zsxkib / moore-animateanyone
Unofficial Re-Trained AnimateAnyone (Image + DWPose Video → Animated Video of Image)
Prediction
zsxkib/moore-animateanyone:c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2ID4e6ffnlb636eue2tlbed6zfizuStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 512
- height
- 768
- length
- 128
- guidance_scale
- 3.5
- sampling_steps
- 25
- motion_sequence
- reference_image
{ "width": 512, "height": 768, "length": 128, "guidance_scale": 3.5, "sampling_steps": 25, "motion_sequence": "https://replicate.delivery/pbxt/KFWQJTPDhFou0smS93XVLMlyVQIedFa2GiP4C1gfTaW5GnQF/anyone-video-5_kps.mp4", "reference_image": "https://replicate.delivery/pbxt/KFWQJsyppeXHrUBQnwo5PS4eaAFe0utu15cvH5TUSrKz3hOR/anyone-10.png" }Install Replicate’s Node.js client library:npm install replicateImport 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 zsxkib/moore-animateanyone using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/moore-animateanyone:c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2", { input: { width: 512, height: 768, length: 128, guidance_scale: 3.5, sampling_steps: 25, motion_sequence: "https://replicate.delivery/pbxt/KFWQJTPDhFou0smS93XVLMlyVQIedFa2GiP4C1gfTaW5GnQF/anyone-video-5_kps.mp4", reference_image: "https://replicate.delivery/pbxt/KFWQJsyppeXHrUBQnwo5PS4eaAFe0utu15cvH5TUSrKz3hOR/anyone-10.png" } } ); // 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 replicateImport the client:import replicateRun zsxkib/moore-animateanyone using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/moore-animateanyone:c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2", input={ "width": 512, "height": 768, "length": 128, "guidance_scale": 3.5, "sampling_steps": 25, "motion_sequence": "https://replicate.delivery/pbxt/KFWQJTPDhFou0smS93XVLMlyVQIedFa2GiP4C1gfTaW5GnQF/anyone-video-5_kps.mp4", "reference_image": "https://replicate.delivery/pbxt/KFWQJsyppeXHrUBQnwo5PS4eaAFe0utu15cvH5TUSrKz3hOR/anyone-10.png" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run zsxkib/moore-animateanyone 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": "zsxkib/moore-animateanyone:c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2", "input": { "width": 512, "height": 768, "length": 128, "guidance_scale": 3.5, "sampling_steps": 25, "motion_sequence": "https://replicate.delivery/pbxt/KFWQJTPDhFou0smS93XVLMlyVQIedFa2GiP4C1gfTaW5GnQF/anyone-video-5_kps.mp4", "reference_image": "https://replicate.delivery/pbxt/KFWQJsyppeXHrUBQnwo5PS4eaAFe0utu15cvH5TUSrKz3hOR/anyone-10.png" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-01-18T19:55:17.196823Z", "created_at": "2024-01-18T19:45:37.512459Z", "data_removed": false, "error": null, "id": "4e6ffnlb636eue2tlbed6zfizu", "input": { "width": 512, "height": 768, "length": 128, "guidance_scale": 3.5, "sampling_steps": 25, "motion_sequence": "https://replicate.delivery/pbxt/KFWQJTPDhFou0smS93XVLMlyVQIedFa2GiP4C1gfTaW5GnQF/anyone-video-5_kps.mp4", "reference_image": "https://replicate.delivery/pbxt/KFWQJsyppeXHrUBQnwo5PS4eaAFe0utu15cvH5TUSrKz3hOR/anyone-10.png" }, "logs": "Using seed: 22384\nSome weights of the model checkpoint were not used when initializing UNet2DConditionModel:\n['conv_norm_out.weight, conv_norm_out.bias, conv_out.weight, conv_out.bias']\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/torch/_utils.py:776: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\nreturn self.fget.__get__(instance, owner)()\n/src/src/pipelines/pipeline_pose2vid_long.py:406: 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.denoising_unet.in_channels\n 0%| | 0/25 [00:00<?, ?it/s]\n 4%|▍ | 1/25 [00:15<06:16, 15.70s/it]\n 8%|▊ | 2/25 [00:31<06:00, 15.68s/it]\n 12%|█▏ | 3/25 [00:47<05:45, 15.70s/it]\n 16%|█▌ | 4/25 [01:02<05:30, 15.72s/it]\n 20%|██ | 5/25 [01:18<05:14, 15.74s/it]\n 24%|██▍ | 6/25 [01:34<04:59, 15.77s/it]\n 28%|██▊ | 7/25 [01:50<04:44, 15.78s/it]\n 32%|███▏ | 8/25 [02:06<04:28, 15.80s/it]\n 36%|███▌ | 9/25 [02:21<04:13, 15.82s/it]\n 40%|████ | 10/25 [02:37<03:57, 15.83s/it]\n 44%|████▍ | 11/25 [02:53<03:41, 15.84s/it]\n 48%|████▊ | 12/25 [03:09<03:26, 15.85s/it]\n 52%|█████▏ | 13/25 [03:25<03:10, 15.86s/it]\n 56%|█████▌ | 14/25 [03:41<02:54, 15.86s/it]\n 60%|██████ | 15/25 [03:57<02:38, 15.86s/it]\n 64%|██████▍ | 16/25 [04:12<02:22, 15.86s/it]\n 68%|██████▊ | 17/25 [04:28<02:06, 15.87s/it]\n 72%|███████▏ | 18/25 [04:44<01:51, 15.87s/it]\n 76%|███████▌ | 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[00:09<00:00, 12.31it/s]\n 93%|█████████▎| 119/128 [00:09<00:00, 12.32it/s]\n 95%|█████████▍| 121/128 [00:09<00:00, 12.32it/s]\n 96%|█████████▌| 123/128 [00:09<00:00, 12.32it/s]\n 98%|█████████▊| 125/128 [00:09<00:00, 12.33it/s]\n 99%|█████████▉| 127/128 [00:10<00:00, 12.32it/s]\n100%|██████████| 128/128 [00:10<00:00, 12.60it/s]", "metrics": { "predict_time": 449.088264, "total_time": 579.684364 }, "output": "https://replicate.delivery/pbxt/aiZzJxBUfC14SSwYJ52eaWcdBGxGvIOuI8sblV4wptmkQzNSA/20240118T1955.mp4", "started_at": "2024-01-18T19:47:48.108559Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/4e6ffnlb636eue2tlbed6zfizu", "cancel": "https://api.replicate.com/v1/predictions/4e6ffnlb636eue2tlbed6zfizu/cancel" }, "version": "c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2" }Generated inUsing seed: 22384 Some weights of the model checkpoint were not used when initializing UNet2DConditionModel: ['conv_norm_out.weight, conv_norm_out.bias, conv_out.weight, conv_out.bias'] /root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/torch/_utils.py:776: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() return self.fget.__get__(instance, owner)() /src/src/pipelines/pipeline_pose2vid_long.py:406: 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.denoising_unet.in_channels 0%| | 0/25 [00:00<?, ?it/s] 4%|▍ | 1/25 [00:15<06:16, 15.70s/it] 8%|▊ | 2/25 [00:31<06:00, 15.68s/it] 12%|█▏ | 3/25 [00:47<05:45, 15.70s/it] 16%|█▌ | 4/25 [01:02<05:30, 15.72s/it] 20%|██ | 5/25 [01:18<05:14, 15.74s/it] 24%|██▍ | 6/25 [01:34<04:59, 15.77s/it] 28%|██▊ | 7/25 [01:50<04:44, 15.78s/it] 32%|███▏ | 8/25 [02:06<04:28, 15.80s/it] 36%|███▌ | 9/25 [02:21<04:13, 15.82s/it] 40%|████ | 10/25 [02:37<03:57, 15.83s/it] 44%|████▍ | 11/25 [02:53<03:41, 15.84s/it] 48%|████▊ | 12/25 [03:09<03:26, 15.85s/it] 52%|█████▏ | 13/25 [03:25<03:10, 15.86s/it] 56%|█████▌ | 14/25 [03:41<02:54, 15.86s/it] 60%|██████ | 15/25 [03:57<02:38, 15.86s/it] 64%|██████▍ | 16/25 [04:12<02:22, 15.86s/it] 68%|██████▊ | 17/25 [04:28<02:06, 15.87s/it] 72%|███████▏ | 18/25 [04:44<01:51, 15.87s/it] 76%|███████▌ | 19/25 [05:00<01:35, 15.87s/it] 80%|████████ | 20/25 [05:16<01:19, 15.87s/it] 84%|████████▍ | 21/25 [05:32<01:03, 15.87s/it] 88%|████████▊ | 22/25 [05:48<00:47, 15.87s/it] 92%|█████████▏| 23/25 [06:04<00:31, 15.87s/it] 96%|█████████▌| 24/25 [06:19<00:15, 15.87s/it] 100%|██████████| 25/25 [06:35<00:00, 15.87s/it] 100%|██████████| 25/25 [06:35<00:00, 15.83s/it] 0%| | 0/128 [00:00<?, ?it/s] 3%|▎ | 4/128 [00:00<00:03, 39.03it/s] 6%|▋ | 8/128 [00:00<00:06, 17.15it/s] 9%|▊ | 11/128 [00:00<00:07, 14.88it/s] 10%|█ | 13/128 [00:00<00:08, 14.10it/s] 12%|█▏ | 15/128 [00:00<00:08, 13.57it/s] 13%|█▎ | 17/128 [00:01<00:08, 13.20it/s] 15%|█▍ | 19/128 [00:01<00:08, 12.94it/s] 16%|█▋ | 21/128 [00:01<00:08, 12.75it/s] 18%|█▊ | 23/128 [00:01<00:08, 12.63it/s] 20%|█▉ | 25/128 [00:01<00:08, 12.52it/s] 21%|██ | 27/128 [00:01<00:08, 12.46it/s] 23%|██▎ | 29/128 [00:02<00:07, 12.42it/s] 24%|██▍ | 31/128 [00:02<00:07, 12.40it/s] 26%|██▌ | 33/128 [00:02<00:07, 12.38it/s] 27%|██▋ | 35/128 [00:02<00:07, 12.37it/s] 29%|██▉ | 37/128 [00:02<00:07, 12.37it/s] 30%|███ | 39/128 [00:02<00:07, 12.35it/s] 32%|███▏ | 41/128 [00:03<00:07, 12.34it/s] 34%|███▎ | 43/128 [00:03<00:06, 12.33it/s] 35%|███▌ | 45/128 [00:03<00:06, 12.32it/s] 37%|███▋ | 47/128 [00:03<00:06, 12.33it/s] 38%|███▊ | 49/128 [00:03<00:06, 12.33it/s] 40%|███▉ | 51/128 [00:03<00:06, 12.33it/s] 41%|████▏ | 53/128 [00:04<00:06, 12.33it/s] 43%|████▎ | 55/128 [00:04<00:05, 12.34it/s] 45%|████▍ | 57/128 [00:04<00:05, 12.34it/s] 46%|████▌ | 59/128 [00:04<00:05, 12.33it/s] 48%|████▊ | 61/128 [00:04<00:05, 12.33it/s] 49%|████▉ | 63/128 [00:04<00:05, 12.33it/s] 51%|█████ | 65/128 [00:05<00:05, 12.32it/s] 52%|█████▏ | 67/128 [00:05<00:04, 12.33it/s] 54%|█████▍ | 69/128 [00:05<00:04, 12.33it/s] 55%|█████▌ | 71/128 [00:05<00:04, 12.34it/s] 57%|█████▋ | 73/128 [00:05<00:04, 12.34it/s] 59%|█████▊ | 75/128 [00:05<00:04, 12.34it/s] 60%|██████ | 77/128 [00:06<00:04, 12.33it/s] 62%|██████▏ | 79/128 [00:06<00:03, 12.33it/s] 63%|██████▎ | 81/128 [00:06<00:03, 12.33it/s] 65%|██████▍ | 83/128 [00:06<00:03, 12.32it/s] 66%|██████▋ | 85/128 [00:06<00:03, 12.33it/s] 68%|██████▊ | 87/128 [00:06<00:03, 12.33it/s] 70%|██████▉ | 89/128 [00:06<00:03, 12.34it/s] 71%|███████ | 91/128 [00:07<00:02, 12.34it/s] 73%|███████▎ | 93/128 [00:07<00:02, 12.34it/s] 74%|███████▍ | 95/128 [00:07<00:02, 12.34it/s] 76%|███████▌ | 97/128 [00:07<00:02, 12.34it/s] 77%|███████▋ | 99/128 [00:07<00:02, 12.33it/s] 79%|███████▉ | 101/128 [00:07<00:02, 12.32it/s] 80%|████████ | 103/128 [00:08<00:02, 12.33it/s] 82%|████████▏ | 105/128 [00:08<00:01, 12.33it/s] 84%|████████▎ | 107/128 [00:08<00:01, 12.34it/s] 85%|████████▌ | 109/128 [00:08<00:01, 12.34it/s] 87%|████████▋ | 111/128 [00:08<00:01, 12.33it/s] 88%|████████▊ | 113/128 [00:08<00:01, 12.33it/s] 90%|████████▉ | 115/128 [00:09<00:01, 12.32it/s] 91%|█████████▏| 117/128 [00:09<00:00, 12.31it/s] 93%|█████████▎| 119/128 [00:09<00:00, 12.32it/s] 95%|█████████▍| 121/128 [00:09<00:00, 12.32it/s] 96%|█████████▌| 123/128 [00:09<00:00, 12.32it/s] 98%|█████████▊| 125/128 [00:09<00:00, 12.33it/s] 99%|█████████▉| 127/128 [00:10<00:00, 12.32it/s] 100%|██████████| 128/128 [00:10<00:00, 12.60it/s]Prediction
zsxkib/moore-animateanyone:c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2IDw6oass3b43qai6ipqpd7ppbdqqStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 512
- height
- 768
- length
- 128
- guidance_scale
- 3.5
- sampling_steps
- 10
- motion_sequence
- reference_image
{ "width": 512, "height": 768, "length": 128, "guidance_scale": 3.5, "sampling_steps": 10, "motion_sequence": "https://replicate.delivery/pbxt/KFWavU9wN1HEHYBiG9wpPL6VJwZgzSl9vPmfKQvYDsY6LatD/anyone-video-2_kps.mp4", "reference_image": "https://replicate.delivery/pbxt/KFWavcx9wpKViDRbTmQxUcpiJl9toskNO8SZhKpUaNukmDPu/anyone-2.png" }Install Replicate’s Node.js client library:npm install replicateImport 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 zsxkib/moore-animateanyone using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/moore-animateanyone:c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2", { input: { width: 512, height: 768, length: 128, guidance_scale: 3.5, sampling_steps: 10, motion_sequence: "https://replicate.delivery/pbxt/KFWavU9wN1HEHYBiG9wpPL6VJwZgzSl9vPmfKQvYDsY6LatD/anyone-video-2_kps.mp4", reference_image: "https://replicate.delivery/pbxt/KFWavcx9wpKViDRbTmQxUcpiJl9toskNO8SZhKpUaNukmDPu/anyone-2.png" } } ); // 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 replicateImport the client:import replicateRun zsxkib/moore-animateanyone using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/moore-animateanyone:c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2", input={ "width": 512, "height": 768, "length": 128, "guidance_scale": 3.5, "sampling_steps": 10, "motion_sequence": "https://replicate.delivery/pbxt/KFWavU9wN1HEHYBiG9wpPL6VJwZgzSl9vPmfKQvYDsY6LatD/anyone-video-2_kps.mp4", "reference_image": "https://replicate.delivery/pbxt/KFWavcx9wpKViDRbTmQxUcpiJl9toskNO8SZhKpUaNukmDPu/anyone-2.png" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run zsxkib/moore-animateanyone 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": "zsxkib/moore-animateanyone:c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2", "input": { "width": 512, "height": 768, "length": 128, "guidance_scale": 3.5, "sampling_steps": 10, "motion_sequence": "https://replicate.delivery/pbxt/KFWavU9wN1HEHYBiG9wpPL6VJwZgzSl9vPmfKQvYDsY6LatD/anyone-video-2_kps.mp4", "reference_image": "https://replicate.delivery/pbxt/KFWavcx9wpKViDRbTmQxUcpiJl9toskNO8SZhKpUaNukmDPu/anyone-2.png" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-01-18T20:01:12.925631Z", "created_at": "2024-01-18T19:56:49.898528Z", "data_removed": false, "error": null, "id": "w6oass3b43qai6ipqpd7ppbdqq", "input": { "width": 512, "height": 768, "length": 128, "guidance_scale": 3.5, "sampling_steps": 10, "motion_sequence": "https://replicate.delivery/pbxt/KFWavU9wN1HEHYBiG9wpPL6VJwZgzSl9vPmfKQvYDsY6LatD/anyone-video-2_kps.mp4", "reference_image": "https://replicate.delivery/pbxt/KFWavcx9wpKViDRbTmQxUcpiJl9toskNO8SZhKpUaNukmDPu/anyone-2.png" }, "logs": "Using seed: 36146\nSome weights of the model checkpoint were not used when initializing UNet2DConditionModel:\n['conv_norm_out.weight, conv_norm_out.bias, conv_out.weight, conv_out.bias']\n/root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/torch/_utils.py:776: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\nreturn self.fget.__get__(instance, owner)()\n/src/src/pipelines/pipeline_pose2vid_long.py:406: 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.denoising_unet.in_channels\n 0%| | 0/10 [00:00<?, ?it/s]\n 10%|█ | 1/10 [00:15<02:21, 15.69s/it]\n 20%|██ | 2/10 [00:31<02:05, 15.67s/it]\n 30%|███ | 3/10 [00:47<01:49, 15.70s/it]\n 40%|████ | 4/10 [01:02<01:34, 15.72s/it]\n 50%|█████ | 5/10 [01:18<01:18, 15.74s/it]\n 60%|██████ | 6/10 [01:34<01:03, 15.77s/it]\n 70%|███████ | 7/10 [01:50<00:47, 15.79s/it]\n 80%|████████ | 8/10 [02:06<00:31, 15.81s/it]\n 90%|█████████ | 9/10 [02:21<00:15, 15.82s/it]\n100%|██████████| 10/10 [02:37<00:00, 15.83s/it]\n100%|██████████| 10/10 [02:37<00:00, 15.78s/it]\n 0%| | 0/128 [00:00<?, ?it/s]\n 4%|▍ | 5/128 [00:00<00:04, 29.52it/s]\n 6%|▋ | 8/128 [00:00<00:06, 17.97it/s]\n 8%|▊ | 10/128 [00:00<00:07, 15.78it/s]\n 9%|▉ | 12/128 [00:00<00:07, 14.54it/s]\n 11%|█ | 14/128 [00:00<00:08, 13.79it/s]\n 12%|█▎ | 16/128 [00:01<00:08, 13.31it/s]\n 14%|█▍ | 18/128 [00:01<00:08, 12.99it/s]\n 16%|█▌ | 20/128 [00:01<00:08, 12.78it/s]\n 17%|█▋ | 22/128 [00:01<00:08, 12.63it/s]\n 19%|█▉ | 24/128 [00:01<00:08, 12.54it/s]\n 20%|██ | 26/128 [00:01<00:08, 12.48it/s]\n 22%|██▏ | 28/128 [00:02<00:08, 12.44it/s]\n 23%|██▎ | 30/128 [00:02<00:07, 12.40it/s]\n 25%|██▌ | 32/128 [00:02<00:07, 12.37it/s]\n 27%|██▋ | 34/128 [00:02<00:07, 12.36it/s]\n 28%|██▊ | 36/128 [00:02<00:07, 12.34it/s]\n 30%|██▉ | 38/128 [00:02<00:07, 12.34it/s]\n 31%|███▏ | 40/128 [00:03<00:07, 12.34it/s]\n 33%|███▎ | 42/128 [00:03<00:06, 12.34it/s]\n 34%|███▍ | 44/128 [00:03<00:06, 12.34it/s]\n 36%|███▌ | 46/128 [00:03<00:06, 12.34it/s]\n 38%|███▊ | 48/128 [00:03<00:06, 12.34it/s]\n 39%|███▉ | 50/128 [00:03<00:06, 12.32it/s]\n 41%|████ | 52/128 [00:03<00:06, 12.32it/s]\n 42%|████▏ | 54/128 [00:04<00:06, 12.32it/s]\n 44%|████▍ | 56/128 [00:04<00:05, 12.32it/s]\n 45%|████▌ | 58/128 [00:04<00:05, 12.33it/s]\n 47%|████▋ | 60/128 [00:04<00:05, 12.33it/s]\n 48%|████▊ | 62/128 [00:04<00:05, 12.32it/s]\n 50%|█████ | 64/128 [00:04<00:05, 12.32it/s]\n 52%|█████▏ | 66/128 [00:05<00:05, 12.32it/s]\n 53%|█████▎ | 68/128 [00:05<00:04, 12.31it/s]\n 55%|█████▍ | 70/128 [00:05<00:04, 12.30it/s]\n 56%|█████▋ | 72/128 [00:05<00:04, 12.30it/s]\n 58%|█████▊ | 74/128 [00:05<00:04, 12.31it/s]\n 59%|█████▉ | 76/128 [00:05<00:04, 12.32it/s]\n 61%|██████ | 78/128 [00:06<00:04, 12.33it/s]\n 62%|██████▎ | 80/128 [00:06<00:03, 12.33it/s]\n 64%|██████▍ | 82/128 [00:06<00:03, 12.33it/s]\n 66%|██████▌ | 84/128 [00:06<00:03, 12.32it/s]\n 67%|██████▋ | 86/128 [00:06<00:03, 12.31it/s]\n 69%|██████▉ | 88/128 [00:06<00:03, 12.32it/s]\n 70%|███████ | 90/128 [00:07<00:03, 12.32it/s]\n 72%|███████▏ | 92/128 [00:07<00:02, 12.32it/s]\n 73%|███████▎ | 94/128 [00:07<00:02, 12.32it/s]\n 75%|███████▌ | 96/128 [00:07<00:02, 12.33it/s]\n 77%|███████▋ | 98/128 [00:07<00:02, 12.33it/s]\n 78%|███████▊ | 100/128 [00:07<00:02, 12.32it/s]\n 80%|███████▉ | 102/128 [00:08<00:02, 12.32it/s]\n 81%|████████▏ | 104/128 [00:08<00:01, 12.31it/s]\n 83%|████████▎ | 106/128 [00:08<00:01, 12.31it/s]\n 84%|████████▍ | 108/128 [00:08<00:01, 12.32it/s]\n 86%|████████▌ | 110/128 [00:08<00:01, 12.33it/s]\n 88%|████████▊ | 112/128 [00:08<00:01, 12.34it/s]\n 89%|████████▉ | 114/128 [00:09<00:01, 12.34it/s]\n 91%|█████████ | 116/128 [00:09<00:00, 12.33it/s]\n 92%|█████████▏| 118/128 [00:09<00:00, 12.32it/s]\n 94%|█████████▍| 120/128 [00:09<00:00, 12.32it/s]\n 95%|█████████▌| 122/128 [00:09<00:00, 12.32it/s]\n 97%|█████████▋| 124/128 [00:09<00:00, 12.33it/s]\n 98%|█████████▊| 126/128 [00:09<00:00, 12.33it/s]\n100%|██████████| 128/128 [00:10<00:00, 12.33it/s]\n100%|██████████| 128/128 [00:10<00:00, 12.61it/s]", "metrics": { "predict_time": 195.519423, "total_time": 263.027103 }, "output": "https://replicate.delivery/pbxt/QWgDhgdLwwIwJRhR6kuit3DmeLk6OZMApDRZ6e6dU1QIWzNSA/20240118T2001.mp4", "started_at": "2024-01-18T19:57:57.406208Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/w6oass3b43qai6ipqpd7ppbdqq", "cancel": "https://api.replicate.com/v1/predictions/w6oass3b43qai6ipqpd7ppbdqq/cancel" }, "version": "c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2" }Generated inUsing seed: 36146 Some weights of the model checkpoint were not used when initializing UNet2DConditionModel: ['conv_norm_out.weight, conv_norm_out.bias, conv_out.weight, conv_out.bias'] /root/.pyenv/versions/3.11.7/lib/python3.11/site-packages/torch/_utils.py:776: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage() return self.fget.__get__(instance, owner)() /src/src/pipelines/pipeline_pose2vid_long.py:406: 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.denoising_unet.in_channels 0%| | 0/10 [00:00<?, ?it/s] 10%|█ | 1/10 [00:15<02:21, 15.69s/it] 20%|██ | 2/10 [00:31<02:05, 15.67s/it] 30%|███ | 3/10 [00:47<01:49, 15.70s/it] 40%|████ | 4/10 [01:02<01:34, 15.72s/it] 50%|█████ | 5/10 [01:18<01:18, 15.74s/it] 60%|██████ | 6/10 [01:34<01:03, 15.77s/it] 70%|███████ | 7/10 [01:50<00:47, 15.79s/it] 80%|████████ | 8/10 [02:06<00:31, 15.81s/it] 90%|█████████ | 9/10 [02:21<00:15, 15.82s/it] 100%|██████████| 10/10 [02:37<00:00, 15.83s/it] 100%|██████████| 10/10 [02:37<00:00, 15.78s/it] 0%| | 0/128 [00:00<?, ?it/s] 4%|▍ | 5/128 [00:00<00:04, 29.52it/s] 6%|▋ | 8/128 [00:00<00:06, 17.97it/s] 8%|▊ | 10/128 [00:00<00:07, 15.78it/s] 9%|▉ | 12/128 [00:00<00:07, 14.54it/s] 11%|█ | 14/128 [00:00<00:08, 13.79it/s] 12%|█▎ | 16/128 [00:01<00:08, 13.31it/s] 14%|█▍ | 18/128 [00:01<00:08, 12.99it/s] 16%|█▌ | 20/128 [00:01<00:08, 12.78it/s] 17%|█▋ | 22/128 [00:01<00:08, 12.63it/s] 19%|█▉ | 24/128 [00:01<00:08, 12.54it/s] 20%|██ | 26/128 [00:01<00:08, 12.48it/s] 22%|██▏ | 28/128 [00:02<00:08, 12.44it/s] 23%|██▎ | 30/128 [00:02<00:07, 12.40it/s] 25%|██▌ | 32/128 [00:02<00:07, 12.37it/s] 27%|██▋ | 34/128 [00:02<00:07, 12.36it/s] 28%|██▊ | 36/128 [00:02<00:07, 12.34it/s] 30%|██▉ | 38/128 [00:02<00:07, 12.34it/s] 31%|███▏ | 40/128 [00:03<00:07, 12.34it/s] 33%|███▎ | 42/128 [00:03<00:06, 12.34it/s] 34%|███▍ | 44/128 [00:03<00:06, 12.34it/s] 36%|███▌ | 46/128 [00:03<00:06, 12.34it/s] 38%|███▊ | 48/128 [00:03<00:06, 12.34it/s] 39%|███▉ | 50/128 [00:03<00:06, 12.32it/s] 41%|████ | 52/128 [00:03<00:06, 12.32it/s] 42%|████▏ | 54/128 [00:04<00:06, 12.32it/s] 44%|████▍ | 56/128 [00:04<00:05, 12.32it/s] 45%|████▌ | 58/128 [00:04<00:05, 12.33it/s] 47%|████▋ | 60/128 [00:04<00:05, 12.33it/s] 48%|████▊ | 62/128 [00:04<00:05, 12.32it/s] 50%|█████ | 64/128 [00:04<00:05, 12.32it/s] 52%|█████▏ | 66/128 [00:05<00:05, 12.32it/s] 53%|█████▎ | 68/128 [00:05<00:04, 12.31it/s] 55%|█████▍ | 70/128 [00:05<00:04, 12.30it/s] 56%|█████▋ | 72/128 [00:05<00:04, 12.30it/s] 58%|█████▊ | 74/128 [00:05<00:04, 12.31it/s] 59%|█████▉ | 76/128 [00:05<00:04, 12.32it/s] 61%|██████ | 78/128 [00:06<00:04, 12.33it/s] 62%|██████▎ | 80/128 [00:06<00:03, 12.33it/s] 64%|██████▍ | 82/128 [00:06<00:03, 12.33it/s] 66%|██████▌ | 84/128 [00:06<00:03, 12.32it/s] 67%|██████▋ | 86/128 [00:06<00:03, 12.31it/s] 69%|██████▉ | 88/128 [00:06<00:03, 12.32it/s] 70%|███████ | 90/128 [00:07<00:03, 12.32it/s] 72%|███████▏ | 92/128 [00:07<00:02, 12.32it/s] 73%|███████▎ | 94/128 [00:07<00:02, 12.32it/s] 75%|███████▌ | 96/128 [00:07<00:02, 12.33it/s] 77%|███████▋ | 98/128 [00:07<00:02, 12.33it/s] 78%|███████▊ | 100/128 [00:07<00:02, 12.32it/s] 80%|███████▉ | 102/128 [00:08<00:02, 12.32it/s] 81%|████████▏ | 104/128 [00:08<00:01, 12.31it/s] 83%|████████▎ | 106/128 [00:08<00:01, 12.31it/s] 84%|████████▍ | 108/128 [00:08<00:01, 12.32it/s] 86%|████████▌ | 110/128 [00:08<00:01, 12.33it/s] 88%|████████▊ | 112/128 [00:08<00:01, 12.34it/s] 89%|████████▉ | 114/128 [00:09<00:01, 12.34it/s] 91%|█████████ | 116/128 [00:09<00:00, 12.33it/s] 92%|█████████▏| 118/128 [00:09<00:00, 12.32it/s] 94%|█████████▍| 120/128 [00:09<00:00, 12.32it/s] 95%|█████████▌| 122/128 [00:09<00:00, 12.32it/s] 97%|█████████▋| 124/128 [00:09<00:00, 12.33it/s] 98%|█████████▊| 126/128 [00:09<00:00, 12.33it/s] 100%|██████████| 128/128 [00:10<00:00, 12.33it/s] 100%|██████████| 128/128 [00:10<00:00, 12.61it/s]Prediction
zsxkib/moore-animateanyone:c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2IDpjr4xntbk7hetovahfsv474o3iStatusSucceededSourceWebHardwareA40 (Large)Total durationCreatedInput
- width
- 512
- height
- 768
- length
- 128
- guidance_scale
- 3.5
- sampling_steps
- 50
- motion_sequence
- reference_image
{ "width": 512, "height": 768, "length": 128, "guidance_scale": 3.5, "sampling_steps": 50, "motion_sequence": "https://replicate.delivery/pbxt/KFWiTCptFa0zbnNMGwsRtUQBtx38ttv6TQwuBZGLfgKWAYHZ/anyone-video-2_kps.mp4", "reference_image": "https://replicate.delivery/pbxt/KFWiSo2bKmo2poY6QStNcJMaHy90LlkLggSlPb20iTpvD4UL/anyone-2.png" }Install Replicate’s Node.js client library:npm install replicateImport 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 zsxkib/moore-animateanyone using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run( "zsxkib/moore-animateanyone:c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2", { input: { width: 512, height: 768, length: 128, guidance_scale: 3.5, sampling_steps: 50, motion_sequence: "https://replicate.delivery/pbxt/KFWiTCptFa0zbnNMGwsRtUQBtx38ttv6TQwuBZGLfgKWAYHZ/anyone-video-2_kps.mp4", reference_image: "https://replicate.delivery/pbxt/KFWiSo2bKmo2poY6QStNcJMaHy90LlkLggSlPb20iTpvD4UL/anyone-2.png" } } ); // 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 replicateImport the client:import replicateRun zsxkib/moore-animateanyone using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run( "zsxkib/moore-animateanyone:c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2", input={ "width": 512, "height": 768, "length": 128, "guidance_scale": 3.5, "sampling_steps": 50, "motion_sequence": "https://replicate.delivery/pbxt/KFWiTCptFa0zbnNMGwsRtUQBtx38ttv6TQwuBZGLfgKWAYHZ/anyone-video-2_kps.mp4", "reference_image": "https://replicate.delivery/pbxt/KFWiSo2bKmo2poY6QStNcJMaHy90LlkLggSlPb20iTpvD4UL/anyone-2.png" } ) print(output)To learn more, take a look at the guide on getting started with Python.
Run zsxkib/moore-animateanyone 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": "zsxkib/moore-animateanyone:c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2", "input": { "width": 512, "height": 768, "length": 128, "guidance_scale": 3.5, "sampling_steps": 50, "motion_sequence": "https://replicate.delivery/pbxt/KFWiTCptFa0zbnNMGwsRtUQBtx38ttv6TQwuBZGLfgKWAYHZ/anyone-video-2_kps.mp4", "reference_image": "https://replicate.delivery/pbxt/KFWiSo2bKmo2poY6QStNcJMaHy90LlkLggSlPb20iTpvD4UL/anyone-2.png" } }' \ https://api.replicate.com/v1/predictionsTo learn more, take a look at Replicate’s HTTP API reference docs.
Output
{ "completed_at": "2024-01-18T20:18:15.038682Z", "created_at": "2024-01-18T20:04:46.499260Z", "data_removed": false, "error": null, "id": "pjr4xntbk7hetovahfsv474o3i", "input": { "width": 512, "height": 768, "length": 128, "guidance_scale": 3.5, "sampling_steps": 50, "motion_sequence": "https://replicate.delivery/pbxt/KFWiTCptFa0zbnNMGwsRtUQBtx38ttv6TQwuBZGLfgKWAYHZ/anyone-video-2_kps.mp4", "reference_image": "https://replicate.delivery/pbxt/KFWiSo2bKmo2poY6QStNcJMaHy90LlkLggSlPb20iTpvD4UL/anyone-2.png" }, "logs": "Using seed: 43447\n 0%| | 0/50 [00:00<?, ?it/s]\n 2%|▏ | 1/50 [00:15<12:50, 15.73s/it]\n 4%|▍ | 2/50 [00:31<12:34, 15.71s/it]\n 6%|▌ | 3/50 [00:47<12:18, 15.72s/it]\n 8%|▊ | 4/50 [01:02<12:03, 15.73s/it]\n 10%|█ | 5/50 [01:18<11:48, 15.75s/it]\n 12%|█▏ | 6/50 [01:34<11:33, 15.77s/it]\n 14%|█▍ | 7/50 [01:50<11:18, 15.79s/it]\n 16%|█▌ | 8/50 [02:06<11:03, 15.80s/it]\n 18%|█▊ | 9/50 [02:22<10:48, 15.82s/it]\n 20%|██ | 10/50 [02:37<10:33, 15.83s/it]\n 22%|██▏ | 11/50 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[08:42<04:29, 15.88s/it]\n 68%|██████▊ | 34/50 [08:58<04:14, 15.88s/it]\n 70%|███████ | 35/50 [09:14<03:58, 15.88s/it]\n 72%|███████▏ | 36/50 [09:30<03:42, 15.88s/it]\n 74%|███████▍ | 37/50 [09:46<03:26, 15.87s/it]\n 76%|███████▌ | 38/50 [10:02<03:10, 15.87s/it]\n 78%|███████▊ | 39/50 [10:18<02:54, 15.88s/it]\n 80%|████████ | 40/50 [10:34<02:38, 15.88s/it]\n 82%|████████▏ | 41/50 [10:49<02:22, 15.88s/it]\n 84%|████████▍ | 42/50 [11:05<02:07, 15.88s/it]\n 86%|████████▌ | 43/50 [11:21<01:51, 15.88s/it]\n 88%|████████▊ | 44/50 [11:37<01:35, 15.88s/it]\n 90%|█████████ | 45/50 [11:53<01:19, 15.88s/it]\n 92%|█████████▏| 46/50 [12:09<01:03, 15.88s/it]\n 94%|█████████▍| 47/50 [12:25<00:47, 15.88s/it]\n 96%|█████████▌| 48/50 [12:41<00:31, 15.88s/it]\n 98%|█████████▊| 49/50 [12:57<00:15, 15.88s/it]\n100%|██████████| 50/50 [13:12<00:00, 15.88s/it]\n100%|██████████| 50/50 [13:12<00:00, 15.86s/it]\n 0%| | 0/128 [00:00<?, ?it/s]\n 4%|▍ | 5/128 [00:00<00:04, 30.69it/s]\n 7%|▋ | 9/128 [00:00<00:06, 17.13it/s]\n 9%|▊ | 11/128 [00:00<00:07, 15.47it/s]\n 10%|█ | 13/128 [00:00<00:07, 14.43it/s]\n 12%|█▏ | 15/128 [00:00<00:08, 13.75it/s]\n 13%|█▎ | 17/128 [00:01<00:08, 13.30it/s]\n 15%|█▍ | 19/128 [00:01<00:08, 12.99it/s]\n 16%|█▋ | 21/128 [00:01<00:08, 12.79it/s]\n 18%|█▊ | 23/128 [00:01<00:08, 12.65it/s]\n 20%|█▉ | 25/128 [00:01<00:08, 12.56it/s]\n 21%|██ | 27/128 [00:01<00:08, 12.49it/s]\n 23%|██▎ | 29/128 [00:02<00:07, 12.45it/s]\n 24%|██▍ | 31/128 [00:02<00:07, 12.42it/s]\n 26%|██▌ | 33/128 [00:02<00:07, 12.39it/s]\n 27%|██▋ | 35/128 [00:02<00:07, 12.36it/s]\n 29%|██▉ | 37/128 [00:02<00:07, 12.34it/s]\n 30%|███ | 39/128 [00:02<00:07, 12.33it/s]\n 32%|███▏ | 41/128 [00:03<00:07, 12.33it/s]\n 34%|███▎ | 43/128 [00:03<00:06, 12.34it/s]\n 35%|███▌ | 45/128 [00:03<00:06, 12.34it/s]\n 37%|███▋ | 47/128 [00:03<00:06, 12.33it/s]\n 38%|███▊ | 49/128 [00:03<00:06, 12.34it/s]\n 40%|███▉ | 51/128 [00:03<00:06, 12.33it/s]\n 41%|████▏ | 53/128 [00:04<00:06, 12.33it/s]\n 43%|████▎ | 55/128 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[00:07<00:02, 12.34it/s]\n 77%|███████▋ | 99/128 [00:07<00:02, 12.33it/s]\n 79%|███████▉ | 101/128 [00:07<00:02, 12.33it/s]\n 80%|████████ | 103/128 [00:08<00:02, 12.34it/s]\n 82%|████████▏ | 105/128 [00:08<00:01, 12.32it/s]\n 84%|████████▎ | 107/128 [00:08<00:01, 12.31it/s]\n 85%|████████▌ | 109/128 [00:08<00:01, 12.31it/s]\n 87%|████████▋ | 111/128 [00:08<00:01, 12.32it/s]\n 88%|████████▊ | 113/128 [00:08<00:01, 12.33it/s]\n 90%|████████▉ | 115/128 [00:09<00:01, 12.33it/s]\n 91%|█████████▏| 117/128 [00:09<00:00, 12.34it/s]\n 93%|█████████▎| 119/128 [00:09<00:00, 12.34it/s]\n 95%|█████████▍| 121/128 [00:09<00:00, 12.34it/s]\n 96%|█████████▌| 123/128 [00:09<00:00, 12.32it/s]\n 98%|█████████▊| 125/128 [00:09<00:00, 12.32it/s]\n 99%|█████████▉| 127/128 [00:10<00:00, 12.32it/s]\n100%|██████████| 128/128 [00:10<00:00, 12.62it/s]", "metrics": { "predict_time": 808.478373, "total_time": 808.539422 }, "output": "https://replicate.delivery/pbxt/ESP3WuTfPCQpPScIOw8fyirewSeHCelUdC7uKKXeZCYph5cjE/20240118T2018.mp4", "started_at": "2024-01-18T20:04:46.560309Z", "status": "succeeded", "urls": { "get": "https://api.replicate.com/v1/predictions/pjr4xntbk7hetovahfsv474o3i", "cancel": "https://api.replicate.com/v1/predictions/pjr4xntbk7hetovahfsv474o3i/cancel" }, "version": "c8b589961b86d3fdffeef13e26fa8465b1935ac3350f2a332dddc1ee4be50df2" }Generated inUsing seed: 43447 0%| | 0/50 [00:00<?, ?it/s] 2%|▏ | 1/50 [00:15<12:50, 15.73s/it] 4%|▍ | 2/50 [00:31<12:34, 15.71s/it] 6%|▌ | 3/50 [00:47<12:18, 15.72s/it] 8%|▊ | 4/50 [01:02<12:03, 15.73s/it] 10%|█ | 5/50 [01:18<11:48, 15.75s/it] 12%|█▏ | 6/50 [01:34<11:33, 15.77s/it] 14%|█▍ | 7/50 [01:50<11:18, 15.79s/it] 16%|█▌ | 8/50 [02:06<11:03, 15.80s/it] 18%|█▊ | 9/50 [02:22<10:48, 15.82s/it] 20%|██ | 10/50 [02:37<10:33, 15.83s/it] 22%|██▏ | 11/50 [02:53<10:17, 15.84s/it] 24%|██▍ | 12/50 [03:09<10:02, 15.85s/it] 26%|██▌ | 13/50 [03:25<09:46, 15.86s/it] 28%|██▊ | 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