Updated Version of YOLOv7 with CUDA Fix

Description

• Integrated from yolov7 official repo https://github.com/WongKinYiu/yolov7, fixed the issue on cuda core can't run on yolov7 model. Tested on conda environment with python3.9, pytorch=1.11.0, cudatoolkit=1.13

Performance

MS COCO

Model	Test Size	APtest	AP50test	AP75test	batch 1 fps	batch 32 average time
YOLOv7	640	51.4%	69.7%	55.9%	161 fps	2.8 ms
YOLOv7-X	640	53.1%	71.2%	57.8%	114 fps	4.3 ms
YOLOv7-W6	1280	54.9%	72.6%	60.1%	84 fps	7.6 ms
YOLOv7-E6	1280	56.0%	73.5%	61.2%	56 fps	12.3 ms
YOLOv7-D6	1280	56.6%	74.0%	61.8%	44 fps	15.0 ms
YOLOv7-E6E	1280	56.8%	74.4%	62.1%	36 fps	18.7 ms

Installation on Windows

Conda environment -- Anaconda https://www.anaconda.com/
Python -- Python 3.9 installed with Anaconda

Install Anaconda

Select Installation Type : 'just me'
Anaconda Install Location : Anywhere you want, doesn't have to be on C drive
Advanved Installation Options :

Clone yolov7 Repo

Run git clone https://github.com/FlyerJB/YOLOv7-RoboMaster.git on your command prompt to some dir under C:/ drive or your OS drive to avoid Enviornment failure \

Make Conda Environment

Open Conda Command Prompt with Admin Right
Cd into yolov7 dir with cd <where you clone your yolov7>
And craete Conda Environment Conda Create -n <The Name You Like> Python3.9

Activate Conda Environment

Run command Conda activate <The Name You put from previous step>

pip install required packages

Option 1 : Install yolov7 for training on CPU
pip install -r requirements.txt

Option 2 : Install yolov7 for training on RTX GPU
pip install -r requirement_nv_gpu.txt

Validate Cuda Installation ( required for nv_gpu training )

Run python or python3 or py to run python
Run import torch
Run torch.cuda_is_available()
If it returns True, it means CUDA is successfully install on your device with Pytorch.

Training

With GPU training

# train p6 models
python train.py --workers 1 --device 0 --batch-size 8 --epochs 50 --img 640 640 --data data/coco_custom.yaml --hyp data/hyp.scratch.custom.yaml --cfg cfg/training/yolov7-custom.yaml --name yolov7-custom-tut5-v1 --weights yolov7.pt

With CPU training

# train p6 models
python train.py --workers 1 --device CPU --batch-size 8 --epochs 50 --img 640 640 --data data/coco_custom.yaml --hyp data/hyp.scratch.custom.yaml --cfg cfg/training/yolov7-custom.yaml --name yolov7-custom-tut5-v1 --weights yolov7.pt