I have trained my model using yoloV5 on google colab, following the provided tutorial and walkthrough provided for training any custom model: Colab file for training your own custom model. I now have an exported best.pt file after running the last cell in the link provided. Now, I want to make use of this trained weight to run a detection locally on any python script. Is this possible? If so, how do I go about doing this?
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Answer
You should follow this step:
- Create an empty folder in desktop called ObjectDetection
- Open command prompt and change directory to that new folder using
cd ObjectDetection. - Clone yolov5 repo using command –
git clone https://github.com/ultralytics/yolov5.git. It will create a new folder called yolov5 inside ObjectDetection folder.
yolov5 folder contains important python file called detect.py which is responsible to detect the objects. - After cloning the repo, enter into yolov5 folder using
cd yolov5 - Install all the necessary requirements using –
pip install -r requirements.txt - Download best.pt from colab and manually paste it inside yolov5 folder.
- Also copy the image that you want to test inside yolov5 folder.
- Before running inference, make sure that image.png, best.pt and detect.py should be in inside yolov5 folder.
- You can then run inference inside yolov5 folder by using this command:
python detect.py --weights best.pt --source image.png - After the process is completed, you can check the result inside path
ObjectDetection/yolov5/runs/detect/exp