# City Teleport

> Place a person’s photo into iconic cities worldwide.


## Overview

- **Endpoint**: `https://fal.run/fal-ai/image-apps-v2/city-teleport`
- **Model ID**: `fal-ai/image-apps-v2/city-teleport`
- **Category**: image-to-image
- **Kind**: inference
**Tags**: city-teleport, backgroundswap



## Pricing

- **Price**: $0.04 per images

For more details, see [fal.ai pricing](https://fal.ai/pricing).

## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
See the input and output schema below, as well as the usage examples.


### Input Schema

The API accepts the following input parameters:


- **`person_image_url`** (`string`, _required_):
  Person photo URL
  - Examples: "https://v3.fal.media/files/kangaroo/qsFWu-bO3FwcTQSym9HeL_e52f70668f2940a3b4ea2cab54fcb65b.png"

- **`city_image_url`** (`string`, _optional_):
  Optional city background image URL. When provided, the person will be blended into this custom scene.

- **`city_name`** (`string`, _required_):
  City name (used when city_image_url is not provided)
  - Examples: "Paris"

- **`photo_shot`** (`PhotoShotEnum`, _optional_):
  Type of photo shot Default value: `"medium_shot"`
  - Default: `"medium_shot"`
  - Options: `"extreme_close_up"`, `"close_up"`, `"medium_close_up"`, `"medium_shot"`, `"medium_long_shot"`, `"long_shot"`, `"extreme_long_shot"`, `"full_body"`

- **`camera_angle`** (`CameraAngleEnum`, _optional_):
  Camera angle for the shot Default value: `"eye_level"`
  - Default: `"eye_level"`
  - Options: `"eye_level"`, `"low_angle"`, `"high_angle"`, `"dutch_angle"`, `"birds_eye_view"`, `"worms_eye_view"`, `"overhead"`, `"side_angle"`

- **`aspect_ratio`** (`AspectRatio`, _optional_):
  Aspect ratio for 4K output



**Required Parameters Example**:

```json
{
  "person_image_url": "https://v3.fal.media/files/kangaroo/qsFWu-bO3FwcTQSym9HeL_e52f70668f2940a3b4ea2cab54fcb65b.png",
  "city_name": "Paris"
}
```

**Full Example**:

```json
{
  "person_image_url": "https://v3.fal.media/files/kangaroo/qsFWu-bO3FwcTQSym9HeL_e52f70668f2940a3b4ea2cab54fcb65b.png",
  "city_name": "Paris",
  "photo_shot": "medium_shot",
  "camera_angle": "eye_level"
}
```


### Output Schema

The API returns the following output format:

- **`images`** (`list<Image>`, _required_):
  Person teleported to city location
  - Array of Image
  - Examples: [{"url":"https://v3b.fal.media/files/b/zebra/IxujEn7zMTwi7JwUFayG0_d0810ad048a24c6d9d80a68c4325a675.png"}]



**Example Response**:

```json
{
  "images": [
    {
      "url": "https://v3b.fal.media/files/b/zebra/IxujEn7zMTwi7JwUFayG0_d0810ad048a24c6d9d80a68c4325a675.png"
    }
  ]
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/fal-ai/image-apps-v2/city-teleport \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "person_image_url": "https://v3.fal.media/files/kangaroo/qsFWu-bO3FwcTQSym9HeL_e52f70668f2940a3b4ea2cab54fcb65b.png",
     "city_name": "Paris"
   }'
```

### Python

Ensure you have the Python client installed:

```bash
pip install fal-client
```

Then use the API client to make requests:

```python
import fal_client

def on_queue_update(update):
    if isinstance(update, fal_client.InProgress):
        for log in update.logs:
           print(log["message"])

result = fal_client.subscribe(
    "fal-ai/image-apps-v2/city-teleport",
    arguments={
        "person_image_url": "https://v3.fal.media/files/kangaroo/qsFWu-bO3FwcTQSym9HeL_e52f70668f2940a3b4ea2cab54fcb65b.png",
        "city_name": "Paris"
    },
    with_logs=True,
    on_queue_update=on_queue_update,
)
print(result)
```

### JavaScript

Ensure you have the JavaScript client installed:

```bash
npm install --save @fal-ai/client
```

Then use the API client to make requests:

```javascript
import { fal } from "@fal-ai/client";

const result = await fal.subscribe("fal-ai/image-apps-v2/city-teleport", {
  input: {
    person_image_url: "https://v3.fal.media/files/kangaroo/qsFWu-bO3FwcTQSym9HeL_e52f70668f2940a3b4ea2cab54fcb65b.png",
    city_name: "Paris"
  },
  logs: true,
  onQueueUpdate: (update) => {
    if (update.status === "IN_PROGRESS") {
      update.logs.map((log) => log.message).forEach(console.log);
    }
  },
});
console.log(result.data);
console.log(result.requestId);
```


## Additional Resources

### Documentation

- [Model Playground](https://fal.ai/models/fal-ai/image-apps-v2/city-teleport)
- [API Documentation](https://fal.ai/models/fal-ai/image-apps-v2/city-teleport/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/image-apps-v2/city-teleport)

### fal.ai Platform

- [Platform Documentation](https://fal.ai/docs/documentation)
- [Python Client](https://fal.ai/docs/api-reference/client-libraries/python)
- [JavaScript Client](https://fal.ai/docs/api-reference/client-libraries/javascript)

### Other agent-readable surfaces

This file covers one model. To find anything else:

- [Platform overview](https://fal.ai/llms.txt): Entry points and representative endpoint IDs
- [Documentation index](https://fal.ai/docs/llms.txt): Every documentation page
- [Full documentation text](https://fal.ai/docs/llms-full.txt): The whole documentation inlined
- Any other model: `https://fal.ai/models/<endpoint-id>/llms.txt`