All the pretrined model weights and cfg is from official site:
https://github.com/AlexeyAB/darknet
yolov4.cfg
yolov4.weights
And thanks ultralytics's project, it's really great and helpful.
https://github.com/ultralytics/yolov3
Let's look the excellent performance about yolo v4!!
In yolo v4 have the shortage about missing detection of small itemes. I try to fix the shortage. I found out The best way to fix the issue is modify the objectness in stride=8 Yolo Layer (76*76)
this project is under my another project "trident", a higher order api both in pytorch and tensorflow, and I'll open-source soon.
本專案是基於我目前正在開發的另一個專案trident所開發的,它是一個整合pytorch與tensorflow動態計算圖的高階api,很快我就會將它開源,各位可以先從pip下載安裝。
trident only support python 3.x
If you want to use pytorch api, you need pytorch 1.2 or higher
If you want to use tensorflow api, you need tensorflow 2.2rc0 or higher (because trident tensorflow api is pure eager mode "without keras, without static graph"")
You can install it from pip
pip install tridentx --upgrade
after installed trident, you can use following syntax to import it and assign the backed.
import os
os.environ['TRIDENT_BACKEND'] = 'pytorch'
import trident as T
from trident import *
- pytorch_yolo.py: it is just a basic library derived from trident , to define darknet and yolo basic block.
- pytorch_darknet.py: we can construction yolo v4 network and load pretrained weights here.
- pytorch_infer_yolo4.py: It's a demo to show how to do object detection by yolo v4 model and how trident api to make things easy.
You also can download my results in pytorch from google drive: pytorch pretrained model pytorch pretrained statedict
- yolov4 for tensorflow eager mode (by trident tensorflow api)
- all the bag of freebies and bag of specials in training context.
- use yolov4 for custom datasets