mmdetection3d
yolov3
| mmdetection3d | yolov3 | |
|---|---|---|
| 3 | 4 | |
| 4,815 | 10,000 | |
| 2.2% | 0.4% | |
| 7.1 | 8.4 | |
| 13 days ago | 6 days ago | |
| Python | Python | |
| Apache License 2.0 | GNU Affero General Public License v3.0 |
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mmdetection3d
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What's the best model to get monocular 3d angle info
There are bunch of methods in this codebase, check it out. https://github.com/open-mmlab/mmdetection3d
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MMDeploy: Deploy All the Algorithms of OpenMMLab
MMDetection3D: OpenMMLab's next-generation platform for general 3D object detection.
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Master thesis on autonomous vehicles (cybersecurity aspect)
You create and test the attacks on datasets like Kitti, NuScenes, and many others. Basically you try to manipulate the input to a certain detection pipeline for example (You can find a lot of LiDAR and camera based detection pipelines here: https://github.com/open-mmlab/mmdetection3d and here https://github.com/open-mmlab/mmdetection). You try to manipulate the input so that it deceives the car to do what you need without having control to the car itself.
yolov3
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[Tutorial] "Fine Tuning" Stable Diffusion using only 5 Images Using Textual Inversion.
Hey. I only have experience using the official repository, and only use Linux. Could you try the solutions here and see if it helps? https://github.com/ultralytics/yolov3/issues/1643
- How to train a model for object detection in Golang?
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Engineering Student AI model turns sign language to English in real time.
YOLOv3: https://github.com/ultralytics/yolov3
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I don't know how to train a YOLO v3 model with some custom data that is labeled in an unusual form (XML files)
Each image has an XML file associated with it. The XML files have the corresponding labels and bounding boxes, so I can write a script to convert them into this form, and follow this tutorial on training custom data.
What are some alternatives?
mmdetection - OpenMMLab Detection Toolbox and Benchmark
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
yolov7 - Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
medicaldetectiontoolkit - The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
yolov7_d2 - 🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
3d-multi-resolution-rcnn - Official PyTorch implementaiton of the paper "3D Instance Segmentation Framework for Cerebral Microbleeds using 3D Multi-Resolution R-CNN."
HASS-Deepstack-object - Home Assistant custom component for using Deepstack object detection
autogluon - Fast and Accurate ML in 3 Lines of Code
yolov5-crowdhuman - Head and Person detection using yolov5. Detection from crowd.
SimpleView - Official Code for ICML 2021 paper "Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline"
tensorflow-yolo-v3 - Implementation of YOLO v3 object detector in Tensorflow (TF-Slim)