deep_sort_pytorch
yolov7
Our great sponsors
| deep_sort_pytorch | yolov7 | |
|---|---|---|
| 1 | 33 | |
| 2,705 | 12,715 | |
| - | - | |
| 0.0 | 3.2 | |
| 7 months ago | 13 days ago | |
| Python | Jupyter Notebook | |
| MIT License | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
deep_sort_pytorch
-
DeepSort with PyTorch(support yolo series)
ZQPei/deep_sort_pytorch
yolov7
- FLaNK Stack Weekly 16 October 2023
-
Train a ML model able to identify animal species
If you want something off-the-shelf, try YoloV7.
-
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).
-
[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
-
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
-
Finding a good Tiny Yolo to train in Python
The only project I found is this one that implements Yolov7
-
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
-
Train YOLOv8 ObjectDetection on Custom Dataset Tutorial
yolov7: https://github.com/WongKinYiu/yolov7#performance
What are some alternatives?
YOLOv6 - YOLOv6: a single-stage object detection framework dedicated to industrial applications.
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
yolor - implementation of paper - You Only Learn One Representation: Unified Network for Multiple Tasks (https://arxiv.org/abs/2105.04206)
edgetpu - Coral issue tracker (and legacy Edge TPU API source)
YOLOX - YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/
edgetpu-yolo - Minimal-dependency Yolov5 export and inference demonstration for the Google Coral EdgeTPU
ScaledYOLOv4 - Scaled-YOLOv4: Scaling Cross Stage Partial Network
YOLOv4 - Port of YOLOv4 to C# + TensorFlow
yolo_series_deepsort_pytorch - Deepsort with yolo series. This project support the existing yolo detection model algorithm (YOLOV8, YOLOV7, YOLOV6, YOLOV5, YOLOV4Scaled, YOLOV4, YOLOv3', PPYOLOE, YOLOR, YOLOX ).
darknet - Convolutional Neural Networks
PPYOLOE_pytorch - An unofficial implementation of Pytorch version PP-YOLOE,based on Megvii YOLOX training code.
XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model