Some smart words, links, tables, figures and graphs
The quickest way will be using colab notebooks to reproduce our results
- training - inference - all togetherInstall
Python>=3.7.0 is required with all requirements.txt installed including PyTorch>=1.7:
$ git clone https://github.com/leetoo/thepaper
$ cd thepaper
$ pip install -r requirements.txt
Inference
Inference with YOLOv5 based model you can execute agains your _ video / images _ here :
import torch
# Model
model = ... # or yolov5m, yolov5x, custom
# Images
img = 'https://... ' # or file, PIL, OpenCV, numpy, multiple
# Inference
results = model(img)
# Results
results.print() # or .show(), .save(), .crop(), .pandas(), etc.
Inference with detect.py
detect.py
runs inference on a variety of sources
and saving results to runs/detect
.
$ python detect.py --source 0 # webcam
file.jpg # image
file.mp4 # video
path/ # directory
path/*.jpg # glob
'https://youtu.be/NUsoVlDFqZg' # YouTube video
'rtsp://example.com/media.mp4' # RTSP, RTMP, HTTP stream
Training
Run commands below to reproduce results on DataSetv5 dataset (dataset auto-downloads). Use the largest --batch-size
your GPU allows (batch sizes shown for 16 GB devices).
$ python train.py --data $$$ --cfg $$$ --weights yolov5l --batch-size 64
Tutorials
- Train Custom Data 🚀 RECOMMENDED
- Tips for Best Training Results ☘️ RECOMMENDED
- Weights & Biases Logging 🌟 NEW
todo ask do we need those tutorials ?
Get started in seconds with our verified environments and integrations, including Weights & Biases for automatic YOLOv5 experiment logging. Click each icon below for details.
For issues running the paper please visit GitHub Issues. For business or professional support requests please visit https://www.fellowship.ai