ILearnDeepLearning.py
yolov7
| ILearnDeepLearning.py | yolov7 | |
|---|---|---|
| 1 | 33 | |
| 1,312 | 12,715 | |
| - | - | |
| 2.6 | 3.2 | |
| 5 months ago | 15 days ago | |
| Jupyter Notebook | 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.
ILearnDeepLearning.py
-
Use YOLOv5 tensorflow.js models to speed up annotation
makesense.ia is certainly the largest one. I just recently started https://github.com/SkalskiP/yolov5js with the aim to make it much easier for frontend developers without computer vision background to use object detection in their projects. Apart from that, I have https://github.com/SkalskiP/ILearnDeepLearning.py which is a repository containing examples related to my blog posts on Medium https://medium.com/@piotr.skalski92.
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?
yolov5js - Effortless YOLOv5 javascript deployment
yolov3 - YOLOv3 in PyTorch > ONNX > CoreML > TFLite
Deep-Learning-Computer-Vision - My assignment solutions for Stanford’s CS231n (CNNs for Visual Recognition) and Michigan’s EECS 498-007/598-005 (Deep Learning for Computer Vision), version 2020.
edgetpu - Coral issue tracker (and legacy Edge TPU API source)
machine_learning_complete - A comprehensive machine learning repository containing 30+ notebooks on different concepts, algorithms and techniques.
edgetpu-yolo - Minimal-dependency Yolov5 export and inference demonstration for the Google Coral EdgeTPU
Andrew-NG-Notes - This is Andrew NG Coursera Handwritten Notes.
YOLOv4 - Port of YOLOv4 to C# + TensorFlow
darknet - Convolutional Neural Networks
XMem - [ECCV 2022] XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
BCNet - Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]
CATNet - 🛰️ Learning to Aggregate Multi-Scale Context for Instance Segmentation in Remote Sensing Images (TNNLS 2023)