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name: varg-tryon-video description: >- Turns a flat-lay or product photo of clothing into a try-on video on varg: clean the garment photo, dress a model photo in it with Bria Virtual Try-On (or a Nano Banana / GPT Image edit for harder garments), keep the same model across shots, then animate fit-check motions that sell clothes (slow turn, tug and let fall, walk to camera, mirror selfie, fabric close-up) on Kling 4 or Seedance 2.5 with the garment kept intact, and add size captions so the fit is honest. Use when a fashion or apparel seller (Shopify, TikTok Shop, Amazon, dropshipping) asks for a try-on video, "my clothes on a model", an AI model wearing their product, a fit-check or outfit video, a try-on haul, or virtual try-on from flat-lays. Not for accessories that need no body (use product-photo-to-video) or for consistent characters across a story (varg-character-design). license: MIT metadata: author: vargHQ version: "1.0.0" openclaw: requires: anyBins: - curl homepage: https://varg.ai/how-to compatibility: >- Needs a VARG_API_KEY with curl (see the varg-ai skill) or the varg MCP connection (https://mcp.varg.ai/mcp). ffmpeg to cut and caption the final ad. allowed-tools: Bash(curl:) Bash(jq:) Bash(ffmpeg:) Bash(ffprobe:) Read Write Edit

Flat-lay to try-on video

Open-source try-on models (OOTDiffusion, IDM-VTON, CatVTON) make stills and most carry research licences; nobody ships a clean video path. On varg it is two steps: a try-on still, then image-to-video with fit-check motion. Fit causes about half of apparel returns, so the video must show the real drape and say the size.

1. Clean the inputs

• Garment: flat-lay or ghost-mannequin photo, 1000 px or more (resolution is the biggest quality factor), tags and measurement labels removed (the model reads them as print). Write a garment-truth caption of only what is visible: fabric, colours, print or stripe pattern, buttons, pockets, logo text and position, hem length.
• Model: a full-body photo (head to shoes, arms relaxed, plain room), a generated one or a consenting real person. Keep one model per product line; for more shots, make a 4-view sheet (front, 45°, side, close-up) with varg-character-design.

2. Dress the model (still)

curl -s -X POST https://api.varg.ai/v2/image -H "Authorization: Bearer $VARG_API_KEY" -H "Content-Type: application/json" \
  -d '{"model":"bria_fibo_edit_1_5_virtual_try_on","files":[{"url":"MODEL_URL"},{"url":"GARMENT_URL"}],
       "prompt":"Dress the woman in the cardigan from the second image, worn open over her white t-shirt. Keep her face, hair, pose, jeans, sneakers and the room unchanged."}'

4 credits. For two garments or accessories, add up to three garment images. For prints, logos or embroidery Bria softens, try nano_banana_2_1 or gpt_image_2_5 with both images and: "preserve all visible text, graphics, prints and seams; do not add text, logos or accessories; full body, hem visible" (test notes). Compare against the garment-truth caption before animating.

3. Animate fit-check motions

One motion per 5 s clip, camera locked, full body and hem in frame, hands away from the print:

| Motion | Prompt core | |---|---| | Turn | "turns slowly 90 degrees to show the side, pauses, turns back" | | Tug and fall | "lightly tugs both front edges and lets go so it falls open naturally" | | Walk to camera | "walks three steps toward the camera, fabric moves with weight" | | Mirror selfie | "phone mirror selfie, shifts weight, checks the back in the mirror" | | Detail | "close-up: fingers pinch the knit at the cuff, slow pan across the texture" |

Fashion fit-check video, phone on a tripod, camera locked, full body and the hem always in frame.
<motion>. Hands stay away from the front panel. <fabric> moves with weight; <pattern, buttons, logo>
stay exactly the same. Natural window light, realistic iPhone footage, no text.

kling_v4 (79 credits per 5 s, 720p) held the stripes and buttons in our test; seedance_2_5 adds references (pass the garment as @image2) when Kling drifts. Cut 3–4 clips into a 15 s ad with a voiceover or music and captions.

4. Honest fit and labels

• Caption the size: "Model 170 cm, wears M". Offer 2–3 body types for bestsellers.
• Show realistic drape; don't let the model slim or reshape the body.
• AI model = AI label on TikTok and Meta; in ads reaching New York, a visible synthetic-performer disclosure (ai-ad-compliance-check). Never use a real person's likeness without consent.

Failure modes

Logo or micro-print melts in motion → slower motion, add a static close-up, or drop that shot. Hands on the garment → the hidden part is redrawn. Hem or length drifts → "full body and hem in frame". Colour flicker → name the exact colours. Face drift → one model photo per product, 4-view sheet for series.

Tested

2026-10-28: a cream cardigan with navy stripes and pearl buttons (flat-lay from nano_banana_2_1) on a full-body model photo. bria_fibo_edit_1_5_virtual_try_on dressed her in one call (4 credits), keeping face, room, jeans and the stripes; it dropped the two patch pockets. kling_v4 fit check, 5 s (79 credits): she turns to the side, turns back, tugs the cardigan open; stripes and buttons held. https://s3.varg.ai/files/194b94d0-58ff-4e8b-91de-4f1959d04013/file_1213e32adbda.mp4

Related skills

varg-character-design (a model who stays the same), varg-product-lock (garment details as references), ai-ad-compliance-check, varg-ad-variants (one per body type or colour), varg-ai.