [
685 1640,
686 270
687 ],
688 "size": [
689 140,
690 70
691 ],
692 "flags": {
693 "collapsed": false
694 },
695 "order": 1,
696 "mode": 0,
697 "inputs": [
698 {
699 "localized_name": "image",
700 "name": "image",
701 "type": "IMAGE",
702 "link": 30
703 }
704 ],
705 "outputs": [
706 {
707 "localized_name": "width",
708 "name": "width",
709 "type": "INT",
710 "links": [
711 16
712 ]
713 },
714 {
715 "localized_name": "height",
716 "name": "height",
717 "type": "INT",
718 "links": [
719 17
720 ]
721 },
722 {
723 "localized_name": "batch_size",
724 "name": "batch_size",
725 "type": "INT",
726 "links": null
727 }
728 ],
729 "properties": {
730 "Node name for S&R": "GetImageSize",
731 "cnr_id": "comfy-core",
732 "ver": "0.3.76"
733 },
734 "widgets_values": []
735 },
736 {
737 "id": 29,
738 "type": "RemBGSession+",
739 "pos": [
740 1170,
741 430
742 ],
743 "size": [
744 270,
745 82
746 ],
747 "flags": [],
748 "order": 0,
749 "mode": 0,
750 "inputs": [],
751 "outputs": [
752 {
753 "localized_name": "REMBG_SESSION",
754 "name": "REMBG_SESSION",
755 "type": "REMBG_SESSION",
756 "links": [
757 32
758 ]
759 }
760 ],
761 "properties": {
762 "Node name for S&R": "RemBGSession+",
763 "cnr_id": "comfyui_essentials",
764 "ver": "1.1.0"
765 },
766 "widgets_values": [
767 "u2net: general purpose",
768 "CPU"
769 ]
770 },
771 {
772 "id": 30,
773 "type": "ImageRemoveBackground+",
774 "pos": [
775 1520,
776 440
777 ],
778 "size": [
779 242.9830078125,
780 46
781 ],
782 "flags": [],
783 "order": 3,
784 "mode": 0,
785 "inputs": [
786 {
787 "localized_name": "rembg_session",
788 "name": "rembg_session",
789 "type": "REMBG_SESSION",
790 "link": 32
791 },
792 {
793 "localized_name": "image",
794 "name": "image",
795 "type": "IMAGE",
796 "link": 33
797 }
798 ],
799 "outputs": [
800 {
801 "localized_name": "IMAGE",
802 "name": "IMAGE",
803 "type": "IMAGE",
804 "links": [
805 34,
806 35
807 ]
808 },
809 {
810 "localized_name": "MASK",
811 "name": "MASK",
812 "type": "MASK",
813 "links": null
814 }
815 ],
816 "properties": {
817 "Node name for S&R": "ImageRemoveBackground+",
818 "cnr_id": "comfyui_essentials",
819 "ver": "1.1.0"
820 },
821 "widgets_values": []
822 },
823 {
824 "id": 32,
825 "type": "PreviewImage",
826 "pos": [
827 2280,
828 340
829 ],
830 "size": [
831 230,
832 400
833 ],
834 "flags": [],
835 "order": 5,
836 "mode": 4,
837 "inputs": [
838 {
839 "localized_name": "images",
840 "name": "images",
841 "type": "IMAGE",
842 "link": 38
843 }
844 ],
845 "outputs": [],
846 "title": "Preview Batched Images",
847 "properties": {
848 "Node name for S&R": "PreviewImage",
849 "cnr_id": "comfy-core",
850 "ver": "0.4.0"
851 },
852 "widgets_values": []
853 },
854 {
855 "id": 31,
856 "type": "PreviewImage",
857 "pos": [
858 1830,
859 470
860 ],
861 "size": [
862 240,
863 310
864 ],
865 "flags": [],
866 "order": 4,
867 "mode": 4,
868 "inputs": [
869 {
870 "localized_name": "images",
871 "name": "images",
872 "type": "IMAGE",
873 "link": 34
874 }
875 ],
876 "outputs": [],
877 "title": "Product Remove BG",
878 "properties": {
879 "Node name for S&R": "PreviewImage",
880 "cnr_id": "comfy-core",
881 "ver": "0.4.0"
882 },
883 "widgets_values": []
884 },
885 {
886 "id": 33,
887 "type": "BatchImagesNode",
888 "pos": [
889 1910,
890 130
891 ],
892 "size": [
893 169.23046875,
894 66
895 ],
896 "flags": [],
897 "order": 6,
898 "mode": 0,
899 "inputs": [
900 {
901 "label": "image0",
902 "localized_name": "images.image0",
903 "name": "images.image0",
904 "type": "IMAGE",
905 "link": 39
906 },
907 {
908 "label": "image1",
909 "localized_name": "images.image1",
910 "name": "images.image1",
911 "type": "IMAGE",
912 "link": 40
913 },
914 {
915 "label": "image2",
916 "localized_name": "images.image2",
917 "name": "images.image2",
918 "shape": 7,
919 "type": "IMAGE",
920 "link": null
921 }
922 ],
923 "outputs": [
924 {
925 "localized_name": "IMAGE",
926 "name": "IMAGE",
927 "type": "IMAGE",
928 "links": [
929 37,
930 38
931 ]
932 }
933 ],
934 "properties": {
935 "Node name for S&R": "BatchImagesNode"
936 },
937 "widgets_values": []
938 }
939 ],
940 "groups": [],
941 "links": [
942 {
943 "id": 16,
944 "origin_id": 16,
945 "origin_slot": 0,
946 "target_id": 17,
947 "target_slot": 1,
948 "type": "INT"
949 },
950 {
951 "id": 17,
952 "origin_id": 16,
953 "origin_slot": 1,
954 "target_id": 17,
955 "target_slot": 2,
956 "type": "INT"
957 },
958 {
959 "id": 30,
960 "origin_id": -10,
961 "origin_slot": 0,
962 "target_id": 16,
963 "target_slot": 0,
964 "type": "IMAGE"
965 },
966 {
967 "id": 32,
968 "origin_id": 29,
969 "origin_slot": 0,
970 "target_id": 30,
971 "target_slot": 0,
972 "type": "REMBG_SESSION"
973 },
974 {
975 "id": 33,
976 "origin_id": -10,
977 "origin_slot": 1,
978 "target_id": 30,
979 "target_slot": 1,
980 "type": "IMAGE"
981 },
982 {
983 "id": 34,
984 "origin_id": 30,
985 "origin_slot": 0,
986 "target_id": 31,
987 "target_slot": 0,
988 "type": "IMAGE"
989 },
990 {
991 "id": 35,
992 "origin_id": 30,
993 "origin_slot": 0,
994 "target_id": 17,
995 "target_slot": 0,
996 "type": "IMAGE"
997 },
998 {
999 "id": 37,
1000 "origin_id": 33,
1001 "origin_slot": 0,
1002 "target_id": -20,
1003 "target_slot": 0,
1004 "type": "IMAGE"
1005 },
1006 {
1007 "id": 38,
1008 "origin_id": 33,
1009 "origin_slot": 0,
1010 "target_id": 32,
1011 "target_slot": 0,
1012 "type": "IMAGE"
1013 },
1014 {
1015 "id": 39,
1016 "origin_id": -10,
1017 "origin_slot": 0,
1018 "target_id": 33,
1019 "target_slot": 0,
1020 "type": "IMAGE"
1021 },
1022 {
1023 "id": 40,
1024 "origin_id": 17,
1025 "origin_slot": 0,
1026 "target_id": 33,
1027 "target_slot": 1,
1028 "type": "IMAGE"
1029 }
1030 ],
1031 "extra": {
1032 "workflowRendererVersion": "LG"
1033 }
1034 }
1035 ]
1036 },
1037 "config": [],
1038 "extra": {
1039 "frontendVersion": "1.37.6",
1040 "workflowRendererVersion": "LG",
1041 "VHS_latentpreview": false,
1042 "VHS_latentpreviewrate": 0,
1043 "VHS_MetadataImage": true,
1044 "VHS_KeepIntermediate": true,
1045 "ds": {
1046 "scale": 0.9403317594257539,
1047 "offset": [
1048 -760.5719330479835,
1049 150.92017326967346
1050 ]
1051 }
1052 },
1053 "version": 0.4
1054}