Bubbliiiingandzouxinyi0625
fb0916f4da
* update EasyAnimateV2 * update datasets loader * update datasets loader * update fast api * complete data preprocess pipeline. * update lots of readme * update readme bans * fix bug in validation while training * provide example for video cut * update text box * add arxiv * delete IDDPM * update gallery * update arxiv * update readme * update readme * link fix * update vae readme --------- Co-authored-by: zouxinyi0625 <zouxinyi.zxy@alibaba-inc.com>
96 lines
3.3 KiB
Python
96 lines
3.3 KiB
Python
import io
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import base64
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import torch
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import gradio as gr
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from fastapi import FastAPI
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from io import BytesIO
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# Function to encode a file to Base64
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def encode_file_to_base64(file_path):
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with open(file_path, "rb") as file:
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# Encode the data to Base64
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file_base64 = base64.b64encode(file.read())
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return file_base64
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def update_edition_api(_: gr.Blocks, app: FastAPI, controller):
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@app.post("/easyanimate/update_edition")
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def _update_edition_api(
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datas: dict,
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):
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edition = datas.get('edition', 'v2')
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try:
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controller.update_edition(
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edition
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)
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comment = "Success"
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except Exception as e:
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torch.cuda.empty_cache()
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comment = f"Error. error information is {str(e)}"
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return {"message": comment}
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def update_diffusion_transformer_api(_: gr.Blocks, app: FastAPI, controller):
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@app.post("/easyanimate/update_diffusion_transformer")
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def _update_diffusion_transformer_api(
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datas: dict,
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):
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diffusion_transformer_path = datas.get('diffusion_transformer_path', 'none')
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try:
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controller.update_diffusion_transformer(
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diffusion_transformer_path
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)
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comment = "Success"
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except Exception as e:
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torch.cuda.empty_cache()
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comment = f"Error. error information is {str(e)}"
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return {"message": comment}
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def infer_forward_api(_: gr.Blocks, app: FastAPI, controller):
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@app.post("/easyanimate/infer_forward")
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def _infer_forward_api(
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datas: dict,
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):
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base_model_path = datas.get('base_model_path', 'none')
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motion_module_path = datas.get('motion_module_path', 'none')
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lora_model_path = datas.get('lora_model_path', 'none')
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lora_alpha_slider = datas.get('lora_alpha_slider', 0.55)
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prompt_textbox = datas.get('prompt_textbox', None)
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negative_prompt_textbox = datas.get('negative_prompt_textbox', '')
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sampler_dropdown = datas.get('sampler_dropdown', 'Euler')
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sample_step_slider = datas.get('sample_step_slider', 30)
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width_slider = datas.get('width_slider', 672)
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height_slider = datas.get('height_slider', 384)
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is_image = datas.get('is_image', False)
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length_slider = datas.get('length_slider', 144)
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cfg_scale_slider = datas.get('cfg_scale_slider', 6)
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seed_textbox = datas.get("seed_textbox", 43)
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try:
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save_sample_path, comment = controller.generate(
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"",
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base_model_path,
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motion_module_path,
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lora_model_path,
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lora_alpha_slider,
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prompt_textbox,
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negative_prompt_textbox,
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sampler_dropdown,
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sample_step_slider,
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width_slider,
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height_slider,
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is_image,
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length_slider,
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cfg_scale_slider,
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seed_textbox,
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is_api = True,
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)
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except Exception as e:
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torch.cuda.empty_cache()
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save_sample_path = ""
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comment = f"Error. error information is {str(e)}"
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return {"message": comment, "save_sample_path": save_sample_path, "base64_encoding": encode_file_to_base64(save_sample_path)} |