detectron2
yolov5
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detectron2 | yolov5 | |
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48 | 128 | |
28,380 | 46,202 | |
1.6% | 2.8% | |
7.5 | 8.9 | |
6 days ago | 4 days ago | |
Python | Python | |
Apache License 2.0 | GNU Affero General Public License v3.0 |
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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
Similarly, I am using the more simple R50-FPN backbone (https://github.com/facebookresearch/detectron2/blob/main/MODEL_ZOO.md) which may be too simple for grainy, small object, segmentation tasks
Thank you, I will have a look at it. I'm not that knowledgeable about existing models. Detectron2 also provides different different backbones (https://github.com/facebookresearch/detectron2/blob/main/MODEL_ZOO.md). Is there a reason you recommend the segmentation-models library (apologies for the naive question)?
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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.
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Object Detection using PyTorch: Would you recommend a Framework (Detectron2, MMDetection, ...) or a project from scratch ?
That would be awesome. But I think that Detectron only provides RCNN, but I could be wrong. At least the model zoo on github looks like it.
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PyTorch 2.0 Release
I could fine-tune a Detectron2 model a few months ago using PyTorch and MPS backend [1]. I'd be interested if it's working yet.
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[P] Image search with localization and open-vocabulary reranking.
I wanted to have a few choices getting localization into image search (index and search time). I immediately thought of using a region proposal network (rpn) from mask-rcnn to create patches that can also be indexed and searched (and add the localisation). I figured it might be somewhat agnostic to classes. I did not want to use mmdetection or detectron2 due to their dependencies and just getting the rpn was not worth it. I was encouraged by the PyTorch native implementations of detection/segmentation models but ended up finding yolox the best.
yolov5
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Changing labels of default YOLOv5 model
I am using the default YOLOv5m6 model here with sahi/yolov5 library for my object detection project. I want to change just some of labels - for example when YOLO detects a human, I want it to label the human as "threat", not "person". Is there any way I can do it just changing some code, or I should train the model from scratch by just changing labels?
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SS: Events triggered no matter the detection zone specified
What I did is hand off my detections to an Nvidia GPU running Yolov5 https://github.com/ultralytics/yolov5 which does the triggering if it's an object class I'm interested in. Since Synology is always caching at least 5 seconds of camera video the 50-100mS delay of grabbing a frame and analyzing before triggering recording is fine. Wish they'd implement something like this.
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AMD ROCm 5.5 In The Process Of Being Released
this is about all I could find, maybe you've been getting different degrees of optimized python libs that do the image resizes. https://github.com/ultralytics/yolov5/issues/11469
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good computer vision or deep learning projects in github
YOLOv5 (GitHub: https://github.com/ultralytics/yolov5) is a fast, accurate object detection model with code for training, testing, deployment, and pre-trained weights.
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[D] Extracting the class labels and bounding boxes for objects, from a YOLO7 model after converting to an ONNX model
Those dimensions suggest you need to apply (i.e. roll your own) non-max suppresion to the outputs: relevant link
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Thought Dump About Recent AI Advancements And Palantir
- YOLOv5 https://github.com/ultralytics/yolov5 (open source, so not Palantir's)
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How to build computer vision dataset labeling team in-house
A team of annotators and the infrastructure described in this article I needed to label my dataset, which was collected from cameras on the road (30k+ photos). This dataset was necessary to train an object detection model on six classes: [person, car, bus, bicycle, motorcycle, truck]. I released the dataset, created in this manner, as open source, and it can be downloaded here (link) together with trained YOLOv5s and YOLOv5x models from a popular repository (link) using this dataset. The license is simple: "Use it well"!
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Flutter Object Detection App + YOLOV5 Model.
Before you can use YOLOv5 in your Flutter application, you'll need to train the model on your specific dataset. You can use an existing dataset or create your own dataset to train the model. For this post I am using the pretrained model of yolov5 available on https://github.com/ultralytics/yolov5 as we are performing object detection we need to converts the pretrained model weights to torchscript format.
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NotImplementedError (YOLOv5)
Thank you Link to the codefor taking the time to reply. I have modified the code as you suggested. And now I see the GPU being utilized. But the precision, recall, mAP is all zero. At least it displays as zero.
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NVIDIA Jetson AGX Orin is now compatible with balena
Read more here about how Theia Scientific is currently using the newest NVIDIA Jetson AGX Orin on their fleet of microscopes. Theia Scientific and Volkov Labs, improved the Jetson AGX Orin inference speeds up to 30FPS. The Jetson AGX Orin running YOLOv5 tripled the Frames-per-Second (FPS) compared with the latest Jetson AGX Xavier.
What are some alternatives?
mmdetection - OpenMMLab Detection Toolbox and Benchmark
darknet - YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
OpenCV - Open Source Computer Vision Library
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."
yolov5-crowdhuman - Head and Person detection using yolov5. Detection from crowd.
CenterNet - Object detection, 3D detection, and pose estimation using center point detection:
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
edge-tpu-tiny-yolo - Run Tiny YOLO-v3 on Google's Edge TPU USB Accelerator.