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lucataco /magic-animate:e24ad72c
Input
Run this model in Node.js with one line of code:
npx create-replicate --model=lucataco/magic-animate
or set up a project from scratch
Install Replicate’s Node.js client library:
npm install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import and set up the client:
import Replicate from "replicate";
import fs from "node:fs";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});Run lucataco/magic-animate using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"lucataco/magic-animate:e24ad72cc67dd2a365b5b909aca70371bba62b685019f4e96317e59d4ace6714",
{
input: {
image: "https://replicate.delivery/pbxt/JzvM9XtqsMeLzNcMfO1AISTv6TndKGPB0Lq6GajEQd7Rqj70/meme.jpeg",
video: "https://replicate.delivery/pbxt/JzvM9RW3L86hkDTYb3RhvOr1YAstTktlOvN2TZ3jMsArFyUi/multi_dancing.mp4",
guidance_scale: 7.5,
num_inference_steps: 25
}
}
);
// To access the file URL:
console.log(output.url()); //=> "http://example.com"
// To write the file to disk:
fs.writeFile("my-image.png", output);To learn more, take a look at the guide on getting started with Node.js.
Install Replicate’s Python client library:
pip install replicateSet the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Import the client:
import replicateRun lucataco/magic-animate using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"lucataco/magic-animate:e24ad72cc67dd2a365b5b909aca70371bba62b685019f4e96317e59d4ace6714",
input={
"image": "https://replicate.delivery/pbxt/JzvM9XtqsMeLzNcMfO1AISTv6TndKGPB0Lq6GajEQd7Rqj70/meme.jpeg",
"video": "https://replicate.delivery/pbxt/JzvM9RW3L86hkDTYb3RhvOr1YAstTktlOvN2TZ3jMsArFyUi/multi_dancing.mp4",
"guidance_scale": 7.5,
"num_inference_steps": 25
}
)
print(output)To learn more, take a look at the guide on getting started with Python.
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=<paste-your-token-here>Find your API token in your account settings.
Run lucataco/magic-animate using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \
-H "Authorization: Bearer $REPLICATE_API_TOKEN" \
-H "Content-Type: application/json" \
-H "Prefer: wait" \
-d $'{
"version": "lucataco/magic-animate:e24ad72cc67dd2a365b5b909aca70371bba62b685019f4e96317e59d4ace6714",
"input": {
"image": "https://replicate.delivery/pbxt/JzvM9XtqsMeLzNcMfO1AISTv6TndKGPB0Lq6GajEQd7Rqj70/meme.jpeg",
"video": "https://replicate.delivery/pbxt/JzvM9RW3L86hkDTYb3RhvOr1YAstTktlOvN2TZ3jMsArFyUi/multi_dancing.mp4",
"guidance_scale": 7.5,
"num_inference_steps": 25
}
}' \
https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
You can run this model locally using Cog. First, install Cog:
brew install cogIf you don’t have Homebrew, there are other installation options available.
Run this to download the model and run it in your local environment:
cog predict r8.im/lucataco/magic-animate@sha256:e24ad72cc67dd2a365b5b909aca70371bba62b685019f4e96317e59d4ace6714 \
-i 'image="https://replicate.delivery/pbxt/JzvM9XtqsMeLzNcMfO1AISTv6TndKGPB0Lq6GajEQd7Rqj70/meme.jpeg"' \
-i 'video="https://replicate.delivery/pbxt/JzvM9RW3L86hkDTYb3RhvOr1YAstTktlOvN2TZ3jMsArFyUi/multi_dancing.mp4"' \
-i 'guidance_scale=7.5' \
-i 'num_inference_steps=25'To learn more, take a look at the Cog documentation.
Run this to download the model and run it in your local environment:
docker run -d -p 5000:5000 --gpus=all r8.im/lucataco/magic-animate@sha256:e24ad72cc67dd2a365b5b909aca70371bba62b685019f4e96317e59d4ace6714curl -s -X POST \ -H "Content-Type: application/json" \ -d $'{ "input": { "image": "https://replicate.delivery/pbxt/JzvM9XtqsMeLzNcMfO1AISTv6TndKGPB0Lq6GajEQd7Rqj70/meme.jpeg", "video": "https://replicate.delivery/pbxt/JzvM9RW3L86hkDTYb3RhvOr1YAstTktlOvN2TZ3jMsArFyUi/multi_dancing.mp4", "guidance_scale": 7.5, "num_inference_steps": 25 } }' \ http://localhost:5000/predictions
To learn more, take a look at the Cog documentation.
Add a payment method to run this model.
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Output
{
"completed_at": "2023-12-05T21:09:58.988081Z",
"created_at": "2023-12-05T21:07:39.467889Z",
"data_removed": false,
"error": null,
"id": "xqiik5zbjv6hvuhr2atlin42rm",
"input": {
"image": "https://replicate.delivery/pbxt/JzvM9XtqsMeLzNcMfO1AISTv6TndKGPB0Lq6GajEQd7Rqj70/meme.jpeg",
"video": "https://replicate.delivery/pbxt/JzvM9RW3L86hkDTYb3RhvOr1YAstTktlOvN2TZ3jMsArFyUi/multi_dancing.mp4",
"guidance_scale": 7.5,
"num_inference_steps": 25
},
"logs": "Using seed: 3659\n/src/magic-animate/magicanimate/pipelines/pipeline_animation.py:43: FutureWarning: Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import from diffusers.pipelines.pipeline_utils instead.\nfrom diffusers.pipeline_utils import DiffusionPipeline\nloaded temporal unet's pretrained weights from /src/pretrained_models/stable-diffusion-v1-5/unet ...\n### missing keys: 560;\n### unexpected keys: 0;\n### Temporal Module Parameters: 417.1376 M\nThe config attributes {'addition_embed_type': None, 'addition_embed_type_num_heads': 64, 'addition_time_embed_dim': None, 'conditioning_channels': 3, 'encoder_hid_dim': None, 'encoder_hid_dim_type': None, 'global_pool_conditions': False, 'num_attention_heads': None, 'transformer_layers_per_block': 1} were passed to ControlNetModel, but are not expected and will be ignored. Please verify your config.json configuration file.\nIt is recommended to provide `attention_head_dim` when calling `get_down_block`. Defaulting `attention_head_dim` to 8.\nIt is recommended to provide `attention_head_dim` when calling `get_down_block`. Defaulting `attention_head_dim` to 8.\nIt is recommended to provide `attention_head_dim` when calling `get_down_block`. Defaulting `attention_head_dim` to 8.\nIt is recommended to provide `attention_head_dim` when calling `get_down_block`. Defaulting `attention_head_dim` to 8.\n/src/magic-animate/magicanimate/pipelines/pipeline_animation.py:103: FutureWarning: The configuration file of this scheduler: DDIMScheduler {\n\"_class_name\": \"DDIMScheduler\",\n\"_diffusers_version\": \"0.21.4\",\n\"beta_end\": 0.012,\n\"beta_schedule\": \"linear\",\n\"beta_start\": 0.00085,\n\"clip_sample\": true,\n\"clip_sample_range\": 1.0,\n\"dynamic_thresholding_ratio\": 0.995,\n\"num_train_timesteps\": 1000,\n\"prediction_type\": \"epsilon\",\n\"rescale_betas_zero_snr\": false,\n\"sample_max_value\": 1.0,\n\"set_alpha_to_one\": true,\n\"steps_offset\": 0,\n\"thresholding\": false,\n\"timestep_spacing\": \"leading\",\n\"trained_betas\": null\n}\nis outdated. `steps_offset` should be set to 1 instead of 0. Please make sure to update the config accordingly as leaving `steps_offset` might led to incorrect results in future versions. If you have downloaded this checkpoint from the Hugging Face Hub, it would be very nice if you could open a Pull request for the `scheduler/scheduler_config.json` file\ndeprecate(\"steps_offset!=1\", \"1.0.0\", deprecation_message, standard_warn=False)\n/src/magic-animate/magicanimate/pipelines/pipeline_animation.py:116: FutureWarning: The configuration file of this scheduler: DDIMScheduler {\n\"_class_name\": \"DDIMScheduler\",\n\"_diffusers_version\": \"0.21.4\",\n\"beta_end\": 0.012,\n\"beta_schedule\": \"linear\",\n\"beta_start\": 0.00085,\n\"clip_sample\": true,\n\"clip_sample_range\": 1.0,\n\"dynamic_thresholding_ratio\": 0.995,\n\"num_train_timesteps\": 1000,\n\"prediction_type\": \"epsilon\",\n\"rescale_betas_zero_snr\": false,\n\"sample_max_value\": 1.0,\n\"set_alpha_to_one\": true,\n\"steps_offset\": 1,\n\"thresholding\": false,\n\"timestep_spacing\": \"leading\",\n\"trained_betas\": null\n}\nhas not set the configuration `clip_sample`. `clip_sample` should be set to False in the configuration file. Please make sure to update the config accordingly as not setting `clip_sample` in the config might lead to incorrect results in future versions. If you have downloaded this checkpoint from the Hugging Face Hub, it would be very nice if you could open a Pull request for the `scheduler/scheduler_config.json` file\ndeprecate(\"clip_sample not set\", \"1.0.0\", deprecation_message, standard_warn=False)\ncurrent seed: 3659\n 0%| | 0/1 [00:00<?, ?it/s]/src/magic-animate/magicanimate/pipelines/pipeline_animation.py:624: FutureWarning: Accessing config attribute `in_channels` directly via 'UNet3DConditionModel' object attribute is deprecated. Please access 'in_channels' over 'UNet3DConditionModel's config object instead, e.g. 'unet.config.in_channels'.\nnum_channels_latents = self.unet.in_channels\n 0%| | 0/25 [00:00<?, ?it/s]\u001b[A\n 4%|▍ | 1/25 [00:04<01:38, 4.12s/it]\u001b[A\n 8%|▊ | 2/25 [00:08<01:32, 4.02s/it]\u001b[A\n 12%|█▏ | 3/25 [00:11<01:27, 3.97s/it]\u001b[A\n 16%|█▌ | 4/25 [00:15<01:23, 3.97s/it]\u001b[A\n 20%|██ | 5/25 [00:19<01:19, 3.97s/it]\u001b[A\n 24%|██▍ | 6/25 [00:23<01:15, 3.96s/it]\u001b[A\n 28%|██▊ | 7/25 [00:27<01:11, 3.96s/it]\u001b[A\n 32%|███▏ | 8/25 [00:31<01:07, 3.96s/it]\u001b[A\n 36%|███▌ | 9/25 [00:35<01:03, 3.96s/it]\u001b[A\n 40%|████ | 10/25 [00:39<00:59, 3.96s/it]\u001b[A\n 44%|████▍ | 11/25 [00:43<00:55, 3.96s/it]\u001b[A\n 48%|████▊ | 12/25 [00:47<00:51, 3.95s/it]\u001b[A\n 52%|█████▏ | 13/25 [00:51<00:47, 3.95s/it]\u001b[A\n 56%|█████▌ | 14/25 [00:55<00:43, 3.95s/it]\u001b[A\n 60%|██████ | 15/25 [00:59<00:39, 3.95s/it]\u001b[A\n 64%|██████▍ | 16/25 [01:03<00:35, 3.95s/it]\u001b[A\n 68%|██████▊ | 17/25 [01:07<00:31, 3.95s/it]\u001b[A\n 72%|███████▏ | 18/25 [01:11<00:27, 3.96s/it]\u001b[A\n 76%|███████▌ | 19/25 [01:15<00:23, 3.96s/it]\u001b[A\n 80%|████████ | 20/25 [01:19<00:19, 3.96s/it]\u001b[A\n 84%|████████▍ | 21/25 [01:23<00:15, 3.96s/it]\u001b[A\n 88%|████████▊ | 22/25 [01:27<00:11, 3.96s/it]\u001b[A\n 92%|█████████▏| 23/25 [01:31<00:07, 3.96s/it]\u001b[A\n 96%|█████████▌| 24/25 [01:35<00:03, 3.96s/it]\u001b[A\n100%|██████████| 25/25 [01:39<00:00, 3.97s/it]\u001b[A\n100%|██████████| 25/25 [01:39<00:00, 3.96s/it]\n 0%| | 0/96 [00:00<?, ?it/s]\u001b[A\n 6%|▋ | 6/96 [00:00<00:01, 46.92it/s]\u001b[A\n 11%|█▏ | 11/96 [00:00<00:02, 33.05it/s]\u001b[A\n 16%|█▌ | 15/96 [00:00<00:02, 30.18it/s]\u001b[A\n 20%|█▉ | 19/96 [00:00<00:02, 28.76it/s]\u001b[A\n 23%|██▎ | 22/96 [00:00<00:02, 28.10it/s]\u001b[A\n 26%|██▌ | 25/96 [00:00<00:02, 27.62it/s]\u001b[A\n 29%|██▉ | 28/96 [00:00<00:02, 27.29it/s]\u001b[A\n 32%|███▏ | 31/96 [00:01<00:02, 27.05it/s]\u001b[A\n 35%|███▌ | 34/96 [00:01<00:02, 26.88it/s]\u001b[A\n 39%|███▊ | 37/96 [00:01<00:02, 26.76it/s]\u001b[A\n 42%|████▏ | 40/96 [00:01<00:02, 26.68it/s]\u001b[A\n 45%|████▍ | 43/96 [00:01<00:01, 26.62it/s]\u001b[A\n 48%|████▊ | 46/96 [00:01<00:01, 26.58it/s]\u001b[A\n 51%|█████ | 49/96 [00:01<00:01, 26.55it/s]\u001b[A\n 54%|█████▍ | 52/96 [00:01<00:01, 26.54it/s]\u001b[A\n 57%|█████▋ | 55/96 [00:01<00:01, 26.52it/s]\u001b[A\n 60%|██████ | 58/96 [00:02<00:01, 26.51it/s]\u001b[A\n 64%|██████▎ | 61/96 [00:02<00:01, 26.50it/s]\u001b[A\n 67%|██████▋ | 64/96 [00:02<00:01, 26.50it/s]\u001b[A\n 70%|██████▉ | 67/96 [00:02<00:01, 26.49it/s]\u001b[A\n 73%|███████▎ | 70/96 [00:02<00:00, 26.49it/s]\u001b[A\n 76%|███████▌ | 73/96 [00:02<00:00, 26.49it/s]\u001b[A\n 79%|███████▉ | 76/96 [00:02<00:00, 26.49it/s]\u001b[A\n 82%|████████▏ | 79/96 [00:02<00:00, 26.49it/s]\u001b[A\n 85%|████████▌ | 82/96 [00:02<00:00, 26.49it/s]\u001b[A\n 89%|████████▊ | 85/96 [00:03<00:00, 26.48it/s]\u001b[A\n 92%|█████████▏| 88/96 [00:03<00:00, 26.49it/s]\u001b[A\n 95%|█████████▍| 91/96 [00:03<00:00, 26.49it/s]\u001b[A\n 98%|█████████▊| 94/96 [00:03<00:00, 26.49it/s]\u001b[A\n100%|██████████| 96/96 [00:03<00:00, 27.22it/s]\nIMAGEIO FFMPEG_WRITER WARNING: input image is not divisible by macro_block_size=16, resizing from (1544, 516) to (1552, 528) to ensure video compatibility with most codecs and players. To prevent resizing, make your input image divisible by the macro_block_size or set the macro_block_size to 1 (risking incompatibility).\n[swscaler @ 0x5baa740] Warning: data is not aligned! This can lead to a speed loss\n100%|██████████| 1/1 [01:48<00:00, 108.06s/it]\n100%|██████████| 1/1 [01:48<00:00, 108.06s/it]\n/src/magic-animate/samples/config-2023-12-05T21-07-44/videos/tmp3x9__2mjmeme_tmp8yfgquj_multi_dancing.mp4",
"metrics": {
"predict_time": 139.505846,
"total_time": 139.520192
},
"output": "https://replicate.delivery/pbxt/qy0jsX7eYTyEBS452fKpLMvKIbCf9xR6RO3UYZwUYgpNdoeHB/tmp3x9__2mjmeme_tmp8yfgquj_multi_dancing.mp4",
"started_at": "2023-12-05T21:07:39.482235Z",
"status": "succeeded",
"urls": {
"get": "https://api.replicate.com/v1/predictions/xqiik5zbjv6hvuhr2atlin42rm",
"cancel": "https://api.replicate.com/v1/predictions/xqiik5zbjv6hvuhr2atlin42rm/cancel"
},
"version": "e24ad72cc67dd2a365b5b909aca70371bba62b685019f4e96317e59d4ace6714"
}Generated in
Using seed: 3659
/src/magic-animate/magicanimate/pipelines/pipeline_animation.py:43: FutureWarning: Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import from diffusers.pipelines.pipeline_utils instead.
from diffusers.pipeline_utils import DiffusionPipeline
loaded temporal unet's pretrained weights from /src/pretrained_models/stable-diffusion-v1-5/unet ...
### missing keys: 560;
### unexpected keys: 0;
### Temporal Module Parameters: 417.1376 M
The config attributes {'addition_embed_type': None, 'addition_embed_type_num_heads': 64, 'addition_time_embed_dim': None, 'conditioning_channels': 3, 'encoder_hid_dim': None, 'encoder_hid_dim_type': None, 'global_pool_conditions': False, 'num_attention_heads': None, 'transformer_layers_per_block': 1} were passed to ControlNetModel, but are not expected and will be ignored. Please verify your config.json configuration file.
It is recommended to provide `attention_head_dim` when calling `get_down_block`. Defaulting `attention_head_dim` to 8.
It is recommended to provide `attention_head_dim` when calling `get_down_block`. Defaulting `attention_head_dim` to 8.
It is recommended to provide `attention_head_dim` when calling `get_down_block`. Defaulting `attention_head_dim` to 8.
It is recommended to provide `attention_head_dim` when calling `get_down_block`. Defaulting `attention_head_dim` to 8.
/src/magic-animate/magicanimate/pipelines/pipeline_animation.py:103: FutureWarning: The configuration file of this scheduler: DDIMScheduler {
"_class_name": "DDIMScheduler",
"_diffusers_version": "0.21.4",
"beta_end": 0.012,
"beta_schedule": "linear",
"beta_start": 0.00085,
"clip_sample": true,
"clip_sample_range": 1.0,
"dynamic_thresholding_ratio": 0.995,
"num_train_timesteps": 1000,
"prediction_type": "epsilon",
"rescale_betas_zero_snr": false,
"sample_max_value": 1.0,
"set_alpha_to_one": true,
"steps_offset": 0,
"thresholding": false,
"timestep_spacing": "leading",
"trained_betas": null
}
is outdated. `steps_offset` should be set to 1 instead of 0. Please make sure to update the config accordingly as leaving `steps_offset` might led to incorrect results in future versions. If you have downloaded this checkpoint from the Hugging Face Hub, it would be very nice if you could open a Pull request for the `scheduler/scheduler_config.json` file
deprecate("steps_offset!=1", "1.0.0", deprecation_message, standard_warn=False)
/src/magic-animate/magicanimate/pipelines/pipeline_animation.py:116: FutureWarning: The configuration file of this scheduler: DDIMScheduler {
"_class_name": "DDIMScheduler",
"_diffusers_version": "0.21.4",
"beta_end": 0.012,
"beta_schedule": "linear",
"beta_start": 0.00085,
"clip_sample": true,
"clip_sample_range": 1.0,
"dynamic_thresholding_ratio": 0.995,
"num_train_timesteps": 1000,
"prediction_type": "epsilon",
"rescale_betas_zero_snr": false,
"sample_max_value": 1.0,
"set_alpha_to_one": true,
"steps_offset": 1,
"thresholding": false,
"timestep_spacing": "leading",
"trained_betas": null
}
has not set the configuration `clip_sample`. `clip_sample` should be set to False in the configuration file. Please make sure to update the config accordingly as not setting `clip_sample` in the config might lead to incorrect results in future versions. If you have downloaded this checkpoint from the Hugging Face Hub, it would be very nice if you could open a Pull request for the `scheduler/scheduler_config.json` file
deprecate("clip_sample not set", "1.0.0", deprecation_message, standard_warn=False)
current seed: 3659
0%| | 0/1 [00:00<?, ?it/s]/src/magic-animate/magicanimate/pipelines/pipeline_animation.py:624: FutureWarning: Accessing config attribute `in_channels` directly via 'UNet3DConditionModel' object attribute is deprecated. Please access 'in_channels' over 'UNet3DConditionModel's config object instead, e.g. 'unet.config.in_channels'.
num_channels_latents = self.unet.in_channels
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IMAGEIO FFMPEG_WRITER WARNING: input image is not divisible by macro_block_size=16, resizing from (1544, 516) to (1552, 528) to ensure video compatibility with most codecs and players. To prevent resizing, make your input image divisible by the macro_block_size or set the macro_block_size to 1 (risking incompatibility).
[swscaler @ 0x5baa740] Warning: data is not aligned! This can lead to a speed loss
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/src/magic-animate/samples/config-2023-12-05T21-07-44/videos/tmp3x9__2mjmeme_tmp8yfgquj_multi_dancing.mp4