yolov7
BCNet
Our great sponsors
| yolov7 | BCNet | |
|---|---|---|
| 33 | 1 | |
| 12,636 | 507 | |
| - | - | |
| 4.0 | 3.0 | |
| 8 days ago | 10 months ago | |
| Jupyter Notebook | Python | |
| GNU General Public License v3.0 only | MIT License |
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.
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
BCNet
-
[CVPR2021] Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers
github: https://github.com/lkeab/BCNet
What are some alternatives?
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
layout-parser - A Unified Toolkit for Deep Learning Based Document Image Analysis
edgetpu - Coral issue tracker (and legacy Edge TPU API source)
mmdetection - OpenMMLab Detection Toolbox and Benchmark
edgetpu-yolo - Minimal-dependency Yolov5 export and inference demonstration for the Google Coral EdgeTPU
yolov7_d2 - 🔥🔥🔥🔥 (Earlier YOLOv7 not official one) YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
YOLOv4 - Port of YOLOv4 to C# + TensorFlow
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.
darknet - Convolutional Neural Networks
PaddleDetection - Object Detection toolkit based on PaddlePaddle. It supports object detection, instance segmentation, multiple object tracking and real-time multi-person keypoint detection.
XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
AdelaiDet - AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.