Wan 2.2 Spicy Image To Video LoRA

Wan 2.2 Spicy Image To Video LoRA

Playground

Generate AI videos with personalized styles using LoRA. Upload images and apply a trained style model to WAN 2.2 — create unique, stylized videos with consistent visual identity.

Features

WAN 2.2 Spicy (LoRA) is an enhanced image-to-video generation model built on the WAN 2.2 multimodal architecture, now featuring LoRA fine-tuning support. It transforms static images into cinematic 480p or 720p motion videos with rich color, expressive movement, and customizable style — ideal for creators, artists, and visual designers.

🔥 Why It Looks Great

• Dynamic Realism: captures smooth, coherent motion with stable subjects and natural camera transitions.
• Cinematic Aesthetics: reproduces professional-grade lighting, depth, and color balance.
• Enhanced with LoRA: supports up to 3 LoRAs per job, allowing style, character, or motion customization.
• Adaptive Motion Design: intelligently adjusts motion intensity based on prompt semantics.
• Flexible Output: supports both portrait and landscape formats for social media or cinematic projects.

✨ Key Features

• Expressive Motion Synthesis — vivid, coherent motion generation with stable frames.
• LoRA Fine-Tuning (up to 3 LoRAs) — apply custom LoRAs for artistic control or stylistic consistency.
• Flexible Duration Options — 5s or 8s video generation for short-form storytelling.
• Artistic Style Adaptation — from realistic visuals to stylized anime or painterly looks.
• Lighting & Color Optimization — automatic tone mapping for cinematic mood and depth.

⚙️ Specifications

• Input: Single image (JPG, PNG)
• Output: Video (480p / 720p, MP4 format)
• Duration: 5s or 8s
• LoRA Support: up to 3 LoRAs (Support high_noise and low_noise)
• Seed Control: Optional reproducibility

💰 Pricing

🧩 How to Use

1. Upload your image (high-quality reference recommended).
2. Enter a prompt describing motion, tone, or camera action.
3. (Optional) Add up to 3 LoRAs under loras, high_noise_loras, or low_noise_loras.
4. Choose resolution (480p or 720p) and duration (5s or 8s).
5. (Optional) Set seed for reproducibility.
6. Click Run to generate your video.

📝 Notes

• Works best with well-lit, clear images.
• Avoid overly complex prompts to maintain clean motion.
• LoRA sources must be from reliable repositories with open access.
• For stronger visual identity, test combinations of low_noise and high_noise LoRAs.
• If the output seems static, increase motion-related phrasing in your prompt.

📄Reference

• How to train your LoRA?
• How to use your LoRA?
• The train method on WaveSpeedAI

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "resolution": "480p",
  "duration": 5,
  "seed": -1
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/wan-2.2-spicy/image-to-video-lora" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "${TASK}" | jq -r '.urls.get // empty')
if [ -z "${RESULT_URL}" ]; then RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"; fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}")
  RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "${STATUS}" >&2; exit 1 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

Response Parameters

Result Request Parameters

Result Response Parameters