YOLOv4-pytorch
This is a pytorch repository of YOLOv4, attentive YOLOv4 and mobilenet YOLOv4 with PASCAL VOC and COCO.
argusswift/YOLOv4-pytorch is ranked 9,723 with 1,673 stars.
argusswift/YOLOv4-pytorch is ranked 9,723 among these 8 peers; Gen-Verse/MMaDA is ranked 9,720.
| Name | Rank | Metrics |
|---|---|---|
| bytedance/Sa2VA | 9,685 |
|
| explosion/sense2vec | 9,698 |
|
| YuliangXiu/ICON | 9,703 |
|
| Gen-Verse/MMaDA | 9,720 |
|
| natanielruiz/deep-head-pose | 9,736 |
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| ry/tensorflow-resnet | 9,741 |
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| google-research/pegasus | 9,754 |
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| Zehaos/MobileNet | 9,756 |
|
| Parameter | Value |
|---|---|
| Language | Python |
| Category | Models |
| Subcategory | Vision models |
| Stars | 1,673 |
| Forks | 322 |
| Contributors | 4 |
| Created date | 2020-07-19 |
| Updated date | 2026-10-09 |
| Stars in 1 day | 0 |
| Stars in 7 days | -1 |
| Rank | 9,723 |
| Previous rank | 9,763 |
| Rank change | 40 |
| 7-day stars rank | 17,054 |
| Previous 7-day stars rank | 17,055 |
| 7-day stars rank change | 1 |
| Total stars rank | 7,393 |
| Previous total stars rank | 7,388 |
| Total stars rank change | -5 |
（You only need to change the MODEL_TYPE in config/yolov4_config. This repo add some useful attention methods in backbone. The following pictures illustrate such thing: SEnet(CVPR 2017) CBAM(CVPR 2018) Highlights YOLOv4 (attentive YOLOv4 and Mobilenet-YOLOv4) with some useful module This repo is simple to use,easy to read and uncomplicated to improve compared with others! Environment Nvida GeForce RTX 2080TI CUDA10. You need to provide the conda install path (e. ~/anaconda3) and the name for
the created conda environment (here ). **Note:** The install script has been tested on an Ubuntu 18. In case of issues, check the detailed installation instructions. Prepared work 1、Git clone YOLOv4 repository Update the in the config/yolov4_config. py to transfer COCO datatype to VOC datatype. txt format (Image_path xmin0,ymin0,xmax0,ymax0,class0 xmin1,ymin1,xmax1,ymax1,class1 . 3、Download weight file Darknet pre-trained weight : yolov4 Mobilenet pre-trained weight : mobilenetv2(code:args),mobilenetv3(code:args
) Make dir in the YOLOv4 and put the weight file in. 4、Transfer to your own dataset（train your own dataset） Put pictures of your dataset into the JPEGImages folder, and Annotations files into the Annotations folder. py file to write the list of training and test files to ImageSets/Main/*. txt format (Image_path xmin0,ymin0,xmax0,ymax0,class0 xmin1,ymin1,xmax1,ymax1,class1 .
How many stars and forks are recorded?
argusswift/YOLOv4-pytorch has 1,673 stars and 322 forks.
What is the repository rank?
argusswift/YOLOv4-pytorch is ranked 9,723.
What language and category are recorded?
argusswift/YOLOv4-pytorch has 1,673 stars, uses Python and belongs to Models.
Which repository is closest in rank?
argusswift/YOLOv4-pytorch is compared with Gen-Verse/MMaDA, ranked 9,720 with 1,673 stars.