open_clip and cliport

CLIPort builds upon open_clip by using CLIP embeddings as its vision-language foundation for robotic manipulation tasks, making them complements rather than competitors.

open_clip
73
Verified
cliport
49
Emerging
Maintenance 13/25
Adoption 15/25
Maturity 25/25
Community 20/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 23/25
Stars: 13,496
Forks: 1,253
Downloads:
Commits (30d): 1
Language: Python
License:
Stars: 541
Forks: 94
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
No risk flags
Stale 6m No Package No Dependents

About open_clip

mlfoundations/open_clip

An open source implementation of CLIP.

This project provides pre-trained models that understand both images and text, allowing you to connect what you see with descriptive phrases. You can input an image and a list of text descriptions to get back probabilities of which description best matches the image. This is ideal for researchers or developers building applications that need to categorize images based on natural language or search for images using text.

image-text-matching zero-shot-classification multimodal-search computer-vision natural-language-processing

About cliport

cliport/cliport

CLIPort: What and Where Pathways for Robotic Manipulation

This project helps robotics engineers and researchers train robotic arms to perform complex tabletop manipulation tasks, such as stacking blocks or picking up specific objects. You provide demonstrations of the desired actions, and the system learns a language-conditioned policy, allowing the robot to understand and execute commands like "stack the red block on the blue block." The output is a trained robotic agent capable of precise object handling based on human instructions.

robotic-manipulation robot-training automation human-robot-interaction dexterous-robotics

Scores updated daily from GitHub, PyPI, and npm data. How scores work