Platform For AI：Hasilkan video panjang definisi tinggi menggunakan EasyAnimate

Di halaman Service Details, klik View Web App.

Di WebUI, pilih jalur model pra-latih. Konfigurasikan parameter lain sesuai kebutuhan.

Klik Generate. Setelah sekitar 5 menit, Anda dapat melihat atau mengunduh video yang dihasilkan di sisi kanan halaman.

Untuk mendapatkan URL layanan dan token, di halaman Service Details , di bagian Call Information , klik View Call Information.

Panggil layanan untuk menghasilkan video. Berikut adalah contoh permintaan Python:

import os
import requests
import json
import base64
from typing import Dict, Any


class EasyAnimateClient:
    """
    EasyAnimate EAS Service API Client.
    """

    def __init__(self, service_url: str, token: str):
        if not service_url or not token:
            raise ValueError("The service URL (service_url) and token cannot be empty")
        self.base_url = service_url.rstrip('/')
        self.headers = {
            'Content-Type': 'application/json',
            'Authorization': token
        }

    def update_model(self, model_path: str, edition: str = "v3", timeout: int = 300) -> Dict[str, Any]:
        """
        Updates and loads the specified model version and path.

        Args:
            model_path: The path of the model within the service, such as "/mnt/models/Diffusion_Transformer/EasyAnimateV3-XL-2-InP-512x512".
            edition: The model edition. Default value: "v3".
            timeout: The request timeout period in seconds. Model loading is slow, so we recommend that you set a long timeout period.
        """
        # 1. Update the edition.
        requests.post(
            f"{self.base_url}/easyanimate/update_edition",
            headers=self.headers,
            json={"edition": edition},
            timeout=timeout
        ).raise_for_status()

        # 2. Update the model path and wait for the model to load.
        print(f"Sending a request to load the model: {model_path}")
        response = requests.post(
            f"{self.base_url}/easyanimate/update_diffusion_transformer",
            headers=self.headers,
            json={"diffusion_transformer_path": model_path},
            timeout=15000
        )
        response.raise_for_status()
        return response.json()

    def generate_video(self, prompt_textbox: str, **kwargs) -> bytes:
        """
        Generates a video based on the prompt.

        Args:
            prompt: The English positive prompt.
            **kwargs: Other optional parameters. For more information, see the parameter description table below.

        Returns:
            The binary data of the video in MP4 format.
        """
        payload = {
            "prompt_textbox": prompt_textbox,
            "negative_prompt_textbox": kwargs.get("negative_prompt",
                                                  "The video is not of a high quality, it has a low resolution..."),
            "width_slider": kwargs.get("width_slider", 672),
            "height_slider": kwargs.get("height_slider", 384),
            "length_slider": kwargs.get("length_slider", 144),
            "sample_step_slider": kwargs.get("sample_step_slider", 30),
            "cfg_scale_slider": kwargs.get("cfg_scale_slider", 6.0),
            "seed_textbox": kwargs.get("seed_textbox", 43),
            "sampler_dropdown": kwargs.get("sampler_dropdown", "Euler"),
            "generation_method": "Video Generation",
            "is_image": False,
            "lora_alpha_slider": 0.55,
            "lora_model_path": "none",
            "base_model_path": "none",
            "motion_module_path": "none"
        }

        response = requests.post(
            f"{self.base_url}/easyanimate/infer_forward",
            headers=self.headers,
            json=payload,
            timeout=1500
        )
        response.raise_for_status()

        result = response.json()
        if "base64_encoding" not in result:
            raise ValueError(f"Invalid API return format: {result}")

        return base64.b64decode(result["base64_encoding"])


# --- Example ---
if __name__ == "__main__":
    try:
        # 1. Configure service information. Replace the placeholders with the actual service endpoint and token. We recommend that you set them as environment variables.
        EAS_URL = "<eas-service-url>"
        EAS_TOKEN = "<eas-service-token>"

        # 2. Create a client.
        client = EasyAnimateClient(service_url=EAS_URL, token=EAS_TOKEN)

        # 3. Load the model. After the service is deployed, no model is loaded by default. Before you send a generation request, you must call update_model at least once to specify the model to use. To switch to a different model later, call this method again.
        client.update_model(model_path="/mnt/models/Diffusion_Transformer/EasyAnimateV3-XL-2-InP-512x512")

        # 4. Generate a video.
        video_bytes = client.generate_video(
            prompt_textbox="A beautiful cat playing in a sunny garden, high quality, detailed",
            width_slider=672,
            height_slider=384,
            length_slider=72,
            sample_step_slider=20
        )

        # 5. Save the video file.
        with open("api_generated_video.mp4", "wb") as f:
            f.write(video_bytes)
        print("The video is saved as api_generated_video.mp4.")

    except requests.RequestException as e:
        print(f"Network request error: {e}")
    except (ValueError, KeyError) as e:
        print(f"Data or parameter error: {e}")
    except Exception as e:
        print(f"An unknown error occurred: {e}")

Tabel berikut menjelaskan parameter input antarmuka layanan.