detrex
detectron2
| detrex | detectron2 | |
|---|---|---|
| 4 | 49 | |
| 1,821 | 28,744 | |
| 1.4% | 1.3% | |
| 7.2 | 7.6 | |
| 3 months ago | 7 days ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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detrex
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[R] detrex 0.2.0 release: New baselines for DETR models
Add model analyze tools and visualization for COCO eval results and annotations in tools
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detrex: the open source toolbox for Transformer based object detection algorithms
- [DETR (ECCV'2020)](https://github.com/IDEA-Research/detrex/tree/main/projects/detr)
Here's the github links: https://github.com/IDEA-Research/detrex
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[R] detrex: the open source toolbox for Transformer based object detection algorithms
detrex has already implemented the following algorithms: - DETR (ECCV'2020) - Deformable-DETR (ICLR'2021 Oral) - Conditional-DETR (ICCV'2021) - DAB-DETR (ICLR'2022) - DAB-Deformable-DETR (ICLR'2022) - DN-DETR (CVPR'2022 Oral) - DN-Deformable-DETR (CVPR'2022 Oral) - DINO (ArXiv'2022) - Group-DETR (ArXiv' 2022)
detectron2
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Ask HN: How to train an image recognition AI
I don’t do AI professionally but as a hobby, so this may not be the best way. But the way you described, it seems the user maybe taking the picture a bit further away and there may be other objects in the frame. So you may want to look into some sort of segmentation or have bounding box. This could help the user make sure they are looking at documents for the correct machine.
I think something like detectron2 [1] could help. It is Apache2 license, so commercial friendly. That said the pre-trained weights may not be used for commercial purposes, so you’ll want to check on that.
[1] https://github.com/facebookresearch/detectron2
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Instance segmentation of small objects in grainy drone imagery
And not enough true positives either. Add more augmentations in the config. Also make sure the config is set correctly, so that Detectron2 isn't skipping background images: https://github.com/facebookresearch/detectron2/issues/80
- Openpose alternatives (humanSD & Densepose)
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Probelms with importing tensormask from detectron2.projects
I followed the setup of https://github.com/facebookresearch/detectron2/tree/main/projects/TensorMask. But still I can not import it. As I can with from detectron2.projects import point_rend easily from PointRend projects
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Problems with Lazy Config detectron2 (MViTv2)
I have to use this config file with the dataloader which is in https://github.com/facebookresearch/detectron2/blob/main/projects/MViTv2/configs/common/coco_loader.py. I figured that i can use cfg.dataloader.train.dataset.names = "my_dataset_train" for this.
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"[D]" Problems with Lazy Config detectron2 (MViTv2)
I want to use this config file https://github.com/facebookresearch/detectron2/blob/main/projects/MViTv2/configs/mask_rcnn_mvitv2_t_3x.py like the beneath typical way I use a yaml config file. But giving so many errors one after another that, I even failed to count at this point.
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AI Real Time (lgd for cn)
Which is built on https://github.com/facebookresearch/detectron2
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List of AI-Models
Click to Learn more...
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good computer vision or deep learning projects in github
Detectron2 (GitHub: https://github.com/facebookresearch/detectron2) is a Facebook AI Research library with state-of-the-art object detection and segmentation algorithms in PyTorch.
- Object Detection using PyTorch: Would you recommend a Framework (Detectron2, MMDetection, ...) or a project from scratch ?
What are some alternatives?
yolov7_d2 - 🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
mmdetection - OpenMMLab Detection Toolbox and Benchmark
IkomiaApi - Deploy Computer Vision solutions with a few lines of code.
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
solo-learn - solo-learn: a library of self-supervised methods for visual representation learning powered by Pytorch Lightning
openpose - OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
U-2-Net - The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."
HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
rembg - Rembg is a tool to remove images background
deep-text-recognition-benchmark - Text recognition (optical character recognition) with deep learning methods, ICCV 2019