tea leaf diseases detection based on YOLOv9 (computer vision project) import os HOME = os.getcwd() print(HOME) //installation !git clone https://github.com/SkalskiP/yolov9.git %cd yolov9 !pip install -r requirements.txt -q !wget -P {HOME}/weights -q https://github.com/WongKinYiu/yolov9/releases/download/v0.1/yolov9-e.pt !wget -P {HOME}/weights -q https://github.com/WongKinYiu/yolov9/releases/download/v0.1/gelan-c.pt !wget -P {HOME}/weights -q https://github.com/WongKinYiu/yolov9/releases/download/v0.1/gelan-e.pt !ls -la {HOME}/weights !wget -P {HOME}/data -q https://media.roboflow.com/notebooks/examples/dog.jpeg %cd {HOME}/yolov9 !pip install roboflow
from roboflow import Roboflow rf = Roboflow(api_key="AGfuNwvA5KninjvE1LRP") project = rf.workspace("AUS").project("tea-76um3") version = project.version(2) dataset = version.download("yolov9") %cd {HOME}/yolov9
!python train.py
--batch 16 --epochs 25 --img 640 --device 0 --min-items 0 --close-mosaic 15
--data {dataset.location}/data.yaml
--weights {HOME}/weights/gelan-c.pt
--cfg models/detect/gelan-c.yaml
--hyp hyp.scratch-high.yaml
import glob
from IPython.display import Image, display
for image_path in glob.glob(f'{HOME}/yolov9/runs/detect/exp3/*.jpg')[:5]: display(Image(filename=image_path, width=600))