klingai-image-to-video

What this skill does

# Kling AI Image-to-Video

## Overview

Animate static images using the `/v1/videos/image2video` endpoint. Supports motion prompts, camera control, dynamic masks (motion brush), static masks, and tail images for start-to-end transitions.

**Endpoint:** `POST https://api.klingai.com/v1/videos/image2video`

## Request Parameters

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `model_name` | string | Yes | `kling-v1-5`, `kling-v2-1`, `kling-v2-master`, etc. |
| `image` | string | Yes | URL of the source image (JPG, PNG, WebP) |
| `prompt` | string | No | Motion description for the animation |
| `negative_prompt` | string | No | What to exclude |
| `duration` | string | Yes | `"5"` or `"10"` seconds |
| `aspect_ratio` | string | No | `"16:9"` default |
| `mode` | string | No | `"standard"` or `"professional"` |
| `cfg_scale` | float | No | Prompt adherence (0.0-1.0) |
| `image_tail` | string | No | End-frame image URL (mutually exclusive with masks/camera) |
| `camera_control` | object | No | Camera movement (mutually exclusive with masks/image_tail) |
| `static_mask` | string | No | Mask image URL for fixed regions |
| `dynamic_masks` | array | No | Motion brush trajectories |
| `callback_url` | string | No | Webhook for completion |

## Basic Image-to-Video

```python
import jwt, time, os, requests

BASE = "https://api.klingai.com/v1"

def get_headers():
    ak, sk = os.environ["KLING_ACCESS_KEY"], os.environ["KLING_SECRET_KEY"]
    token = jwt.encode(
        {"iss": ak, "exp": int(time.time()) + 1800, "nbf": int(time.time()) - 5},
        sk, algorithm="HS256", headers={"alg": "HS256", "typ": "JWT"}
    )
    return {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}

# Animate a landscape photo
response = requests.post(f"{BASE}/videos/image2video", headers=get_headers(), json={
    "model_name": "kling-v2-1",
    "image": "https://example.com/landscape.jpg",
    "prompt": "Clouds slowly drifting across the sky, gentle wind rustling through trees",
    "negative_prompt": "static, frozen, blurry",
    "duration": "5",
    "mode": "standard",
})

task_id = response.json()["data"]["task_id"]

# Poll for result
while True:
    time.sleep(15)
    result = requests.get(
        f"{BASE}/videos/image2video/{task_id}", headers=get_headers()
    ).json()
    if result["data"]["task_status"] == "succeed":
        print(f"Video: {result['data']['task_result']['videos'][0]['url']}")
        break
    elif result["data"]["task_status"] == "failed":
        raise RuntimeError(result["data"]["task_status_msg"])
```

## Start-to-End Transition (image_tail)

Use `image_tail` to specify both the first and last frame. Kling interpolates the motion between them.

```python
response = requests.post(f"{BASE}/videos/image2video", headers=get_headers(), json={
    "model_name": "kling-v2-master",
    "image": "https://example.com/sunrise.jpg",        # first frame
    "image_tail": "https://example.com/sunset.jpg",    # last frame
    "prompt": "Time lapse of sun moving across the sky",
    "duration": "5",
    "mode": "professional",
})
```

## Motion Brush (dynamic_masks)

Draw motion paths for specific elements in the image. Up to 6 motion paths per image in v2.6.

```python
response = requests.post(f"{BASE}/videos/image2video", headers=get_headers(), json={
    "model_name": "kling-v2-6",
    "image": "https://example.com/person-standing.jpg",
    "prompt": "Person walking forward naturally",
    "duration": "5",
    "dynamic_masks": [
        {
            "mask": "https://example.com/person-mask.png",  # white = selected region
            "trajectories": [
                {"x": 0.5, "y": 0.7, "t": 0.0},   # start position (normalized 0-1)
                {"x": 0.5, "y": 0.5, "t": 0.5},   # midpoint
                {"x": 0.5, "y": 0.3, "t": 1.0},   # end position
            ]
        }
    ],
})
```

## Static Mask (freeze regions)

Keep specific areas of the image static while animating the rest.

```python
response = requests.post(f"{BASE}/videos/image2video", headers=get_headers(), json={
    "model_name": "kling-v2-master",
    "image": "https://example.com/scene.jpg",
    "prompt": "Water flowing in the river, birds flying",
    "duration": "5",
    "static_mask": "https://example.com/buildings-mask.png",  # white = frozen
})
```

## Mutual Exclusivity Rules

These features cannot be combined in a single request:

| Feature Set A | Feature Set B |
|--------------|--------------|
| `image_tail` | `dynamic_masks`, `static_mask`, `camera_control` |
| `dynamic_masks` / `static_mask` | `image_tail`, `camera_control` |
| `camera_control` | `image_tail`, `dynamic_masks`, `static_mask` |

## Image Requirements

| Constraint | Value |
|-----------|-------|
| Formats | JPG, PNG, WebP |
| Max size | 10 MB |
| Min resolution | 300x300 px |
| Max resolution | 4096x4096 px |
| Mask format | PNG with white (selected) / black (excluded) |

## Error Handling

| Error | Cause | Fix |
|-------|-------|-----|
| `400` invalid image | URL unreachable or wrong format | Verify image URL is publicly accessible |
| `400` mutual exclusivity | Combined incompatible features | Use only one feature set per request |
| `task_status: failed` | Image too complex or low quality | Use higher resolution, clearer source |
| Mask mismatch | Mask dimensions differ from source | Ensure mask matches source image dimensions |

## Resources

- [Image-to-Video API](https://app.klingai.com/global/dev/document-api/apiReference/model/imageToVideo)
- [Motion Control Guide](https://app.klingai.com/global/quickstart/motion-control-user-guide)