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feature: stable diffusion video (SVD)
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import logging | ||
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import click | ||
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logger = logging.getLogger(__name__) | ||
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@click.command() | ||
@click.option( | ||
"--start-image", | ||
default="other/images/sound-music.jpg", | ||
help="Input path for image file.", | ||
) | ||
@click.option("--num-frames", default=None, type=int, help="Number of frames.") | ||
@click.option("--num-steps", default=None, type=int, help="Number of steps.") | ||
@click.option( | ||
"--model", | ||
default="svd", | ||
help="Model to use. One of: svd, svd_xt, svd_image_decoder, svd_xt_image_decoder", | ||
) | ||
@click.option( | ||
"--fps", default=6, type=int, help="FPS for the AI to target when generating video" | ||
) | ||
@click.option("--output-fps", default=None, type=int, help="FPS for the output video") | ||
@click.option( | ||
"--motion-amount", | ||
default=127, | ||
type=int, | ||
help="How much motion to generate. value between 0 and 255.", | ||
) | ||
@click.option( | ||
"-r", | ||
"--repeats", | ||
default=1, | ||
show_default=True, | ||
type=int, | ||
help="How many times to repeat the renders. ", | ||
) | ||
@click.option("--cond-aug", default=0.02, type=float, help="Conditional augmentation.") | ||
@click.option( | ||
"--seed", default=None, type=int, help="Seed for random number generator." | ||
) | ||
@click.option( | ||
"--decoding_t", default=1, type=int, help="Number of frames decoded at a time." | ||
) | ||
@click.option("--device", default=None, help="Device to use.") | ||
@click.option("--output_folder", default=None, help="Output folder.") | ||
def videogen_cmd( | ||
start_image, | ||
num_frames, | ||
num_steps, | ||
model, | ||
fps, | ||
output_fps, | ||
motion_amount, | ||
repeats, | ||
cond_aug, | ||
seed, | ||
decoding_t, | ||
device, | ||
output_folder, | ||
): | ||
""" | ||
AI generate a video from an image | ||
Example: | ||
aimg videogen --start-image assets/rocket-wide.png | ||
""" | ||
from imaginairy.log_utils import configure_logging | ||
from imaginairy.video_sample import generate_video | ||
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configure_logging() | ||
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output_fps = output_fps or fps | ||
for i in range(repeats): | ||
logger.info(f"Generating video from image {start_image}") | ||
generate_video( | ||
input_path=start_image, | ||
num_frames=num_frames, | ||
num_steps=num_steps, | ||
model_name=model, | ||
fps_id=fps, | ||
output_fps=output_fps, | ||
motion_bucket_id=motion_amount, | ||
cond_aug=cond_aug, | ||
seed=seed, | ||
decoding_t=decoding_t, | ||
device=device, | ||
output_folder=output_folder, | ||
) |
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model: | ||
target: imaginairy.modules.sgm.diffusion.DiffusionEngine | ||
params: | ||
scale_factor: 0.18215 | ||
disable_first_stage_autocast: False | ||
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denoiser_config: | ||
target: imaginairy.modules.sgm.diffusionmodules.denoiser.Denoiser | ||
params: | ||
scaling_config: | ||
target: imaginairy.modules.sgm.diffusionmodules.denoiser_scaling.VScalingWithEDMcNoise | ||
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network_config: | ||
target: imaginairy.modules.sgm.diffusionmodules.video_model.VideoUNet | ||
params: | ||
adm_in_channels: 768 | ||
num_classes: sequential | ||
use_checkpoint: False | ||
in_channels: 8 | ||
out_channels: 4 | ||
model_channels: 320 | ||
attention_resolutions: [4, 2, 1] | ||
num_res_blocks: 2 | ||
channel_mult: [1, 2, 4, 4] | ||
num_head_channels: 64 | ||
use_linear_in_transformer: True | ||
transformer_depth: 1 | ||
context_dim: 1024 | ||
spatial_transformer_attn_type: softmax-xformers | ||
extra_ff_mix_layer: True | ||
use_spatial_context: True | ||
merge_strategy: learned_with_images | ||
video_kernel_size: [3, 1, 1] | ||
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conditioner_config: | ||
target: imaginairy.modules.sgm.encoders.modules.GeneralConditioner | ||
params: | ||
emb_models: | ||
- is_trainable: False | ||
input_key: cond_frames_without_noise | ||
target: imaginairy.modules.sgm.encoders.modules.FrozenOpenCLIPImagePredictionEmbedder | ||
params: | ||
n_cond_frames: 1 | ||
n_copies: 1 | ||
open_clip_embedding_config: | ||
target: imaginairy.modules.sgm.encoders.modules.FrozenOpenCLIPImageEmbedder | ||
params: | ||
freeze: True | ||
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- input_key: fps_id | ||
is_trainable: False | ||
target: imaginairy.modules.sgm.encoders.modules.ConcatTimestepEmbedderND | ||
params: | ||
outdim: 256 | ||
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- input_key: motion_bucket_id | ||
is_trainable: False | ||
target: imaginairy.modules.sgm.encoders.modules.ConcatTimestepEmbedderND | ||
params: | ||
outdim: 256 | ||
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- input_key: cond_frames | ||
is_trainable: False | ||
target: imaginairy.modules.sgm.encoders.modules.VideoPredictionEmbedderWithEncoder | ||
params: | ||
disable_encoder_autocast: False | ||
n_cond_frames: 1 | ||
n_copies: 1 | ||
is_ae: True | ||
encoder_config: | ||
target: imaginairy.modules.sgm.autoencoder.AutoencoderKLModeOnly | ||
params: | ||
embed_dim: 4 | ||
monitor: val/rec_loss | ||
ddconfig: | ||
attn_type: vanilla-xformers | ||
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 | ||
lossconfig: | ||
target: torch.nn.Identity | ||
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- input_key: cond_aug | ||
is_trainable: False | ||
target: imaginairy.modules.sgm.encoders.modules.ConcatTimestepEmbedderND | ||
params: | ||
outdim: 256 | ||
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first_stage_config: | ||
target: imaginairy.modules.sgm.autoencoder.AutoencodingEngine | ||
params: | ||
loss_config: | ||
target: torch.nn.Identity | ||
regularizer_config: | ||
target: imaginairy.modules.sgm.autoencoding.regularizers.DiagonalGaussianRegularizer | ||
encoder_config: | ||
target: imaginairy.modules.sgm.diffusionmodules.model.Encoder | ||
params: | ||
attn_type: vanilla | ||
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 | ||
decoder_config: | ||
target: imaginairy.modules.sgm.autoencoding.temporal_ae.VideoDecoder | ||
params: | ||
attn_type: vanilla | ||
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] | ||
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sampler_config: | ||
target: imaginairy.modules.sgm.diffusionmodules.sampling.EulerEDMSampler | ||
params: | ||
discretization_config: | ||
target: imaginairy.modules.sgm.diffusionmodules.discretizer.EDMDiscretization | ||
params: | ||
sigma_max: 700.0 | ||
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guider_config: | ||
target: imaginairy.modules.sgm.diffusionmodules.guiders.LinearPredictionGuider | ||
params: | ||
max_scale: 2.5 | ||
min_scale: 1.0 |
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