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Running
on
Zero
File size: 5,185 Bytes
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import os, torch, json
from .sd_video import ModelManager, SDVideoPipeline, ControlNetConfigUnit
from ..processors.sequencial_processor import SequencialProcessor
from ..data import VideoData, save_frames, save_video
class SDVideoPipelineRunner:
def __init__(self, in_streamlit=False):
self.in_streamlit = in_streamlit
def load_pipeline(self, model_list, textual_inversion_folder, device, lora_alphas, controlnet_units):
# Load models
model_manager = ModelManager(torch_dtype=torch.float16, device=device)
model_manager.load_models(model_list)
pipe = SDVideoPipeline.from_model_manager(
model_manager,
[
ControlNetConfigUnit(
processor_id=unit["processor_id"],
model_path=unit["model_path"],
scale=unit["scale"]
) for unit in controlnet_units
]
)
textual_inversion_paths = []
for file_name in os.listdir(textual_inversion_folder):
if file_name.endswith(".pt") or file_name.endswith(".bin") or file_name.endswith(".pth") or file_name.endswith(".safetensors"):
textual_inversion_paths.append(os.path.join(textual_inversion_folder, file_name))
pipe.prompter.load_textual_inversions(textual_inversion_paths)
return model_manager, pipe
def load_smoother(self, model_manager, smoother_configs):
smoother = SequencialProcessor.from_model_manager(model_manager, smoother_configs)
return smoother
def synthesize_video(self, model_manager, pipe, seed, smoother, **pipeline_inputs):
torch.manual_seed(seed)
if self.in_streamlit:
import streamlit as st
progress_bar_st = st.progress(0.0)
output_video = pipe(**pipeline_inputs, smoother=smoother, progress_bar_st=progress_bar_st)
progress_bar_st.progress(1.0)
else:
output_video = pipe(**pipeline_inputs, smoother=smoother)
model_manager.to("cpu")
return output_video
def load_video(self, video_file, image_folder, height, width, start_frame_id, end_frame_id):
video = VideoData(video_file=video_file, image_folder=image_folder, height=height, width=width)
if start_frame_id is None:
start_frame_id = 0
if end_frame_id is None:
end_frame_id = len(video)
frames = [video[i] for i in range(start_frame_id, end_frame_id)]
return frames
def add_data_to_pipeline_inputs(self, data, pipeline_inputs):
pipeline_inputs["input_frames"] = self.load_video(**data["input_frames"])
pipeline_inputs["num_frames"] = len(pipeline_inputs["input_frames"])
pipeline_inputs["width"], pipeline_inputs["height"] = pipeline_inputs["input_frames"][0].size
if len(data["controlnet_frames"]) > 0:
pipeline_inputs["controlnet_frames"] = [self.load_video(**unit) for unit in data["controlnet_frames"]]
return pipeline_inputs
def save_output(self, video, output_folder, fps, config):
os.makedirs(output_folder, exist_ok=True)
save_frames(video, os.path.join(output_folder, "frames"))
save_video(video, os.path.join(output_folder, "video.mp4"), fps=fps)
config["pipeline"]["pipeline_inputs"]["input_frames"] = []
config["pipeline"]["pipeline_inputs"]["controlnet_frames"] = []
with open(os.path.join(output_folder, "config.json"), 'w') as file:
json.dump(config, file, indent=4)
def run(self, config):
if self.in_streamlit:
import streamlit as st
if self.in_streamlit: st.markdown("Loading videos ...")
config["pipeline"]["pipeline_inputs"] = self.add_data_to_pipeline_inputs(config["data"], config["pipeline"]["pipeline_inputs"])
if self.in_streamlit: st.markdown("Loading videos ... done!")
if self.in_streamlit: st.markdown("Loading models ...")
model_manager, pipe = self.load_pipeline(**config["models"])
if self.in_streamlit: st.markdown("Loading models ... done!")
if "smoother_configs" in config:
if self.in_streamlit: st.markdown("Loading smoother ...")
smoother = self.load_smoother(model_manager, config["smoother_configs"])
if self.in_streamlit: st.markdown("Loading smoother ... done!")
else:
smoother = None
if self.in_streamlit: st.markdown("Synthesizing videos ...")
output_video = self.synthesize_video(model_manager, pipe, config["pipeline"]["seed"], smoother, **config["pipeline"]["pipeline_inputs"])
if self.in_streamlit: st.markdown("Synthesizing videos ... done!")
if self.in_streamlit: st.markdown("Saving videos ...")
self.save_output(output_video, config["data"]["output_folder"], config["data"]["fps"], config)
if self.in_streamlit: st.markdown("Saving videos ... done!")
if self.in_streamlit: st.markdown("Finished!")
video_file = open(os.path.join(os.path.join(config["data"]["output_folder"], "video.mp4")), 'rb')
if self.in_streamlit: st.video(video_file.read())
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