pixverse/c1/start-end-to-video

image-to-video

Pixverse c1 Start-End-to-Video API by PIXVERSE

pixverse/c1/start-end-to-video

Start-end-to-video

Pixverse c1 Start-End-to-Video model. High-quality video generation from image prompts.

Pixverse c1 Start-End-to-Video is developed by PixVerse. Atlas Cloud (operated by Atlas Cloud AI LLC) provides access to it and does not own it. All trademarks belong to their respective owners.

INPUT

Prompt *

Image

You can drag and drop a file or click to upload

MAX:1

End Image

You can drag and drop a file or click to upload

MAX:1

Duration

Quality

Sound

Seed

OUTPUT

Idle

Your generated videos will appear here

Configure your settings and click Run to get started

Your request will cost $0.03 per run. For $10 you can run this model approximately 333 times.

Here's what you can do next:

Seedance 2.0 Kling v3 Vidu Wan2.7

Parameters

Code Example
import requests
import time

# Step 1: Start video generation
generate_url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "pixverse/c1/start-end-to-video",  # Required. model name
    "duration": 5,  # The duration of the generated media in seconds (1-15)
    "image": "example_value",  # First frame of the video; Notes: 1
    "end_image": "example_value",  # Last frame of the video; Notes: 1
    "prompt": "A beautiful sunset over the ocean with gentle waves",  # Required. The positive prompt for the generation
    "sound": True,  # Whether sound is generated simultaneously when generating a video
    "quality": "720p",  # The resolution of the generated video. options: 360p | 540p | 720p | 1080p
    "seed": 1,  # Random seed for reproducibility
}

generate_response = requests.post(generate_url, headers=headers, json=data)
generate_result = generate_response.json()
prediction_id = generate_result["data"]["id"]

# Step 2: Poll for result
poll_url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"

def check_status():
    while True:
        response = requests.get(poll_url, headers={"Authorization": "Bearer $ATLASCLOUD_API_KEY"})
        result = response.json()

        if result["data"]["status"] in ["completed", "succeeded"]:
            print("Generated video:", result["data"]["outputs"][0])
            return result["data"]["outputs"][0]
        elif result["data"]["status"] == "failed":
            raise Exception(result["data"]["error"] or "Generation failed")
        else:
            # Still processing, wait 2 seconds
            time.sleep(2)

video_url = check_status()

Install

Install the required package for your language.

pip install requests

Authentication

All API requests require authentication via an API key. You can get your API key from the Atlas Cloud dashboard.

export ATLASCLOUD_API_KEY="your-api-key-here"

HTTP Headers

import os

API_KEY = os.environ.get("ATLASCLOUD_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {API_KEY}"
}

Keep your API key secure

Never expose your API key in client-side code or public repositories. Use environment variables or a backend proxy instead.

Submit a request

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}
data = {
    "model": "your-model",
    "prompt": "A beautiful landscape"
}

response = requests.post(url, headers=headers, json=data)
print(response.json())

Submit a Request

Submit an asynchronous generation request. The API returns a prediction ID that you can use to check the status and retrieve the result.

POST/api/v1/model/generateVideo

Request Body

import requests

url = "https://api.atlascloud.ai/api/v1/model/generateVideo"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer $ATLASCLOUD_API_KEY"
}

data = {
    "model": "pixverse/c1/start-end-to-video",
    "prompt": "A beautiful sunset over the ocean with gentle waves"
}

response = requests.post(url, headers=headers, json=data)
result = response.json()

print(f"Prediction ID: {result['data']['id']}")
print(f"Status: {result['data']['status']}")

Response

{
  "code": 200,
  "data": {
    "id": "pred_abc123",
    "status": "processing",
    "model": "model-name",
    "created_at": "2025-01-01T00:00:00Z"
  }
}

Check Status

Poll the prediction endpoint to check the current status of your request.

GET/api/v1/model/prediction/{prediction_id}

Polling Example

import requests
import time

prediction_id = "pred_abc123"
url = f"https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

while True:
    response = requests.get(url, headers=headers)
    result = response.json()
    status = result["data"]["status"]
    print(f"Status: {status}")

    if status in ["completed", "succeeded"]:
        output_url = result["data"]["outputs"][0]
        print(f"Output URL: {output_url}")
        break
    elif status == "failed":
        print(f"Error: {result['data'].get('error', 'Unknown')}")
        break

    time.sleep(3)

Status Values

processingThe request is still being processed.

completedGeneration is complete. Outputs are available.

succeededGeneration succeeded. Outputs are available.

failedGeneration failed. Check the error field.

Completed Response

{
  "data": {
    "id": "pred_abc123",
    "status": "completed",
    "outputs": [
      "https://storage.atlascloud.ai/outputs/result.mp4"
    ],
    "metrics": {
      "predict_time": 45.2
    },
    "created_at": "2025-01-01T00:00:00Z",
    "completed_at": "2025-01-01T00:00:10Z"
  }
}

Upload Files

Upload files to Atlas Cloud storage and get a URL you can use in your API requests. Use multipart/form-data to upload.

POST/api/v1/model/uploadMedia

Upload Example

import requests

url = "https://api.atlascloud.ai/api/v1/model/uploadMedia"
headers = { "Authorization": "Bearer $ATLASCLOUD_API_KEY" }

with open("image.png", "rb") as f:
    files = {"file": ("image.png", f, "image/png")}
    response = requests.post(url, headers=headers, files=files)

result = response.json()
download_url = result["data"]["download_url"]
print(f"File URL: {download_url}")

Response

{
  "data": {
    "download_url": "https://storage.atlascloud.ai/uploads/abc123/image.png",
    "file_name": "image.png",
    "content_type": "image/png",
    "size": 1024000
  }
}

Input Schema

The following parameters are accepted in the request body.

Total: 8Required: 2Optional: 6

modelstringrequired

model name

Default: "pixverse/c1/start-end-to-video"

durationinteger

The duration of the generated media in seconds (1-15).

Default: 5

123456789101112131415

imagestring

First frame of the video; Notes: 1.Public URL or Base64. 2.Aspect ratios must be close: ratio between start/end frame must be in 0.8~1.25. 3.Format: png, jpeg, jpg, webp. 4.The post body of the HTTP request should not exceed 20MB

end_imagestring

Last frame of the video; Notes: 1.Public URL or Base64. 2.Aspect ratios must be close: ratio between start/end frame must be in 0.8~1.25. 3.Format: png, jpeg, jpg, webp. 4.The post body of the HTTP request should not exceed 20MB

promptstringrequired

The positive prompt for the generation.

soundboolean

Whether sound is generated simultaneously when generating a video.

Default: true

qualitystring

The resolution of the generated video.

Default: "720p"

360p540p720p1080p

seedinteger

Random seed for reproducibility.

Example Request Body

{
  "model": "pixverse/c1/start-end-to-video",
  "duration": 5,
  "prompt": "A beautiful landscape",
  "sound": true,
  "quality": "720p"
}

Output Schema

The API returns a prediction response with the generated output URLs.

created_atstring

ISO timestamp of when the request was created.

idstring

Unique identifier for the prediction.

modelstring

Model ID used for the prediction.

outputsarray

Array of URLs to the generated content.

statusstring

Status of the task: created, processing, completed, or failed.

Example Response

{
  "id": "pred_abc123",
  "status": "completed",
  "model": "model-name",
  "outputs": [
    "https://storage.atlascloud.ai/outputs/result.mp4"
  ],
  "metrics": {
    "predict_time": 45.2
  },
  "created_at": "2025-01-01T00:00:00Z",
  "completed_at": "2025-01-01T00:00:10Z"
}

Atlas Cloud Skills

Atlas Cloud Skills integrates 400+ AI models directly into your AI coding assistant. One command to install, then use natural language to generate images, videos, and chat with LLMs.

Supported Clients

Claude Code

OpenAI Codex

Gemini CLI

Cursor

Windsurf

VS Code

Trae

GitHub Copilot

Cline

Roo Code

Amp

Goose

Replit

40+ supported clients

Install

npx skills add AtlasCloudAI/atlas-cloud-skills

Setup API Key

Get your API key from the Atlas Cloud dashboard and set it as an environment variable.

export ATLASCLOUD_API_KEY="your-api-key-here"

Capabilities

Once installed, you can use natural language in your AI assistant to access all Atlas Cloud models.

Image GenerationGenerate images with models like Nano Banana 2, Z-Image, and more.

Video CreationCreate videos from text or images with Kling, Vidu, Veo, etc.

LLM ChatChat with Qwen, DeepSeek, and other large language models.

Media UploadUpload local files for image editing and image-to-video workflows.

Learn more

github.com/AtlasCloudAI/atlas-cloud-skills

MCP Server

Atlas Cloud MCP Server connects your IDE with 400+ AI models via the Model Context Protocol. Works with any MCP-compatible client.

Supported Clients

Cursor

VS Code

Windsurf

Claude Code

OpenAI Codex

Gemini CLI

Cline

Roo Code

100+ supported clients

Install

npx -y atlascloud-mcp

Configuration

Add the following configuration to your IDE's MCP settings file.

{
  "mcpServers": {
    "atlascloud": {
      "command": "npx",
      "args": [
        "-y",
        "atlascloud-mcp"
      ],
      "env": {
        "ATLASCLOUD_API_KEY": "your-api-key-here"
      }
    }
  }
}

Available Tools

atlas_generate_imageGenerate images from text prompts.

atlas_generate_videoCreate videos from text or images.

atlas_chatChat with large language models.

atlas_list_modelsBrowse 400+ available AI models.

atlas_quick_generateOne-step content creation with auto model selection.

atlas_upload_mediaUpload local files for API workflows.

Learn more

github.com/AtlasCloudAI/mcp-server

API Schema

{
  "components": {
    "schemas": {
      "Input": {
        "properties": {
          "model": {
            "type": "string",
            "description": "model name",
            "default": "pixverse/c1/start-end-to-video"
          },
          "duration": {
            "default": 5,
            "description": "The duration of the generated media in seconds (1-15).",
            "enum": [
              1,
              2,
              3,
              4,
              5,
              6,
              7,
              8,
              9,
              10,
              11,
              12,
              13,
              14,
              15
            ],
            "type": "integer",
            "x-ui-component": "select"
          },
          "image": {
            "description": "First frame of the video; Notes: 1.Public URL or Base64. 2.Aspect ratios must be close: ratio between start/end frame must be in 0.8~1.25. 3.Format: png, jpeg, jpg, webp. 4.The post body of the HTTP request should not exceed 20MB",
            "type": "string",
            "x-ui-component": "uploaders"
          },
          "end_image": {
            "description": "Last frame of the video; Notes: 1.Public URL or Base64. 2.Aspect ratios must be close: ratio between start/end frame must be in 0.8~1.25. 3.Format: png, jpeg, jpg, webp. 4.The post body of the HTTP request should not exceed 20MB",
            "type": "string",
            "x-ui-component": "uploaders"
          },
          "prompt": {
            "description": "The positive prompt for the generation.",
            "type": "string",
            "maxLength": 5000,
            "minLength": 1
          },
          "sound": {
            "description": "Whether sound is generated simultaneously when generating a video.",
            "type": "boolean",
            "default": true
          },
          "quality": {
            "default": "720p",
            "description": "The resolution of the generated video.",
            "enum": [
              "360p",
              "540p",
              "720p",
              "1080p"
            ],
            "type": "string",
            "x-ui-component": "select"
          },
          "seed": {
            "description": "Random seed for reproducibility.",
            "type": "integer"
          }
        },
        "required": [
          "model",
          "prompt"
        ],
        "type": "object",
        "x-order-properties": [
          "model",
          "prompt",
          "image",
          "end_image",
          "duration",
          "quality",
          "sound",
          "seed"
        ]
      },
      "PredictionResponse": {
        "properties": {
          "created_at": {
            "description": "ISO timestamp of when the request was created.",
            "format": "date-time",
            "type": "string"
          },
          "has_nsfw_contents": {
            "description": "Array of boolean values indicating NSFW detection for each output.",
            "items": {
              "type": "boolean"
            },
            "type": "array"
          },
          "id": {
            "description": "Unique identifier for the prediction.",
            "type": "string"
          },
          "model": {
            "description": "Model ID used for the prediction.",
            "type": "string"
          },
          "outputs": {
            "description": "Array of URLs to the generated content.",
            "items": {
              "type": "string"
            },
            "type": "array"
          },
          "status": {
            "description": "Status of the task: created, processing, completed, or failed.",
            "type": "string"
          },
          "urls": {
            "description": "Object containing related API endpoints.",
            "type": "object"
          }
        },
        "type": "object"
      }
    },
    "securitySchemes": {
      "apiKeyAuth": {
        "in": "header",
        "name": "Authorization",
        "type": "apiKey"
      }
    }
  },
  "info": {
    "description": "The AtlasCloud API.",
    "title": "AtlasCloud API",
    "version": "1.0.0"
  },
  "openapi": "3.0.0",
  "paths": {
    "/api/v1/model/generateVideo": {
      "post": {
        "requestBody": {
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/Input"
              }
            }
          },
          "required": true
        },
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "The request status."
          }
        }
      },
      "x-api-name": "model_run"
    },
    "/api/v1/model/result/{request_id}": {
      "get": {
        "parameters": [
          {
            "in": "path",
            "name": "request_id",
            "required": true,
            "schema": {
              "description": "Request ID",
              "type": "string"
            }
          }
        ],
        "responses": {
          "200": {
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/PredictionResponse"
                }
              }
            },
            "description": "Result of the request."
          }
        }
      },
      "x-api-name": "model_result"
    }
  },
  "servers": [
    {
      "url": "https://api.atlascloud.ai"
    }
  ],
  "model": "pixverse/c1/start-end-to-video",
  "description": "PixVerse C1 Start-End-to-Video"
}

LLM-Friendly Prompt Template

# pixverse/c1/start-end-to-video

> Pixverse c1 Start-End-to-Video model. High-quality video generation from image prompts.


## Overview

- **Submit endpoint (POST)**: `https://api.atlascloud.ai/api/v1/model/generateVideo` — start an async generation; returns a `prediction_id`
- **Poll endpoint (GET)**: `https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}` — poll this until the prediction finishes
- **Model ID**: `pixverse/c1/start-end-to-video`


## 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:

- **`model`** (`string`, _required_):
  model name
  - Default: `"pixverse/c1/start-end-to-video"`

- **`prompt`** (`string`, _required_):
  The positive prompt for the generation.

- **`image`** (`string`, _optional_):
  First frame of the video; Notes: 1.Public URL or Base64. 2.Aspect ratios must be close: ratio between start/end frame must be in 0.8~1.25. 3.Format: png, jpeg, jpg, webp. 4.The post body of the HTTP request should not exceed 20MB

- **`end_image`** (`string`, _optional_):
  Last frame of the video; Notes: 1.Public URL or Base64. 2.Aspect ratios must be close: ratio between start/end frame must be in 0.8~1.25. 3.Format: png, jpeg, jpg, webp. 4.The post body of the HTTP request should not exceed 20MB

- **`duration`** (`integer`, _optional_):
  The duration of the generated media in seconds (1-15).
  - Default: `5`
  - Options: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15

- **`quality`** (`string`, _optional_):
  The resolution of the generated video.
  - Default: `"720p"`
  - Options: "360p", "540p", "720p", "1080p"

- **`sound`** (`boolean`, _optional_):
  Whether sound is generated simultaneously when generating a video.
  - Default: `true`

- **`seed`** (`integer`, _optional_):
  Random seed for reproducibility.



**Required Parameters Example**:

```json
{
  "model": "pixverse/c1/start-end-to-video",
  "prompt": ""
}
```


**Full Example**:

```json
{
  "model": "pixverse/c1/start-end-to-video",
  "prompt": "",
  "image": "",
  "end_image": "",
  "duration": 5,
  "quality": "720p",
  "sound": true,
  "seed": 0
}
```


### Output Schema

The API returns the following output format:


- **`created_at`** (`string`, _optional_):
  ISO timestamp of when the request was created.

- **`has_nsfw_contents`** (`array[boolean]`, _optional_):
  Array of boolean values indicating NSFW detection for each output.

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`outputs`** (`array[string]`, _optional_):
  Array of URLs to the generated content.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example Response**:

```json
{
  "created_at": "",
  "has_nsfw_contents": [],
  "id": "",
  "model": "",
  "outputs": [
    ""
  ],
  "status": "",
  "urls": {}
}
```


## Usage Examples

### cURL

```bash
# Step 1: Start generation (async)
curl -X POST "https://api.atlascloud.ai/api/v1/model/generateVideo" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "pixverse/c1/start-end-to-video",
  "prompt": "",
  "image": "",
  "end_image": "",
  "duration": 5,
  "quality": "720p",
  "sound": true,
  "seed": 0
}'

# Response will contain: {"code": 200, "data": {"id": "prediction_id", "status": "processing"}}

# Step 2: Poll for result (replace {prediction_id} with the id returned above)
curl -X GET "https://api.atlascloud.ai/api/v1/model/prediction/{prediction_id}" \
  -H "Authorization: Bearer $ATLASCLOUD_API_KEY"

# Keep polling until status is "completed", "succeeded" or "failed"
# When completed, outputs will contain the generated content URL(s)
```

## Additional Resources

### Documentation

- [Model Playground](https://www.atlascloud.ai/models/pixverse/c1/start-end-to-video)

The device on the wrist activates, and a protective film gradually spreads to cover the back of the hand.

PixVerse C1 Start-End-to-Video

PixVerse C1 Start-End-to-Video gives you precise control over video generation by letting you define both the first and last frames. Upload a start image and an end image, describe the transition, and the model generates a smooth cinematic video connecting the two frames.

Why Choose This?

Full frame control Define exactly where the video starts and ends.
Smooth transitions Generate natural, fluid motion between two keyframes.
High resolution output Generate videos in 360p, 540p, 720p, or 1080p quality.
Flexible duration Create videos from 1 to 15 seconds in length.
Audio generation Optional synchronized audio that matches your scene.

Parameters

Parameter	Required	Description
prompt	Yes	Text description of the desired motion and transition
image	Yes	Starting frame (from image upload API)
end_image	Yes	Ending frame (from image upload API)
model	Yes	Model name (default: c1)
duration	No	Video length in seconds (1-15, default: 5)
quality	No	Output resolution: 360p, 540p, 720p (default), 1080p
sound	No	Generate synchronized audio (default: enabled)
seed	No	Random seed for reproducibility

How to Use

Upload start image — call the image upload API to get the start frame.
Upload end image — call the image upload API to get the end frame.
Write your prompt — describe the motion and transition between the two frames.
Set quality — choose resolution based on your quality and speed requirements.
Adjust duration — set video length up to 15 seconds.
Configure audio (optional) — enable or disable synchronized audio generation.
Run — submit and download your video.

Best Use Cases

Controlled Transitions — Create precise scene transitions between two specific moments.
Product Showcases — Animate between product states (before/after, open/closed).
Story Sequences — Connect two story moments with smooth animation.
Camera Movements — Define start and end compositions for cinematic shots.
Visual Effects — Generate transformation effects between two states.

Pro Tips

Describe intermediate motion explicitly in the prompt (e.g., "the door slowly swings open").
Use images with matching lighting conditions for natural-looking transitions.
Keep duration proportional to the complexity of the motion between frames.
Upload both images via the upload API before submitting the generation request.

Pricing

Quality	Billing Standard	Without Audio	With Audio
360p	per second	$0.030	$0.040
540p	per second	$0.040	$0.050
720p	per second	$0.050	$0.065
1080p	per second	$0.095	$0.120

Notes

prompt, image, and end_image are all required fields.
Both start and end images must be uploaded via the upload API first.
Supported image formats: PNG, JPEG, JPG, WebP (max 10MB).
Maximum video duration is 15 seconds.

PixVerse C1 Image-to-Video — Animate a single reference image.
PixVerse C1 Text-to-Video — Generate video directly from text descriptions.

VEED Lipsync

VEED Lipsync re-drives the lip movements of an existing talking-head video to match a new audio track, preserving identity, appearance and background.

LIP-SYNC

From

$0.013/SEC