Skip to main content

Mimic Video

Project description

Mimic Video (wip)

Implementation of Mimic-Video, Video-Action Models for Generalizable Robot Control Beyond VLAs

Appreciation

  • Pranoy for submitting a pull request for proprioception masking

Install

$ pip install mimic-video

Usage

import torch

# video wrapper
# but will be agnostic to the model

from mimic_video.cosmos_predict import CosmosPredictWrapper

video_wrapper = CosmosPredictWrapper(
    extract_layer = 1,
    random_weights = True,
    tiny = True
)

# mimic video

from mimic_video import MimicVideo

model = MimicVideo(512, video_wrapper)

# states

video = torch.rand(2, 3, 3, 32, 32)

joint_state = torch.randn(2, 32)

# action

actions = torch.randn(2, 32, 20)

# training

loss = model(
    prompts = [
        'put the package on the conveyer belt',
        'pass the butter'
    ],
    video = video,
    actions = actions,
    joint_state = joint_state
)

loss.backward()

# inference

actions = model.sample(
    prompts = 'peel the orange',
    video = video[:1],
    joint_state = joint_state[:1]
)

assert actions.shape == (1, 32, 20)

Contributing

First make sure pytest and test dependencies are installed with

$ pip install '.[test]'

Then add your test to tests/test_mimic_video.py and run

$ pytest tests

That's it

Citations

@inproceedings{Pai2025mimicvideoVM,
    title   = {mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAs},
    author  = {Jonas Pai and Liam Achenbach and Victoriano Montesinos and Benedek Forrai and Oier Mees and Elvis Nava},
    year    = {2025},
    url     = {https://api.semanticscholar.org/CorpusID:283920528}
}
@misc{black2025trainingtimeactionconditioningefficient,
    title   = {Training-Time Action Conditioning for Efficient Real-Time Chunking}, 
    author  = {Kevin Black and Allen Z. Ren and Michael Equi and Sergey Levine},
    year    = {2025},
    eprint  = {2512.05964},
    archivePrefix = {arXiv},
    primaryClass = {cs.RO},
    url     = {https://arxiv.org/abs/2512.05964}, 
}

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mimic_video-0.0.26.tar.gz (780.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mimic_video-0.0.26-py3-none-any.whl (12.0 kB view details)

Uploaded Python 3

File details

Details for the file mimic_video-0.0.26.tar.gz.

File metadata

  • Download URL: mimic_video-0.0.26.tar.gz
  • Upload date:
  • Size: 780.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for mimic_video-0.0.26.tar.gz
Algorithm Hash digest
SHA256 1e7cd70f9b2b71358a15b90d3e8add328f6f9b4cf980ab55a81e75eb0d1df8e7
MD5 f8bd9e6071495890b1805cc93e53657f
BLAKE2b-256 b0e2854927207eea3f184135a4137e82c7ff0b303507b8c67d320b7269e1aaf6

See more details on using hashes here.

File details

Details for the file mimic_video-0.0.26-py3-none-any.whl.

File metadata

  • Download URL: mimic_video-0.0.26-py3-none-any.whl
  • Upload date:
  • Size: 12.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.9.25

File hashes

Hashes for mimic_video-0.0.26-py3-none-any.whl
Algorithm Hash digest
SHA256 311d54ed38e88dbe2f474a99871409a802d22d494bdad6a404859e2e6ca30b09
MD5 a2976edcdb7e80a0e9e14586e457f357
BLAKE2b-256 9e76ae212e1142b927db0d920ddbf4ed2f004f6ee993527d196e7f1f7293d0aa

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page