SkyReels V1
Playground
Try it on WavespeedAI!SkyReels V1 is the first and most advanced open-source human-centric video foundation model. By fine-tuning HunyuanVideo on O(10M) high-quality film and television clips.
Features
SkyReels V1: Human-Centric Video Foundation Model
🌟 Overview
SkyReels V1 is the first and most advanced open-source human-centric video foundation model. By fine-tuning HunyuanVideo on O(10M) high-quality film and television clips, SkyReels V1 offers three key advantages:
- Open-Source Leadership: Our Text-to-Video model achieves state-of-the-art (SOTA) performance among open-source models, comparable to proprietary models like Kling and Hailuo.
- Advanced Facial Animation: Captures 33 distinct facial expressions with over 400 natural movement combinations, accurately reflecting human emotions.
- Cinematic Lighting and Aesthetics: Trained on high-quality Hollywood-level film and television data, each generated frame exhibits cinematic quality in composition, actor positioning, and camera angles.
🔑 Key Features
1. Self-Developed Data Cleaning and Annotation Pipeline
Our model is built on a self-developed data cleaning and annotation pipeline, creating a vast dataset of high-quality film, television, and documentary content.
- Expression Classification: Categorizes human facial expressions into 33 distinct types.
- Character Spatial Awareness: Utilizes 3D human reconstruction technology to understand spatial relationships between multiple people in a video, enabling film-level character positioning.
- Action Recognition: Constructs over 400 action semantic units to achieve a precise understanding of human actions.
- Scene Understanding: Conducts cross-modal correlation analysis of clothing, scenes, and plots.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/SkyReels-V1" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"prompt": "Camera tracking shot of the woman driving the red convertible along a cliffside road, her hair flowing in the wind, ocean reflecting sunlight",
"image": "https://d3gnftk2yhz9lr.wavespeed.ai/media/images/1745145676350203025_T0lFAytr.jpg",
"guidance_scale": 6,
"num_inference_steps": 30,
"aspect_ratio": "16:9"
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
Parameter | Type | Required | Default | Range | Description |
---|---|---|---|---|---|
prompt | string | Yes | - | The prompt to generate the video from. | |
image | string | Yes | - | URL of the image input. | |
seed | integer | No | - | -1 ~ 2147483647 | The random seed to use for the generation. |
guidance_scale | number | No | 6 | 1 ~ 20 | The guidance scale to use for the generation. |
num_inference_steps | integer | No | 30 | 1 ~ 50 | The number of inference steps to perform. |
negative_prompt | string | No | - | Negative prompt to guide generation away from certain attributes. | |
aspect_ratio | string | No | 16:9 | - | Aspect ratio of the output video. |
Response Parameters
Parameter | Type | Description |
---|---|---|
code | integer | HTTP status code (e.g., 200 for success) |
message | string | Status message (e.g., “success”) |
data.id | string | Unique identifier for the prediction, Task Id |
data.model | string | Model ID used for the prediction |
data.outputs | array | Array of URLs to the generated content (empty when status is not completed ) |
data.urls | object | Object containing related API endpoints |
data.urls.get | string | URL to retrieve the prediction result |
data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
data.status | string | Status of the task: created , processing , completed , or failed |
data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
data.error | string | Error message (empty if no error occurred) |
data.timings | object | Object containing timing details |
data.timings.inference | integer | Inference time in milliseconds |
Result Query Parameters
Result Request Parameters
Parameter | Type | Required | Default | Description |
---|---|---|---|---|
id | string | Yes | - | Task ID |
Result Response Parameters
Parameter | Type | Description |
---|---|---|
code | integer | HTTP status code (e.g., 200 for success) |
message | string | Status message (e.g., “success”) |
data | object | The prediction data object containing all details |
data.id | string | Unique identifier for the prediction, the ID of the prediction to get |
data.model | string | Model ID used for the prediction |
data.outputs | array | Array of URLs to the generated content (empty when status is not completed ) |
data.urls | object | Object containing related API endpoints |
data.urls.get | string | URL to retrieve the prediction result |
data.has_nsfw_contents | array | Array of boolean values indicating NSFW detection for each output |
data.status | string | Status of the task: created , processing , completed , or failed |
data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
data.error | string | Error message (empty if no error occurred) |
data.timings | object | Object containing timing details |
data.timings.inference | integer | Inference time in milliseconds |