medicaldetectiontoolkit
PaddleDetection
medicaldetectiontoolkit | PaddleDetection | |
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2 | 7 | |
1,269 | 12,074 | |
0.3% | 0.9% | |
0.0 | 6.5 | |
29 days ago | 7 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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medicaldetectiontoolkit
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3D rcnn
Checkout https://github.com/MIC-DKFZ/medicaldetectiontoolkit, they have a recent 3d rcnn implementation. Their paper is a good start on the topic. Also have a look at nnDetection from the same group, it might provide some more leads. Hth
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3D Faster R-CNN for microscopy image analysis
I'm doing research in the area of biomedical image processing using deep learning. At the moment, I'm focused in the detection of biological structures in 3D microscopy images. For this task I trained a Faster R-CNN architecture, however I noticed that while the training loss is decreasing the validation loss is high, doesn't decrease and sometimes oscillates. When I looked at the results, the bounding boxes in the training and validation sets were too small but located at random spots. At first I thought that I should adjust the size of the anchors, however, even after trying different anchor sizes the results didn't improve. I would like to know if anyone has experience in working with 3D Faster R-CNN that could help me with suggestions for this project. (btw, I'm using the code available in this repo). Thanks in advance.
PaddleDetection
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[R]DETRs Beat YOLOs on Real-time Object Detection
Our RTDETR-L achieves 53.0% AP on COCO val2017 and 114 FPS on T4 GPU, while RT-DETR-X achieves 54.8% AP and 74 FPS, outperforming all YOLO detectors of the same scale in both speed and accuracy. Furthermore, our RTDETR-R50 achieves 53.1% AP and 108 FPS, outperforming DINO-Deformable-DETR->R50 by 2.2% AP in accuracy and by about 21 times in FPS. Source code and pretrained models will be available at PaddleDetection1 (https://github.com/PaddlePaddle/PaddleDetection) .
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YOLO series models ALL IN ONE
In order to make it easier for everyone to use the YOLO series model, we have open-sourced this collections. You can experience PP-YOLOE+, YOLOv8, RTMDet, DAMO-YOLO, YOLOv7, YOLOv6, YOLOX, YOLOv5...just in https://github.com/PaddlePaddle/PaddleDetection/blob/release/2.5/docs/feature_models/PaddleYOLO_MODEL_en.md
- YOLO series Models ALL IN ONE
- Paddledetection - Object detection toolkit based on paddlepaddle
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Baidu Researchers Propose PP-YOLOE Object Detector: an Evolved Version of YOLO Achieving SOTA Performance in Object Detection
Code for https://arxiv.org/abs/2203.16250 found: https://github.com/PaddlePaddle/PaddleDetection
Github: https://github.com/PaddlePaddle/PaddleDetection
- Imagine what historians will say about naming convention for pre trained models in 50 years…
What are some alternatives?
nnUNet
mmdetection - OpenMMLab Detection Toolbox and Benchmark
mmdetection3d - OpenMMLab's next-generation platform for general 3D object detection.
mmtracking - OpenMMLab Video Perception Toolbox. It supports Video Object Detection (VID), Multiple Object Tracking (MOT), Single Object Tracking (SOT), Video Instance Segmentation (VIS) with a unified framework.
Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0
faster-rcnn.pytorch - A faster pytorch implementation of faster r-cnn
BlenderProc - A procedural Blender pipeline for photorealistic training image generation
SOLO - SOLO and SOLOv2 for instance segmentation, ECCV 2020 & NeurIPS 2020.
MONAILabel - MONAI Label is an intelligent open source image labeling and learning tool.
BCNet - Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]
DeepSORT - support deepsort and bytetrack MOT(Multi-object tracking) using yolov5 with C++