huggingface / huggingface/transformers

Add DFFT

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New model
Dominant language
Python
Stars
166k
Forks
34.6k
Avg merge
3d 9h
Merged PRs (30d)
281

Description

Model description

DFFT is a new fully Transformer-based object detector. The model doesn't require a decoder, unlike DETR.

Open source status
  • The model implementation is available
  • The model weights are available
Provide useful links for the implementation

Paper: https://arxiv.org/abs/2206.06829

Github repo (and weights): https://github.com/Pealing/DFFT

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Read the DFFT paper and the upstream implementation and weights at https://github.com/Pealing/DFFT first. Then compare the model with existing object-detection integrations in Transformers; done means DFFT is implemented and its available weights can be used through the project.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, pytorch
Domain
computer-vision, machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
42/100

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