typefile
ID
k6dulktb4ye3os5r35lqhcj7ge
Status
Succeeded
Source
Web
Hardware
A100 (40GB)
Total duration
Created
Webhook
–
Input
- video
- num_inference_steps
- 25default25typenumeric-rangevalue typeintegerminimum1maximum200
- guidance_scale
- 7.5default7.5typenumeric-rangevalue typenumberminimum1maximum50
{
"guidance_scale": 7.5,
"image": "https://replicate.delivery/pbxt/K0kzPvawpylCI7kbDaglA1HI55TcHwIizaPpA0kvymsFOqM3/dalle8.jpeg",
"num_inference_steps": 25,
"video": "https://replicate.delivery/pbxt/K0kzQQLaQjwf8MYBJUVX9mpoL38pGSzzgygXvgQnEcSmZhft/hiphop-openpose.mp4"
}Install Replicate’s Node.js client library:
npm install replicate
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_S96**********************************
This is your API token. Keep it to yourself.
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-openpose 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-openpose:4e88cd2f48240dcfd59186b00b52b3763250486e0c65bb4d1ff4744506d222c3",
{
input: {
guidance_scale: 7.5,
image: "https://replicate.delivery/pbxt/K0kzPvawpylCI7kbDaglA1HI55TcHwIizaPpA0kvymsFOqM3/dalle8.jpeg",
num_inference_steps: 25,
video: "https://replicate.delivery/pbxt/K0kzQQLaQjwf8MYBJUVX9mpoL38pGSzzgygXvgQnEcSmZhft/hiphop-openpose.mp4"
}
}
);
// 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 replicate
Set the
REPLICATE_API_TOKEN environment variable:export REPLICATE_API_TOKEN=r8_S96**********************************
This is your API token. Keep it to yourself.
Import the client:
import replicate
Run lucataco/magic-animate-openpose using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"lucataco/magic-animate-openpose:4e88cd2f48240dcfd59186b00b52b3763250486e0c65bb4d1ff4744506d222c3",
input={
"guidance_scale": 7.5,
"image": "https://replicate.delivery/pbxt/K0kzPvawpylCI7kbDaglA1HI55TcHwIizaPpA0kvymsFOqM3/dalle8.jpeg",
"num_inference_steps": 25,
"video": "https://replicate.delivery/pbxt/K0kzQQLaQjwf8MYBJUVX9mpoL38pGSzzgygXvgQnEcSmZhft/hiphop-openpose.mp4"
}
)
# To access the file URL:
print(output.url())
#=> "http://example.com"
# To write the file to disk:
with open("my-image.png", "wb") as file:
file.write(output.read())
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=r8_S96**********************************
This is your API token. Keep it to yourself.
Run lucataco/magic-animate-openpose 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-openpose:4e88cd2f48240dcfd59186b00b52b3763250486e0c65bb4d1ff4744506d222c3",
"input": {
"guidance_scale": 7.5,
"image": "https://replicate.delivery/pbxt/K0kzPvawpylCI7kbDaglA1HI55TcHwIizaPpA0kvymsFOqM3/dalle8.jpeg",
"num_inference_steps": 25,
"video": "https://replicate.delivery/pbxt/K0kzQQLaQjwf8MYBJUVX9mpoL38pGSzzgygXvgQnEcSmZhft/hiphop-openpose.mp4"
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Output
{
"id": "k6dulktb4ye3os5r35lqhcj7ge",
"model": "lucataco/magic-animate-openpose",
"version": "4e88cd2f48240dcfd59186b00b52b3763250486e0c65bb4d1ff4744506d222c3",
"input": {
"guidance_scale": 7.5,
"image": "https://replicate.delivery/pbxt/K0kzPvawpylCI7kbDaglA1HI55TcHwIizaPpA0kvymsFOqM3/dalle8.jpeg",
"num_inference_steps": 25,
"video": "https://replicate.delivery/pbxt/K0kzQQLaQjwf8MYBJUVX9mpoL38pGSzzgygXvgQnEcSmZhft/hiphop-openpose.mp4"
},
"logs": "Using seed: 2244563620\nThe cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.\n0it [00:00, ?it/s]\n0it [00:00, ?it/s]\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\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: 2244563620\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 [00:06<02:41, 6.74s/it]\u001b[A\n 8%|▊ | 2/25 [00:13<02:33, 6.69s/it]\u001b[A\n 12%|█▏ | 3/25 [00:20<02:26, 6.67s/it]\u001b[A\n 16%|█▌ | 4/25 [00:26<02:20, 6.67s/it]\u001b[A\n 20%|██ | 5/25 [00:33<02:13, 6.67s/it]\u001b[A\n 24%|██▍ | 6/25 [00:40<02:06, 6.67s/it]\u001b[A\n 28%|██▊ | 7/25 [00:46<02:00, 6.67s/it]\u001b[A\n 32%|███▏ | 8/25 [00:53<01:53, 6.67s/it]\u001b[A\n 36%|███▌ | 9/25 [01:00<01:46, 6.67s/it]\u001b[A\n 40%|████ | 10/25 [01:06<01:40, 6.67s/it]\u001b[A\n 44%|████▍ | 11/25 [01:13<01:33, 6.67s/it]\u001b[A\n 48%|████▊ | 12/25 [01:20<01:26, 6.67s/it]\u001b[A\n 52%|█████▏ | 13/25 [01:26<01:20, 6.67s/it]\u001b[A\n 56%|█████▌ | 14/25 [01:33<01:13, 6.67s/it]\u001b[A\n 60%|██████ | 15/25 [01:40<01:06, 6.67s/it]\u001b[A\n 64%|██████▍ | 16/25 [01:46<01:00, 6.67s/it]\u001b[A\n 68%|██████▊ | 17/25 [01:53<00:53, 6.67s/it]\u001b[A\n 72%|███████▏ | 18/25 [02:00<00:46, 6.67s/it]\u001b[A\n 76%|███████▌ | 19/25 [02:06<00:40, 6.67s/it]\u001b[A\n 80%|████████ | 20/25 [02:13<00:33, 6.67s/it]\u001b[A\n 84%|████████▍ | 21/25 [02:20<00:26, 6.68s/it]\u001b[A\n 88%|████████▊ | 22/25 [02:26<00:20, 6.68s/it]\u001b[A\n 92%|█████████▏| 23/25 [02:33<00:13, 6.68s/it]\u001b[A\n 96%|█████████▌| 24/25 [02:40<00:06, 6.68s/it]\u001b[A\n100%|██████████| 25/25 [02:46<00:00, 6.68s/it]\u001b[A\n100%|██████████| 25/25 [02:46<00:00, 6.67s/it]\n 0%| | 0/160 [00:00<?, ?it/s]\u001b[A\n 4%|▍ | 6/160 [00:00<00:03, 50.88it/s]\u001b[A\n 8%|▊ | 12/160 [00:00<00:04, 33.01it/s]\u001b[A\n 10%|█ | 16/160 [00:00<00:04, 30.35it/s]\u001b[A\n 12%|█▎ | 20/160 [00:00<00:04, 28.94it/s]\u001b[A\n 14%|█▍ | 23/160 [00:00<00:04, 28.27it/s]\u001b[A\n 16%|█▋ | 26/160 [00:00<00:04, 27.76it/s]\u001b[A\n 18%|█▊ | 29/160 [00:00<00:04, 27.40it/s]\u001b[A\n 20%|██ | 32/160 [00:01<00:04, 27.15it/s]\u001b[A\n 22%|██▏ | 35/160 [00:01<00:04, 26.97it/s]\u001b[A\n 24%|██▍ | 38/160 [00:01<00:04, 26.84it/s]\u001b[A\n 26%|██▌ | 41/160 [00:01<00:04, 26.74it/s]\u001b[A\n 28%|██▊ | 44/160 [00:01<00:04, 26.68it/s]\u001b[A\n 29%|██▉ | 47/160 [00:01<00:04, 26.64it/s]\u001b[A\n 31%|███▏ | 50/160 [00:01<00:04, 26.60it/s]\u001b[A\n 33%|███▎ | 53/160 [00:01<00:04, 26.59it/s]\u001b[A\n 35%|███▌ | 56/160 [00:02<00:03, 26.56it/s]\u001b[A\n 37%|███▋ | 59/160 [00:02<00:03, 26.55it/s]\u001b[A\n 39%|███▉ | 62/160 [00:02<00:03, 26.54it/s]\u001b[A\n 41%|████ | 65/160 [00:02<00:03, 26.54it/s]\u001b[A\n 42%|████▎ | 68/160 [00:02<00:03, 26.55it/s]\u001b[A\n 44%|████▍ | 71/160 [00:02<00:03, 26.55it/s]\u001b[A\n 46%|████▋ | 74/160 [00:02<00:03, 26.54it/s]\u001b[A\n 48%|████▊ | 77/160 [00:02<00:03, 26.53it/s]\u001b[A\n 50%|█████ | 80/160 [00:02<00:03, 26.53it/s]\u001b[A\n 52%|█████▏ | 83/160 [00:03<00:02, 26.53it/s]\u001b[A\n 54%|█████▍ | 86/160 [00:03<00:02, 26.52it/s]\u001b[A\n 56%|█████▌ | 89/160 [00:03<00:02, 26.51it/s]\u001b[A\n 57%|█████▊ | 92/160 [00:03<00:02, 26.52it/s]\u001b[A\n 59%|█████▉ | 95/160 [00:03<00:02, 26.53it/s]\u001b[A\n 61%|██████▏ | 98/160 [00:03<00:02, 26.53it/s]\u001b[A\n 63%|██████▎ | 101/160 [00:03<00:02, 26.53it/s]\u001b[A\n 65%|██████▌ | 104/160 [00:03<00:02, 26.52it/s]\u001b[A\n 67%|██████▋ | 107/160 [00:03<00:01, 26.53it/s]\u001b[A\n 69%|██████▉ | 110/160 [00:04<00:01, 26.52it/s]\u001b[A\n 71%|███████ | 113/160 [00:04<00:01, 26.53it/s]\u001b[A\n 72%|███████▎ | 116/160 [00:04<00:01, 26.53it/s]\u001b[A\n 74%|███████▍ | 119/160 [00:04<00:01, 26.52it/s]\u001b[A\n 76%|███████▋ | 122/160 [00:04<00:01, 26.52it/s]\u001b[A\n 78%|███████▊ | 125/160 [00:04<00:01, 26.53it/s]\u001b[A\n 80%|████████ | 128/160 [00:04<00:01, 26.52it/s]\u001b[A\n 82%|████████▏ | 131/160 [00:04<00:01, 26.52it/s]\u001b[A\n 84%|████████▍ | 134/160 [00:04<00:00, 26.52it/s]\u001b[A\n 86%|████████▌ | 137/160 [00:05<00:00, 26.51it/s]\u001b[A\n 88%|████████▊ | 140/160 [00:05<00:00, 26.52it/s]\u001b[A\n 89%|████████▉ | 143/160 [00:05<00:00, 26.53it/s]\u001b[A\n 91%|█████████▏| 146/160 [00:05<00:00, 26.54it/s]\u001b[A\n 93%|█████████▎| 149/160 [00:05<00:00, 26.54it/s]\u001b[A\n 95%|█████████▌| 152/160 [00:05<00:00, 26.55it/s]\u001b[A\n 97%|█████████▋| 155/160 [00:05<00:00, 26.55it/s]\u001b[A\n 99%|█████████▉| 158/160 [00:05<00:00, 26.55it/s]\u001b[A\n100%|██████████| 160/160 [00:05<00:00, 27.01it/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 @ 0x7239ac0] Warning: data is not aligned! This can lead to a speed loss\n100%|██████████| 1/1 [03:21<00:00, 201.71s/it]\n100%|██████████| 1/1 [03:21<00:00, 201.71s/it]\n/src/magic-animate/samples/config-2023-12-08T05-30-28/videos/input_tmpqk3hj7h7hiphop-openpose.mp4",
"output": "https://replicate.delivery/pbxt/nG5oBs4feEvx5Et9578NOUpY9aqKYVfPeeqMRqspgV9KauAQC/input_tmpqk3hj7h7hiphop-openpose.mp4",
"data_removed": false,
"error": null,
"source": "web",
"status": "succeeded",
"created_at": "2023-12-08T05:26:09.45792Z",
"started_at": "2023-12-08T05:30:23.803519Z",
"completed_at": "2023-12-08T05:34:09.935934Z",
"urls": {
"cancel": "https://api.replicate.com/v1/predictions/k6dulktb4ye3os5r35lqhcj7ge/cancel",
"get": "https://api.replicate.com/v1/predictions/k6dulktb4ye3os5r35lqhcj7ge"
},
"metrics": {
"predict_time": 226.132415,
"total_time": 480.478014
}
}Generated in
Using seed: 2244563620
The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.
0it [00:00, ?it/s]
0it [00:00, ?it/s]
/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
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: 2244563620
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 @ 0x7239ac0] Warning: data is not aligned! This can lead to a speed loss
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/src/magic-animate/samples/config-2023-12-08T05-30-28/videos/input_tmpqk3hj7h7hiphop-openpose.mp4