Detic
Code release for "Detecting Twenty-thousand Classes using Image-level Supervision". (by facebookresearch)
clipseg
This repository contains the code of the CVPR 2022 paper "Image Segmentation Using Text and Image Prompts". (by timojl)
| Detic | clipseg | |
|---|---|---|
| 11 | 7 | |
| 1,769 | 1,012 | |
| 1.0% | - | |
| 1.9 | 3.8 | |
| about 1 month ago | 4 months ago | |
| Python | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Detic
Posts with mentions or reviews of Detic.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-09-30.
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Autodistill: A new way to create CV models
Some of the foundation/base models include: * GroundedSAM (Segment Anything Model) * DETIC * GroundingDINO
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[P] Image search with localization and open-vocabulary reranking.
For localisation at search time I ended up using OWL-ViT. This worked really well. I did not try Detic or CLIPseg but would be interested to hear if anyone else has tried these?
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training object detector using classified images?
git clone https://github.com/facebookresearch/Detic cd Detic pip install -r requirements python demo.py --config-file configs/Detic_LCOCOI21k_CLIP_SwinB_896b32_4x_ft4x_max-size.yaml --input desk.jpg --output out.jpg --vocabulary lvis --opts MODEL.WEIGHTS models/Detic_LCOCOI21k_CLIP_SwinB_896b32_4x_ft4x_max-size.pth
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[P] Any object detection library
You might want to take a look at DETIC : https://github.com/facebookresearch/Detic (Open Vocabulary Object Detection, trained on thousands of classes)
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[P] Awesome Image Segmentation Project Based on Deep Learning (5.6k star)
Are there any open-label segmentation model included in this repo, like Detic or LSeg?
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[R] CLIP-Fields: Weakly Supervised Semantic Fields for Robotic Memory + Code + Robot demo
We made this using pretty recent advances in web-data pretrained models like Detic and LSeg for detection, CLIP for visual queries, and Sentence BERT for semantic queries. Our "database" is really a neural field (Instant NGP) that maps from 3D coordinates to a high dimensional embedding vector in the same representation space as CLIP and SBERT.
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[P] Using OpenAI's CLIP repository as a support, I was able to create a software to detect anything in an image at its original resolution!
Is it similar to the open vocabulary detic?
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Researchers at Meta and the University of Texas at Austin Propose ‘Detic’: A Method to Detect Twenty-Thousand Classes using Image-Level Supervision
Code for https://arxiv.org/abs/2201.02605 found: https://github.com/facebookresearch/Detic
- Detecting Twenty-thousand Classes using Image-level Supervision
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[R] Detecting Twenty-thousand Classes using Image-level Supervision
github: https://github.com/facebookresearch/Detic
clipseg
Posts with mentions or reviews of clipseg.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-12-08.
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How to blend a logo or clip art to a design
Following the comments to this old post, I tried to use in-painting with manual mask selection. I didn't get beautiful results but I'm sure with some tweaking, I could make it better. The main problem I had was having to manually select the area where I wanted to place the logo and trying to resize my logo mask to the fit the segment. I tried some automatic segmentation tools (Clipseg and Segment Anything). I couldn't tell the segmentation models to find a good area to for logo placement (i.e. some small flat surface). Given the complexity of what I was dealing with, I think there could be a better way (XY problem).
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New Feature: "ZOOM ENHANCE" for the A111 WebUI. Automatically fix small details like faces and hands!
The addon utilizes clipseg for region masking, which was trained on "an extended version of the PhraseCut dataset" (many thousands of images.)
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Txt2mask just received a big update!! 🎅
You'll also need to make sure to update your clipseg repo. The script won't do this for you. Namely you just need to update this models/clipseg.py file to ensure your clipseg has support for the new model.
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[P] Image search with localization and open-vocabulary reranking.
For localisation at search time I ended up using OWL-ViT. This worked really well. I did not try Detic or CLIPseg but would be interested to hear if anyone else has tried these?
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Who needs prompt2prompt anyway? SD 1.5 inpainting model with clipseg prompt for "hair" and various prompts for different hair colors
clipseg is an image segmentation method used to find a mask for an image from a prompt. I implemented it as an executor for dalle-flow and added it to my bot yasd-discord-bot.
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txt2mask working in imaginAIry python library
Automated Replacement (txt2mask) by clipseg
- txt2mask was just released! We don't have to use the brush tool for inpainting anymore!
What are some alternatives?
When comparing Detic and clipseg you can also consider the following projects:
GroundingDINO - Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
stable-diffusion - Latent Text-to-Image Diffusion
FasterRCNN - Clean and readable implementations of Faster R-CNN in PyTorch and TensorFlow 2 with Keras.
LAVIS - LAVIS - A One-stop Library for Language-Vision Intelligence
ultralytics - NEW - YOLOv8 🚀 in PyTorch > ONNX > OpenVINO > CoreML > TFLite
imaginAIry - Pythonic AI generation of images and videos
segment-anything - The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
txt2mask - Automatically create masks for Stable Diffusion inpainting using natural language.
super-gradients - Easily train or fine-tune SOTA computer vision models with one open source training library. The home of Yolo-NAS.
dalle-flow - 🌊 A Human-in-the-Loop workflow for creating HD images from text
sentence-transformers - Multilingual Sentence & Image Embeddings with BERT
unprompted - Templating language written for Stable Diffusion workflows. Available as an extension for the Automatic1111 WebUI.