使用EasyAnimate生成视频

WebUI方式

1. 在服务详情页面，单击查看WEB应用。

   

2. 在WebUI界面选择预训练的模型路径，其它参数按需配置即可。

   

3. 单击Generate（生成），等待大约5分钟后，即可在右侧查看或下载生成的视频。

   

API方式

1. 在服务详情页面的资源详情区域，单击查看调用信息，获取调用服务所需的信息。

   

2. 通过接口更新Transformer模型，可在DSW实例或本地Python环境中执行。

   如果已经在WebUI中选择模型，则无需发送请求重复调用。如遇请求超时，请在EAS日志中确认模型已加载完毕。加载完成，日志中将提示Update diffusion transformer done。

   Python请求示例如下。

   import json
   import requests
   
   
   def post_diffusion_transformer(diffusion_transformer_path, url='http://127.0.0.1:7860', token=None):
       datas = json.dumps({
           "diffusion_transformer_path": diffusion_transformer_path
       })
       head = {
           'Authorization': token
       }
       r = requests.post(f'{url}/easyanimate/update_diffusion_transformer', data=datas, headers=head, timeout=15000)
       data = r.content.decode('utf-8')
       return data
   
   def post_update_edition(edition, url='http://0.0.0.0:7860',token=None):
       head = {
           'Authorization': token
       }
   
       datas = json.dumps({
           "edition": edition
       })
       r = requests.post(f'{url}/easyanimate/update_edition', data=datas, headers=head)
       data = r.content.decode('utf-8')
       return data
     
   if __name__ == '__main__':
       url = '<eas-service-url>'
       token = '<eas-service-token>'
   
       # -------------------------- #
       #  Step 1: update edition
       # -------------------------- #
       edition = "v3"
       outputs = post_update_edition(edition,url = url,token=token)
       print('Output update edition: ', outputs)
   
       # -------------------------- #
       #  Step 2: update edition
       # -------------------------- #
       # 默认路径 (二选一)
       diffusion_transformer_path = "/mnt/models/Diffusion_Transformer/EasyAnimateV3-XL-2-InP-512x512"
       # diffusion_transformer_path = "/mnt/models/Diffusion_Transformer/EasyAnimateV3-XL-2-InP-768x768"
       outputs = post_diffusion_transformer(diffusion_transformer_path, url = url, token=token)
       print('Output update edition: ', outputs)

   其中：

   • <eas-service-url>：替换为步骤a中查询到的服务访问地址。

   • <eas-service-token>：替换为步骤a中查询到的服务Token。

3. 调用服务，生成视频或图片。

• 服务输入参数说明

  参数名	说明	类型	默认值
  prompt_textbox	用户输入的正向提示词。	string	必填。无默认值
  negative_prompt_textbox	用户输入的负向提示词。	string	"The video is not of a high quality, it has a low resolution, and the audio quality is not clear. Strange motion trajectory, a poor composition and deformed video, low resolution, duplicate and ugly, strange body structure, long and strange neck, bad teeth, bad eyes, bad limbs, bad hands, rotating camera, blurry camera, shaking camera. Deformation, low-resolution, blurry, ugly, distortion."
  sample_step_slider	用户输入的步数。	int	30
  cfg_scale_slider	引导系数。	int	6
  sampler_dropdown	采样器类型。 取值包括：Eluer、EluerA、DPM++、PNDM、DDIM	string	Eluer
  width_slider	生成视频宽度。	int	672
  height_slider	生成视频高度。	int	384
  length_slider	生成视频帧数。	int	144
  is_image	是否是图片。	bool	FALSE
  lora_alpha_slider	LoRA模型参数的权重。	float	0.55
  seed_textbox	随机种子。	int	43
  lora_model_path	额外的LoRA模型路径。 若有，则会在请求时带上lora。在当次请求后移除。	string	none
  base_model_path	需要更新的transformer模型路径。	string	none
  motion_module_path	需要更新的motion_module模型路径。	string	none
  generation_method	生成类型。包括：Video Generation，Image Generation	string	none

• Python请求示例

  服务返回base64_encoding，为base64结果。

  您可以在/mnt/workspace/demos/easyanimate/目录中查看生成结果。

  import base64
  import json
  import sys
  import time
  from datetime import datetime
  from io import BytesIO
  
  import cv2
  import requests
  import base64
  
  def post_infer(generation_method, length_slider, url='http://127.0.0.1:7860',token=None):
      head = {
          'Authorization': token
      }
  
      datas = json.dumps({
          "base_model_path": "none",
          "motion_module_path": "none",
          "lora_model_path": "none", 
          "lora_alpha_slider": 0.55, 
          "prompt_textbox": "This video shows Mount saint helens, washington - the stunning scenery of a rocky mountains during golden hours - wide shot. A soaring drone footage captures the majestic beauty of a coastal cliff, its red and yellow stratified rock faces rich in color and against the vibrant turquoise of the sea.", 
          "negative_prompt_textbox": "Strange motion trajectory, a poor composition and deformed video, worst quality, normal quality, low quality, low resolution, duplicate and ugly, strange body structure, long and strange neck, bad teeth, bad eyes, bad limbs, bad hands, rotating camera, blurry camera, shaking camera", 
          "sampler_dropdown": "Euler", 
          "sample_step_slider": 30, 
          "width_slider": 672, 
          "height_slider": 384, 
          "generation_method": "Video Generation",
          "length_slider": length_slider,
          "cfg_scale_slider": 6,
          "seed_textbox": 43,
      })
      r = requests.post(f'{url}/easyanimate/infer_forward', data=datas, headers=head, timeout=1500)
      data = r.content.decode('utf-8')
      return data
  
  
  if __name__ == '__main__':
      # initiate time
      now_date    = datetime.now()
      time_start  = time.time()  
      
      url = '<eas-service-url>'
      token = '<eas-service-token>'
  
      # -------------------------- #
      #  Step 3: infer
      # -------------------------- #
      # "Video Generation" and "Image Generation"
      generation_method = "Video Generation"
      length_slider = 72
      outputs = post_infer(generation_method, length_slider, url = url, token=token)
      
      # Get decoded data
      outputs = json.loads(outputs)
      base64_encoding = outputs["base64_encoding"]
      decoded_data = base64.b64decode(base64_encoding)
  
      is_image = True if generation_method == "Image Generation" else False
      if is_image or length_slider == 1:
          file_path = "1.png"
      else:
          file_path = "1.mp4"
      with open(file_path, "wb") as file:
          file.write(decoded_data)
          
      # End of record time
      # The calculated time difference is the execution time of the program, expressed in seconds / s
      time_end = time.time()  
      time_sum = (time_end - time_start) % 60 
      print('# --------------------------------------------------------- #')
      print(f'#   Total expenditure: {time_sum}s')
      print('# --------------------------------------------------------- #')

  其中：

  • <eas-service-url>：替换为步骤a中查询到的服务访问地址。

  • <eas-service-token>：替换为步骤a中查询到的服务Token。