Overview
This repo is a packaged version of the Yolov7 model.
Installation
pip install yolov7detect
Yolov7 Inference
import yolov7
# load pretrained or custom model
model = yolov7.load('yolov7.pt')
#model = yolov7.load('kadirnar/yolov7-v0.1', hf_model=True)
# set model parameters
model.conf = 0.25 # NMS confidence threshold
model.iou = 0.45 # NMS IoU threshold
model.classes = None # (optional list) filter by class
# set image
imgs = 'inference/images'
# perform inference
results = model(imgs)
# inference with larger input size and test time augmentation
results = model(img, size=1280, augment=True)
# parse results
predictions = results.pred[0]
boxes = predictions[:, :4] # x1, y1, x2, y2
scores = predictions[:, 4]
categories = predictions[:, 5]
# show detection bounding boxes on image
results.show()
Citation
@article{wang2022yolov7,
title={{YOLOv7}: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors},
author={Wang, Chien-Yao and Bochkovskiy, Alexey and Liao, Hong-Yuan Mark},
journal={arXiv preprint arXiv:2207.02696},
year={2022}
}
Acknowledgement
A part of the code is borrowed from Yolov5-pip. Many thanks for their wonderful works.
Metadata
Release files for yolov7detect 1.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| yolov7detect-1.0.1.tar.gz | 122.5 kB | Details |
Release files / yolov7detect-1.0.1.tar.gz
| Download URL | yolov7detect-1.0.1.tar.gz |
|---|---|
| Size | 122.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
08e3c93cb2963adc7da03dd2c48c80f9c07436b0abb00c8e101d416e5cceb738
|
|
BLAKE2b-256 checksum How to use checksums |
81c5bdebbae697003981a25c7560bf27c5338845952fa23265ab47d585d63621
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.1.1 pkginfo/1.4.2 requests/2.22.0 setuptools/45.2.0 requests-toolbelt/0.8.0 tqdm/4.30.0 CPython/3.8.10
|