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Unified CLI (opentryon)

Once OpenTryOn is installed (pip install -e . or pip install opentryon), every adapter in the repo is available through a single opentryon command with three levels of control: service → model → parameters.

opentryon <service> --model <model> [params...]
  • service: what kind of task -- vton, generate, edit, understand, video-generate, bg-remove
  • model: which adapter/provider to use for that service, e.g. --model flux-vto
  • parameters: model-specific flags (image inputs, prompts, sampling knobs, etc.)

Services and Models​

ServiceWhat it doesModels
vtonVirtual try-on: compose a garment onto a person imageflux-vto, nova-canvas, kling-ai, segmind
generateText-to-image generationnano-banana, nano-banana-pro, nano-banana-2, flux2-pro, flux2-flex, flux2-turbo (local), gpt-image, luma-image
editImage editing (image + instruction → image)nano-banana, nano-banana-pro, nano-banana-2, flux2-pro, flux2-flex, flux2-turbo (local), gpt-image
understandImage/video understandingkimi-k2.6, kimi-k2.7-code, kimi-vl (local), llava-next (local)
video-generateText/image-to-video generationveo, sora, luma-video
bg-removeBackground removalben2 (local)

Models marked "local" run on your own GPU and require pip install opentryon[local]; everything else calls a cloud API and needs the corresponding API key set in your environment (see Configuration).

Discovering Flags​

Every level of the CLI is self-documenting:

opentryon --help                              # list services
opentryon understand --help                   # list models for a service
opentryon understand --model kimi-k2.6 --help # list that model's parameters

Examples​

# Virtual try-on
opentryon vton --model flux-vto \
  --person-image model.png --garment-image garment.png

# Text-to-image
opentryon generate --model nano-banana-pro \
  --prompt "A fashion model wearing elegant evening wear" --resolution 4K

# Image editing
opentryon edit --model gpt-image \
  --images person.jpg --prompt "Change the jacket to black leather"

# Image/video understanding (Kimi K2.6, general-purpose -- not fashion-only)
opentryon understand --model kimi-k2.6 \
  --image garment.jpg --prompt "Describe this outfit."
opentryon understand --model kimi-k2.6 \
  --video runway_clip.mp4 --prompt "Summarize the styling shown."

# Coding-focused multimodal understanding
opentryon understand --model kimi-k2.7-code \
  --image ui_mockup.png --prompt "Write the HTML/CSS for this design."

# Open-weight local understanding (no API key, needs a GPU)
opentryon understand --model kimi-vl --image garment.jpg

# Text-to-video
opentryon video-generate --model veo \
  --prompt "A model walking a runway in slow motion" --duration 6

# Background removal
opentryon bg-remove --model ben2 --image product.jpg --refine

Every command accepts -o/--output-dir (default: outputs/) and --dry-run (print the resolved adapter call without invoking the API/GPU):

opentryon vton --model flux-vto \
  --person-image model.png --garment-image garment.png --dry-run

Local (GPU-only) Models​

Local models (flux2-turbo, kimi-vl, llava-next, ben2) need the local extra:

pip install opentryon[local]

Running a local model without it prints an install hint instead of a raw stack trace:

✗ 'Kimi-VL (open-weight, local)' requires local ML dependencies that aren't installed.
  Install them with: pip install opentryon[local]

See Also​