yolov7
yolact
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| yolov7 | yolact | |
|---|---|---|
| 33 | 4 | |
| 12,681 | 4,924 | |
| - | - | |
| 4.0 | 0.0 | |
| 8 days ago | 6 months ago | |
| Jupyter Notebook | Python | |
| GNU General Public License v3.0 only | MIT License |
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yolov7
- FLaNK Stack Weekly 16 October 2023
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Train a ML model able to identify animal species
If you want something off-the-shelf, try YoloV7.
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A video based Latin dictionary: get what you see in Latin (beta) - What do you think?
The current dictionary is still in a beta state and has only been trained on 80 words (e.g. 'man', 'dog', 'car', 'keyboard', 'book', etc.; see list of words, see dataset). I used the object detection model Yolov7 (paper, all credits to them).
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[D] Extracting the class labels and bounding boxes for objects, from a YOLO7 model after converting to an ONNX model
(Please note, this is a re-post of my original question here, I think this subreddit might be more appropriate for asking this question)At work, we use Unity, we have a project that needs object detection and classification. We decided to use this YOLO7 model (for non-technical reasons, It had to be the exact same model as the company does have pre-trained weights for this exact model). However, Unity only supports ONNX so I exported the model as an ONNX model, using the code provided in the repo:
- Coding Question Help
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DL for the Web: Repository of Models
Github Projects offering pretrained weights and train / run scripts. Example
- [OC] Football Player 3D Pose Estimation using YOLOv7 and Matplotlib
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Finding a good Tiny Yolo to train in Python
The only project I found is this one that implements Yolov7
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Visualizing image augmentations from YOLOV7
I'm wondering if there's an efficient way to visualize the image augmentations from the Yolov7 hyperparameters list here
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Train YOLOv8 ObjectDetection on Custom Dataset Tutorial
yolov7: https://github.com/WongKinYiu/yolov7#performance
yolact
- YOLOv6: Redefine state-of-the-art for object detection
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Instance segmentation
YOLACT
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Advice needed
The Github repo is not highly structured and is probably written during the time of the author's research. Been using this for well over a year and does the job so well.
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A question on Instance Segmentation Labelling
I am using yolact : https://github.com/dbolya/yolact
What are some alternatives?
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
Mask_RCNN - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
edgetpu - Coral issue tracker (and legacy Edge TPU API source)
yolact_edge - The first competitive instance segmentation approach that runs on small edge devices at real-time speeds.
edgetpu-yolo - Minimal-dependency Yolov5 export and inference demonstration for the Google Coral EdgeTPU
yolov3-tf2 - YoloV3 Implemented in Tensorflow 2.0
YOLOv4 - Port of YOLOv4 to C# + TensorFlow
mmdetection - OpenMMLab Detection Toolbox and Benchmark
darknet - Convolutional Neural Networks
segmentation_models.pytorch - Segmentation models with pretrained backbones. PyTorch.
XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
yolo_tracking - BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models