I’m trying to make a currency recognition model and I did so using a dataset on kaggle and colab using yolov5 and I exactly carried out the steps explained on yolov5 github. At the end, I downloaded a .pt file which has the weights of the model and now I want to use it in python file to detect and
Tag: yolov5
Using Yolox on an asset image doesn’t draw any detection
So I’m trying to learn how to use Yolox for my bachelor thesis, and after hours of installing and updating components, finally managed to run Yolox on a test image in the assets folder. However, when I go to the output folder, it’s the same image there, with no boxes on detected objects and I can’t understand why.. Here is
How do I use the exported ‘best.pt” file from yolov5 colab file to run the trained weights locally?
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
How to get class and bounding box coordinates from YOLOv5 predictions?
I am trying to perform inference on my custom YOLOv5 model. The official documentation uses the default detect.py script for inference. I have written my own python script but I cannot access the predicted class and the bounding box coordinates from the output of the model. Here is my code: Answer This will give you labels, coordinates, and thresholds for