Isi-dev-ComfyUI-UniAnimate-W/Animate_X.ipynb at 8cb4ac3cad41ceda67a338e63df97745d78bbbd2

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Yo can now run animate-x on google colab

2025-02-10 17:23:14 +01:00

674 KiB

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Prepare Environment & Download Models

In [ ]:

# @title

!pip install torch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 numpy opencv-python==4.9.0.80 pillow tqdm

!pip install -r https://raw.githubusercontent.com/Isi-dev/animate-x/main/requirements.txt

!pip install onnxruntime-gpu

!pip install pynvml
!pip install kornia


!git clone https://github.com/Isi-dev/animate-x.git
%cd animate-x


!mkdir -p checkpoints

# Download DWPose models
!wget -O checkpoints/dw-ll_ucoco_384.onnx "https://huggingface.co/Isi99999/UniAnimate_and_Animate-X_Models/resolve/main/dw-ll_ucoco_384.onnx"
!wget -O checkpoints/yolox_l.onnx "https://huggingface.co/Isi99999/UniAnimate_and_Animate-X_Models/resolve/main/yolox_l.onnx"

# Download Animate-X, Embedder & AutoEncoder models
!wget -O checkpoints/animate-x_ckpt.pth "https://huggingface.co/Isi99999/UniAnimate_and_Animate-X_Models/resolve/main/animate-x_ckpt.pth"
!wget -O checkpoints/open_clip_pytorch_model.bin "https://huggingface.co/Isi99999/UniAnimate_and_Animate-X_Models/resolve/main/open_clip_pytorch_model.bin"
!wget -O checkpoints/v2-1_512-ema-pruned.ckpt "https://huggingface.co/Isi99999/UniAnimate_and_Animate-X_Models/resolve/main/v2-1_512-ema-pruned.ckpt"

print("✅ All models are ready!")

Collecting torch==2.3.1
  Downloading torch-2.3.1-cp311-cp311-manylinux1_x86_64.whl.metadata (26 kB)
Collecting torchvision==0.18.1
  Downloading torchvision-0.18.1-cp311-cp311-manylinux1_x86_64.whl.metadata (6.6 kB)
Collecting torchaudio==2.3.1
  Downloading torchaudio-2.3.1-cp311-cp311-manylinux1_x86_64.whl.metadata (6.4 kB)
Requirement already satisfied: numpy in /usr/local/lib/python3.11/dist-packages (1.26.4)
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  Downloading opencv_python-4.9.0.80-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (20 kB)
Requirement already satisfied: pillow in /usr/local/lib/python3.11/dist-packages (11.1.0)
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Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch==2.3.1)
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  Downloading nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)
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[?25hInstalling collected packages: triton, opencv-python, nvidia-nvtx-cu12, nvidia-nccl-cu12, nvidia-cusparse-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusolver-cu12, nvidia-cudnn-cu12, torch, torchvision, torchaudio
  Attempting uninstall: triton
    Found existing installation: triton 3.1.0
    Uninstalling triton-3.1.0:
      Successfully uninstalled triton-3.1.0
  Attempting uninstall: opencv-python
    Found existing installation: opencv-python 4.11.0.86
    Uninstalling opencv-python-4.11.0.86:
      Successfully uninstalled opencv-python-4.11.0.86
  Attempting uninstall: nvidia-nvtx-cu12
    Found existing installation: nvidia-nvtx-cu12 12.4.127
    Uninstalling nvidia-nvtx-cu12-12.4.127:
      Successfully uninstalled nvidia-nvtx-cu12-12.4.127
  Attempting uninstall: nvidia-nccl-cu12
    Found existing installation: nvidia-nccl-cu12 2.21.5
    Uninstalling nvidia-nccl-cu12-2.21.5:
      Successfully uninstalled nvidia-nccl-cu12-2.21.5
  Attempting uninstall: nvidia-cusparse-cu12
    Found existing installation: nvidia-cusparse-cu12 12.5.1.3
    Uninstalling nvidia-cusparse-cu12-12.5.1.3:
      Successfully uninstalled nvidia-cusparse-cu12-12.5.1.3
  Attempting uninstall: nvidia-curand-cu12
    Found existing installation: nvidia-curand-cu12 10.3.6.82
    Uninstalling nvidia-curand-cu12-10.3.6.82:
      Successfully uninstalled nvidia-curand-cu12-10.3.6.82
  Attempting uninstall: nvidia-cufft-cu12
    Found existing installation: nvidia-cufft-cu12 11.2.3.61
    Uninstalling nvidia-cufft-cu12-11.2.3.61:
      Successfully uninstalled nvidia-cufft-cu12-11.2.3.61
  Attempting uninstall: nvidia-cuda-runtime-cu12
    Found existing installation: nvidia-cuda-runtime-cu12 12.5.82
    Uninstalling nvidia-cuda-runtime-cu12-12.5.82:
      Successfully uninstalled nvidia-cuda-runtime-cu12-12.5.82
  Attempting uninstall: nvidia-cuda-nvrtc-cu12
    Found existing installation: nvidia-cuda-nvrtc-cu12 12.5.82
    Uninstalling nvidia-cuda-nvrtc-cu12-12.5.82:
      Successfully uninstalled nvidia-cuda-nvrtc-cu12-12.5.82
  Attempting uninstall: nvidia-cuda-cupti-cu12
    Found existing installation: nvidia-cuda-cupti-cu12 12.5.82
    Uninstalling nvidia-cuda-cupti-cu12-12.5.82:
      Successfully uninstalled nvidia-cuda-cupti-cu12-12.5.82
  Attempting uninstall: nvidia-cublas-cu12
    Found existing installation: nvidia-cublas-cu12 12.5.3.2
    Uninstalling nvidia-cublas-cu12-12.5.3.2:
      Successfully uninstalled nvidia-cublas-cu12-12.5.3.2
  Attempting uninstall: nvidia-cusolver-cu12
    Found existing installation: nvidia-cusolver-cu12 11.6.3.83
    Uninstalling nvidia-cusolver-cu12-11.6.3.83:
      Successfully uninstalled nvidia-cusolver-cu12-11.6.3.83
  Attempting uninstall: nvidia-cudnn-cu12
    Found existing installation: nvidia-cudnn-cu12 9.3.0.75
    Uninstalling nvidia-cudnn-cu12-9.3.0.75:
      Successfully uninstalled nvidia-cudnn-cu12-9.3.0.75
  Attempting uninstall: torch
    Found existing installation: torch 2.5.1+cu124
    Uninstalling torch-2.5.1+cu124:
      Successfully uninstalled torch-2.5.1+cu124
  Attempting uninstall: torchvision
    Found existing installation: torchvision 0.20.1+cu124
    Uninstalling torchvision-0.20.1+cu124:
      Successfully uninstalled torchvision-0.20.1+cu124
  Attempting uninstall: torchaudio
    Found existing installation: torchaudio 2.5.1+cu124
    Uninstalling torchaudio-2.5.1+cu124:
      Successfully uninstalled torchaudio-2.5.1+cu124
Successfully installed nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvtx-cu12-12.1.105 opencv-python-4.9.0.80 torch-2.3.1 torchaudio-2.3.1 torchvision-0.18.1 triton-2.3.1
Collecting rotary-embedding-torch==0.5.3 (from -r https://raw.githubusercontent.com/Isi-dev/animate-x/main/requirements.txt (line 2))
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[?25h  Installing build dependencies ... [?25l[?25hdone
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--2025-02-10 14:55:57--  https://huggingface.co/Isi99999/UniAnimate_and_Animate-X_Models/resolve/main/animate-x_ckpt.pth
Resolving huggingface.co (huggingface.co)... 13.35.202.121, 13.35.202.34, 13.35.202.97, ...
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Location: https://cdn-lfs-us-1.hf.co/repos/bd/61/bd61bc81127dde17d80e0681845855b3d0000efc2ec5c9a2efd7e46ddf53aeae/e3bfb656bafe603132a28f43f758c6a86f424152858187efc7f854ef1169c630?response-content-disposition=inline%3B+filename*%3DUTF-8%27%27animate-x_ckpt.pth%3B+filename%3D%22animate-x_ckpt.pth%22%3B&Expires=1739202957&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTczOTIwMjk1N319LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2RuLWxmcy11cy0xLmhmLmNvL3JlcG9zL2JkLzYxL2JkNjFiYzgxMTI3ZGRlMTdkODBlMDY4MTg0NTg1NWIzZDAwMDBlZmMyZWM1YzlhMmVmZDdlNDZkZGY1M2FlYWUvZTNiZmI2NTZiYWZlNjAzMTMyYTI4ZjQzZjc1OGM2YTg2ZjQyNDE1Mjg1ODE4N2VmYzdmODU0ZWYxMTY5YzYzMD9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSoifV19&Signature=dlF4Z8d3nvoTqSiJvNmSgQT1ATRjVZjRfHdXz1VJlli2tVAmhdqxEIeiAYgYF2LpEVWWt0-VF-hQS8w2XCMqQPgwS9Cvr5tGrAzF1khDrMxIrGvCfPNzZtuD6hg7F6GgQOPmtYlFo6ey2tIDZT6p9g6eCYd0D-8z96PsM61BMH3KnEXpyb8rOEi0NcKKnNp-8O4%7EBFobHZUusiD3-pHFlHxzUx9k-VJpf4WIYi69OuQe94cY2WkbClA22qF6T6chRJE6888YEm3QFM9pyqFSzSPqifX9ZH7TihkroayhFrnPTkqeGcXokMcc5HL1WXac7zGQCta44JwGDgyuUNuvOw__&Key-Pair-Id=K24J24Z295AEI9 [following]
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checkpoints/animate 100%[===================>]   6.77G  23.9MB/s    in 4m 55s  

2025-02-10 15:00:52 (23.5 MB/s) - ‘checkpoints/animate-x_ckpt.pth’ saved [7271879778/7271879778]

--2025-02-10 15:00:52--  https://huggingface.co/Isi99999/UniAnimate_and_Animate-X_Models/resolve/main/open_clip_pytorch_model.bin
Resolving huggingface.co (huggingface.co)... 13.35.202.121, 13.35.202.97, 13.35.202.40, ...
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checkpoints/open_cl 100%[===================>]   3.67G  23.4MB/s    in 2m 40s  

2025-02-10 15:03:33 (23.5 MB/s) - ‘checkpoints/open_clip_pytorch_model.bin’ saved [3944692325/3944692325]

--2025-02-10 15:03:33--  https://huggingface.co/Isi99999/UniAnimate_and_Animate-X_Models/resolve/main/v2-1_512-ema-pruned.ckpt
Resolving huggingface.co (huggingface.co)... 13.35.202.121, 13.35.202.34, 13.35.202.40, ...
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Location: https://cdn-lfs-us-1.hf.co/repos/bd/61/bd61bc81127dde17d80e0681845855b3d0000efc2ec5c9a2efd7e46ddf53aeae/88ecb782561455673c4b78d05093494b9c539fc6bfc08f3a9a4a0dd7b0b10f36?response-content-disposition=inline%3B+filename*%3DUTF-8%27%27v2-1_512-ema-pruned.ckpt%3B+filename%3D%22v2-1_512-ema-pruned.ckpt%22%3B&Expires=1739203413&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTczOTIwMzQxM319LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2RuLWxmcy11cy0xLmhmLmNvL3JlcG9zL2JkLzYxL2JkNjFiYzgxMTI3ZGRlMTdkODBlMDY4MTg0NTg1NWIzZDAwMDBlZmMyZWM1YzlhMmVmZDdlNDZkZGY1M2FlYWUvODhlY2I3ODI1NjE0NTU2NzNjNGI3OGQwNTA5MzQ5NGI5YzUzOWZjNmJmYzA4ZjNhOWE0YTBkZDdiMGIxMGYzNj9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSoifV19&Signature=bp9tymR2IVUlDVgiInT5b-3KIr2BSrwGt9XvJn61lkmvoEHopGy1S-z8g2RDfQsA8PR1lFHK8bjbm1U1E57FOGGczND8TQhQCOSleGyTl6god%7EJpKt6HyOYc-BNRkhimZa5LlFNVEcT4eNwmtIHCJufpC5xQT2I94JhIparlA%7Es6VHnS0kjR0MoYsg8w5lJGsJ26WnT9L4AulDe-gcaVS%7EBIDXdaj9jEf0A7lpzNOMbOZBUIyWQ3qu4-USoUTR3XvX5mf5ajc9u3IOVAFvmsW%7ENj7orUhVF685hOlk8WIsYXRAAA8hzObiBGc9sGu6tzCTwlCiUWJgwO3d38EBemcQ__&Key-Pair-Id=K24J24Z295AEI9 [following]
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Resolving cdn-lfs-us-1.hf.co (cdn-lfs-us-1.hf.co)... 13.35.202.120, 13.35.202.18, 13.35.202.117, ...
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checkpoints/v2-1_51 100%[===================>]   4.86G  23.3MB/s    in 3m 34s  

2025-02-10 15:07:08 (23.2 MB/s) - ‘checkpoints/v2-1_512-ema-pruned.ckpt’ saved [5214865159/5214865159]

🎉 All models are ready!

Load Inputs & Generate DWPose Data

In [ ]:

# @title
import os
import glob
import cv2
import ipywidgets as widgets
from google.colab import files
from IPython.display import display, Video, HTML
import PIL.Image
from base64 import b64encode
from IPython.display import clear_output


os.makedirs("data/videos", exist_ok=True)
os.makedirs("data/images", exist_ok=True)
os.makedirs("data/saved_pkl", exist_ok=True)
os.makedirs("data/saved_pose", exist_ok=True)
os.makedirs("data/saved_frames", exist_ok=True)


upload_image = widgets.FileUpload(accept="image/*", multiple=False)
upload_video = widgets.FileUpload(accept="video/*", multiple=False)
run_button = widgets.Button(description="Extract DWPose", button_style="success")
output_display = widgets.Output()

print("Upload Reference Image:")
display(upload_image)
print("\nUpload Driving Video:")
display(upload_video)



def save_uploaded_files(upload_widget, save_dir):
    if not upload_widget.value:
        return None
    for filename, file_info in upload_widget.value.items():
        file_path = os.path.join(save_dir, filename)
        with open(file_path, 'wb') as f:
            f.write(file_info['content'])
        return file_path


def on_run_button_click(b):
    clear_output(wait=True)

    with output_display:
        output_display.clear_output()


        image_path = save_uploaded_files(upload_image, "data/images")
        video_path = save_uploaded_files(upload_video, "data/videos")

        if not video_path:
            print("❌ No driving video uploaded!")
            return

        print(f"✅ Reference Image Saved: {image_path}")
        print(f"✅ Driving Video Saved: {video_path}")
        print("🔄 Running DWPose extraction...")

        def check_and_install(package):
          try:
              __import__(package)
          except ImportError:
              print(f"🔍 {package} not found. Installing...")
              import subprocess
              import sys
              subprocess.check_call([sys.executable, "-m", "pip", "install", package])
              print(f"✅ {package} installed successfully.")


        check_and_install("onnxruntime")


        !python process_data.py --source_video_paths data/videos --saved_pose_dir data/saved_pkl --saved_pose data/saved_pose --saved_frame_dir data/saved_frames

        print("✅ DWPose data extraction complete!")

        # Process Extracted Frames
        # frame_paths = sorted(glob.glob("data/saved_pose/*/*.jpg"))  # Include subdirectories

        # if not frame_paths:
        #     print("❌ No extracted frames found. Ensure process_data.py ran successfully.")
        # else:
        #
        #
        #     first_frame = cv2.imread(frame_paths[0])
        #     if first_frame is None:
        #         print("❌ First frame is blank. Video cannot be generated.")
        #     else:
        #         print("First frame loaded correctly.")

        #
        #     video_output_path = "dwpose_output.mp4"
        #     heightV, widthV = first_frame.shape[:2]
        #     print(f"width of video: {widthV}")
        #     print(f"height of video: {heightV}")
        #     fourcc = cv2.VideoWriter_fourcc(*'mp4v')
        #     video = cv2.VideoWriter(video_output_path, fourcc, 30, (widthV, heightV))

        #     for frame_path in frame_paths:
        #         img = cv2.imread(frame_path, cv2.IMREAD_UNCHANGED)
        #         if img is None:
        #             print(f"❌ Skipping blank frame: {frame_path}")
        #             continue  # Skip blank frames

        #         if img.shape[2] == 4:  # Convert RGBA to BGR if needed
        #             print("Converting frames to BGR...")
        #             img = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)

        #         video.write(img)

        #     video.release()
        #     print("✅ Video generation complete.")

        #
        #     print("✅ Extracted DWPose video:")
        #     display(Video(video_output_path, embed=True))


run_button.on_click(on_run_button_click)

display(run_button, output_display)

Upload Reference Image:

FileUpload(value={}, accept='image/*', description='Upload')

Upload Driving Video:

FileUpload(value={}, accept='video/*', description='Upload')

Button(button_style='success', description='Extract DWPose', style=ButtonStyle())

Output()

Set Inference Parameters & Run

In [ ]:

# @title
import os
import yaml
import glob
import IPython.display as display
import ipywidgets as widgets
from IPython.display import clear_output


def run_inference(_):

    clear_output(wait=True)

    import glob

    max_frames = max_frames_input.value
    resolution = [int(x) for x in resolution_input.value.split(",")]
    round_val = round_input.value
    ddim_timesteps = ddim_timesteps_input.value
    seed = seed_input.value
    save_fps = save_fps_input.value
    n = frame_skip_input.value


    image_files = sorted(glob.glob("data/images/*"))
    saved_pose_folders = sorted(glob.glob("data/saved_pose/*"))
    saved_frame_folders = sorted(glob.glob("data/saved_frames/*"))
    saved_pkl_files = sorted(glob.glob("data/saved_pkl/*.pkl"))


    test_list_path = []
    for img_file, pose_folder, frame_folder, pkl_file in zip(image_files, saved_pose_folders, saved_frame_folders, saved_pkl_files):
        test_list_path.append([n, img_file, pose_folder, frame_folder, pkl_file, seed])


    config = {
        "max_frames": max_frames,
        "resolution": resolution,
        "round": round_val,
        "ddim_timesteps": ddim_timesteps,
        "seed": seed,
        "save_fps": save_fps,
        "test_list_path": test_list_path,
        "log_dir": "results",
        "test_model": "checkpoints/animate-x_ckpt.pth",
        "partial_keys": [["image", "local_image", "dwpose", "pose_embeddings"]],
        "TASK_TYPE": "inference_animate_x_entrance",
        "use_fp16": True,
        "guide_scale": 2.5,
        "vit_resolution": [224, 224],
        "batch_size": 1,
        "latent_random_ref": True,
        "chunk_size": 2,
        "decoder_bs": 2,
        "scale": 8,
        "use_fps_condition": False,
        "embedder": {
            "type": "FrozenOpenCLIPTextVisualEmbedder",
            "layer": "penultimate",
            "pretrained": "checkpoints/open_clip_pytorch_model.bin"
        },
        "auto_encoder": {
            "type": "AutoencoderKL",
            "ddconfig": {
                "double_z": True,
                "z_channels": 4,
                "resolution": 256,
                "in_channels": 3,
                "out_ch": 3,
                "ch": 128,
                "ch_mult": [1, 2, 4, 4],
                "num_res_blocks": 2,
                "attn_resolutions": [],
                "dropout": 0.0,
                "video_kernel_size": [3, 1, 1]
            },
            "embed_dim": 4,
            "pretrained": "checkpoints/v2-1_512-ema-pruned.ckpt"
        },
        "UNet": {
            "type": "UNetSD_Animate_X",
            "config": None,
            "in_dim": 4,
            "num": 0,
            "no_hand": True,
            "dim": 320,
            "y_dim": 1024,
            "context_dim": 1024,
            "out_dim": 4,
            "dim_mult": [1, 2, 4, 4],
            "num_heads": 8,
            "head_dim": 64,
            "num_res_blocks": 2,
            "dropout": 0.1,
            "temporal_attention": True,
            "num_tokens": 4,
            "temporal_attn_times": 1,
            "use_checkpoint": True,
            "use_fps_condition": False,
            "use_sim_mask": False,
            "seq_len": max_frames + 1
        },
        "video_compositions": ["image", "local_image", "dwpose", "randomref", "randomref_pose", "pose_embedding"],
        "Diffusion": {
            "type": "DiffusionDDIM",
            "schedule": "linear_sd",
            "schedule_param": {
                "num_timesteps": 1000,
                "init_beta": 0.00085,
                "last_beta": 0.0120,
                "zero_terminal_snr": True
            },
            "mean_type": "v",
            "loss_type": "mse",
            "var_type": "fixed_small",
            "rescale_timesteps": False,
            "noise_strength": 0.1
        },
        "use_DiffusionDPM": False,
        "CPU_CLIP_VAE": True
    }


    config_path = "configs/Animate_X_infer.yaml"
    with open(config_path, "w") as file:
        yaml.dump(config, file, default_flow_style=False, sort_keys=False)

    print(f"✅ Configuration file updated: {config_path}")


    !python inference.py --cfg configs/Animate_X_infer.yaml

    import os
    import glob
    from IPython.display import display as displayVid, Video as outVid


    video_folder = "results/Animate_X_infer/"


    video_files = glob.glob(os.path.join(video_folder, "*.mp4"))

    if video_files:
        latest_video = max(video_files, key=os.path.getctime)
        print(f"Displaying video: {latest_video}")
        displayVid(outVid(latest_video, embed=True))
    else:
        print("❌ No video found in results/Animate_X_infer/")


max_frames_input = widgets.IntText(value=32, description="Max Frames:")
resolution_input = widgets.Text(value="512,768", description="Resolution:")
round_input = widgets.IntText(value=1, description="Round:")
ddim_timesteps_input = widgets.IntText(value=30, description="DDIM Steps:")
seed_input = widgets.IntText(value=13, description="Seed:")
save_fps_input = widgets.FloatText(value=8.0, description="FPS:", step=0.5)
frame_skip_input = widgets.IntText(value=1, description="Frame Skip (n):")


run_button = widgets.Button(description="Run Inference", button_style="danger")
run_button.on_click(run_inference)


widgets_box = widgets.VBox([max_frames_input, resolution_input, round_input, ddim_timesteps_input, seed_input, save_fps_input, frame_skip_input, run_button])
display.display(widgets_box)

✅ Configuration file updated: configs/Animate_X_infer.yaml
For Windows users, we explicitly import registry function inference_animate_x_entrance !!!
/usr/local/lib/python3.11/dist-packages/timm/models/layers/__init__.py:48: FutureWarning: Importing from timm.models.layers is deprecated, please import via timm.layers
  warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.layers", FutureWarning)
[2025-02-10 15:38:58,765] INFO: {'__name__': 'Config: VideoLDM Decoder', 'mean': [0.5, 0.5, 0.5], 'std': [0.5, 0.5, 0.5], 'max_words': 1000, 'num_workers': 8, 'prefetch_factor': 2, 'resolution': [512, 768], 'vit_out_dim': 1024, 'vit_resolution': [224, 224], 'depth_clamp': 10.0, 'misc_size': 384, 'depth_std': 20.0, 'save_fps': 8.0, 'frame_lens': [32, 32, 32, 1], 'sample_fps': [4], 'vid_dataset': {'type': 'VideoBaseDataset', 'data_list': [], 'max_words': 1000, 'resolution': [448, 256]}, 'img_dataset': {'type': 'ImageBaseDataset', 'data_list': ['laion_400m'], 'max_words': 1000, 'resolution': [448, 256]}, 'batch_sizes': {'1': 256, '4': 4, '8': 4, '16': 4}, 'Diffusion': {'type': 'DiffusionDDIM', 'schedule': 'linear_sd', 'schedule_param': {'num_timesteps': 1000, 'init_beta': 0.00085, 'last_beta': 0.012, 'zero_terminal_snr': True}, 'mean_type': 'v', 'loss_type': 'mse', 'var_type': 'fixed_small', 'rescale_timesteps': False, 'noise_strength': 0.1, 'ddim_timesteps': 50}, 'ddim_timesteps': 30, 'use_div_loss': False, 'p_zero': 0.9, 'guide_scale': 2.5, 'vit_mean': [0.48145466, 0.4578275, 0.40821073], 'vit_std': [0.26862954, 0.26130258, 0.27577711], 'sketch_mean': [0.485, 0.456, 0.406], 'sketch_std': [0.229, 0.224, 0.225], 'hist_sigma': 10.0, 'scale_factor': 0.18215, 'use_checkpoint': True, 'use_sharded_ddp': False, 'use_fsdp': False, 'use_fp16': True, 'temporal_attention': True, 'UNet': {'type': 'UNetSD_Animate_X', 'in_dim': 4, 'dim': 320, 'y_dim': 1024, 'context_dim': 1024, 'out_dim': 4, 'dim_mult': [1, 2, 4, 4], 'num_heads': 8, 'head_dim': 64, 'num_res_blocks': 2, 'attn_scales': [1.0, 0.5, 0.25], 'dropout': 0.1, 'temporal_attention': True, 'temporal_attn_times': 1, 'use_checkpoint': True, 'use_fps_condition': False, 'use_sim_mask': False, 'config': None, 'num': 0, 'no_hand': True, 'num_tokens': 4, 'seq_len': 39}, 'guidances': [], 'auto_encoder': {'type': 'AutoencoderKL', 'ddconfig': {'double_z': True, 'z_channels': 4, 'resolution': 256, 'in_channels': 3, 'out_ch': 3, 'ch': 128, 'ch_mult': [1, 2, 4, 4], 'num_res_blocks': 2, 'attn_resolutions': [], 'dropout': 0.0, 'video_kernel_size': [3, 1, 1]}, 'embed_dim': 4, 'pretrained': 'checkpoints/v2-1_512-ema-pruned.ckpt'}, 'embedder': {'type': 'FrozenOpenCLIPTextVisualEmbedder', 'layer': 'penultimate', 'pretrained': 'checkpoints/open_clip_pytorch_model.bin'}, 'ema_decay': 0.9999, 'num_steps': 600000, 'lr': 5e-05, 'weight_decay': 0.0, 'betas': [0.9, 0.999], 'eps': 1e-08, 'chunk_size': 2, 'decoder_bs': 2, 'alpha': 0.7, 'save_ckp_interval': 1000, 'warmup_steps': 10, 'decay_mode': 'cosine', 'use_ema': False, 'load_from': None, 'Pretrain': {'type': 'pretrain_specific_strategies', 'fix_weight': False, 'grad_scale': 0.2, 'resume_checkpoint': 'models/jiuniu_0267000.pth', 'sd_keys_path': 'models/stable_diffusion_image_key_temporal_attention_x1.json'}, 'viz_interval': 1000, 'resume_checkpoint': '', 'visual_train': {'type': 'VisualTrainTextImageToVideo'}, 'visual_inference': {'type': 'VisualGeneratedVideos'}, 'inference_list_path': '', 'log_interval': 100, 'log_dir': 'results/Animate_X_infer', 'seed': 13, 'negative_prompt': 'Distorted, discontinuous, Ugly, blurry, low resolution, motionless, static, disfigured, disconnected limbs, Ugly faces, incomplete arms', 'max_frames': 38, 'round': 1, 'test_list_path': [[4, 'data/images/9x16_A_Beautiful_Brazilian_blonde_gir (1).png', 'data/saved_pose/Professional_Mode_Woman_walking_forward_as_the_cam (1)', 'data/saved_frames/Professional_Mode_Woman_walking_forward_as_the_cam (1)', 'data/saved_pkl/Professional_Mode_Woman_walking_forward_as_the_cam (1).pkl', 13]], 'test_model': 'checkpoints/animate-x_ckpt.pth', 'partial_keys': [['image', 'local_image', 'dwpose', 'pose_embeddings']], 'TASK_TYPE': 'inference_animate_x_entrance', 'batch_size': 1, 'latent_random_ref': True, 'scale': 8, 'use_fps_condition': False, 'video_compositions': ['image', 'local_image', 'dwpose', 'randomref', 'randomref_pose', 'pose_embedding'], 'use_DiffusionDPM': False, 'CPU_CLIP_VAE': True, 'cfg_file': 'configs/Animate_X_infer.yaml', 'init_method': 'tcp://localhost:9999', 'debug': False, 'opts': [], 'pmi_rank': 0, 'pmi_world_size': 1, 'gpus_per_machine': 1, 'world_size': 1, 'gpu': 0, 'rank': 0, 'log_file': 'results/Animate_X_infer/log_00.txt'}
[2025-02-10 15:38:58,765] INFO: Running Animate-X inference on gpu 0
[2025-02-10 15:38:58,787] INFO: Loaded ViT-H-14 model config.
[2025-02-10 15:39:09,412] INFO: Loading pretrained ViT-H-14 weights (checkpoints/open_clip_pytorch_model.bin).
[2025-02-10 15:40:06,986] INFO: Restored from checkpoints/v2-1_512-ema-pruned.ckpt
[2025-02-10 15:41:07,051] INFO: Load model from checkpoints/animate-x_ckpt.pth with status _IncompatibleKeys(missing_keys=['pose_embedding_before.pos_embed.pos_table'], unexpected_keys=[])
[2025-02-10 15:41:09,508] INFO: There are 1 videos. with 1 times
[2025-02-10 15:41:09,509] INFO: [0]/[1] Begin to sample data/images/9x16_A_Beautiful_Brazilian_blonde_gir (1).png, pose sequence from data/saved_pose/Professional_Mode_Woman_walking_forward_as_the_cam (1) init seed 13 ...
[2025-02-10 15:41:24,691] INFO: Current seed 13 ...
100% 31/31 [10:42<00:00, 20.73s/it]
[2025-02-10 15:52:30,249] INFO: video saved in results/Animate_X_infer/9x16_A_Beautiful_Brazilian_blonde_gir 1_Professional_Mode_Woman_walking_forward_as_the_cam 1_seed_13_rank_01_00_00_768x512.mp4!
[2025-02-10 15:52:30,249] INFO: Congratulations! The inference is completed!
Displaying video: results/Animate_X_infer/9x16_A_Beautiful_Brazilian_blonde_gir 1_Professional_Mode_Woman_walking_forward_as_the_cam 1_seed_13_rank_01_00_00_768x512_results_1col.mp4

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