FastMOT
darknet
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FastMOT | darknet | |
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2 | 62 | |
1,085 | 21,369 | |
- | - | |
0.0 | 7.0 | |
about 2 years ago | 24 days ago | |
Python | C | |
MIT License | GNU General Public License v3.0 or later |
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FastMOT
- Does Multi Object Tracking work better (precision/recall) on videos than jury rigging a SOTA image object detection to work on videos?
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Assign ID and track moving object with optical flow
On failure, you can try using a re-identification methods like FastReid: https://github.com/JDAI-CV/fast-reid in combination with your detector. A good pipeline that combines everything you seem to need is here: https://github.com/GeekAlexis/FastMOT. It uses a combination of Yolov4 (detector) + Kalman filters, Optical flow (tracker) and FastReid (re-identification)
darknet
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Anybody building ML models in C++?
YoloV3/4 is C based if that counts: https://github.com/AlexeyAB/darknet
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[D] Fixing the angle of Skewed Paintings, see comments
This is all well-known information, see any (and all!) previous discussions when YOLOv5 comes up. For details: https://github.com/AlexeyAB/darknet/issues/5920
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Viseron 2.0.0 - Self-hosted, local only NVR and AI Computer Vision software.
Yes it is official, it is in another repo however, but it is linked from the main repo https://github.com/AlexeyAB/darknet
- Machine learning Library in C?
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GPL vs MIT.
Still to long. Here's my favourite license: https://github.com/AlexeyAB/darknet/blob/master/LICENSE
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Pretrained model on aerial object detection
(As an aside, it isn't just that YOLOv5 is evil, the problem is YOLOv5 is both slower and less precise than YOLOv4, and even then, no-one can reproduce the performance results they claim to get.) Source: https://github.com/AlexeyAB/darknet/issues/5920
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[D][P] YOLOv6: state-of-the-art object detection at 1242 FPS
For a quick start on YOLOv3 / 4 follow the instructions here: https://github.com/AlexeyAB/darknet
- Does Multi Object Tracking work better (precision/recall) on videos than jury rigging a SOTA image object detection to work on videos?
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Which model is best for detecting small objects? Yolov3? MaskRCNN, Faster-RCNN?
YOLOv4-tiny-3L is what I use when I'm doing projects that require finding small objects. And for really tiny objects in large images where the object would be resized to zero (or near zero) due to network dimensions, then I use DarkHelp with tiling, combined with YOLOv4-tiny-3L. Depending on how precise the bounding boxes need to be, I also tend to use YOLOv4-tiny, which is faster but less precise than YOLO-v4-tiny-3L.
What are some alternatives?
yolov5 - YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
tensorflow-yolov4-tflite - YOLOv4, YOLOv4-tiny, YOLOv3, YOLOv3-tiny Implemented in Tensorflow 2.0, Android. Convert YOLO v4 .weights tensorflow, tensorrt and tflite
multi-object-tracker - Multi-object trackers in Python
Deep-SORT-YOLOv4 - People detection and optional tracking with Tensorflow backend.
tensorflow-yolo-v3 - Implementation of YOLO v3 object detector in Tensorflow (TF-Slim)
efficientdet-pytorch - A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weights
ByteTrack - [ECCV 2022] ByteTrack: Multi-Object Tracking by Associating Every Detection Box
fast-reid - SOTA Re-identification Methods and Toolbox
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
darknet_ros - YOLO ROS: Real-Time Object Detection for ROS
tensorflow-lite-YOLOv3 - YOLOv3: convert .weights to .tflite format for tensorflow lite. Convert .weights to .pb format for tensorflow serving
Alturos.Yolo - C# Yolo Darknet Wrapper (real-time object detection)