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reference script
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#!/bin/bash
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OUTPUT_DIR="inference/output_2/final_output"
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POSE_FRAME_DIR="inference/output_2/poses"
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STARTING_IMAGE="inference/output_1/frames/frame_0.png"
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#mkdir -p $OUTPUT_DIR
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#CUDA_VISIBLE_DEVICES=0
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python inference_advanced.py \
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--start_image_path="${STARTING_IMAGE}" \
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--output_dir="${OUTPUT_DIR}" \
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--pose_images_folder="/tmp/pose" \
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--pre_pose_video_path="inference/zeihan_trimmed.mp4" \
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--width=1024 \
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--height=576 \
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--pretrained_model_name_or_path="checkpoints/stable-video-diffusion-img2vid-xt" \
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--posenet_model_name_or_path="checkpoints/Animation/pose_net.pth" \
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--face_encoder_model_name_or_path="checkpoints/Animation/face_encoder.pth" \
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--unet_model_name_or_path="checkpoints/Animation/unet.pth" \
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--guidance_scale=3.0 \
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--num_inference_steps=25 \
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--tile_size=16 \
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--overlap=4 \
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--noise_aug_strength=0.02 \
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--frames_overlap=4 \
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--decode_chunk_size=4 \
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--gradient_checkpointing
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#ffmpeg -framerate 30 \
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# -start_number 0 \
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# -i "${OUTPUT_DIR}/animated_images/frame_%d.png" \
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# -c:v libx264 -pix_fmt yuv420p "${OUTPUT_DIR}/out.mp4" -y
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