yolov5 does not train the model

Question

I trained a dataset by yolov5. The model is existed but it does not work. It does not predict excatly.

Here the code I used:

python train.py --img 640 --batch 8 --epochs 3 --data ../datasets/coco128/coco128.yaml --workers 0 --image-weights '' --name test

outputs of the code:

When we look at the test folder for prediction:

Labels

Predictions

As you see, predictions are nothing. Also there are best.pt and last.pt files. Their size are 14.475 mb. But google colab works with same code.

Also when I try to predict images with default yolov5s.pt, it works, predictions are right.

matrix confusion, result.csv are almost empty with nan text as well.

Thank you for your helps...

Answer 1

I had a similar issue with YOLOv5 and was able to resolve it by paying attention to the --img (image size) and --conf attributes.

When calling the training script, you can define the image dimensions

python train.py --img 672 1216 ...

But you might have forgotten to use the same argument in the inference script

python detect.py --img 672 ...

Another issue is when your dataset is too small and the Recall/Precision/mAP is too low, you need to decrease the confidence filter for output during inference:

python detect.py ... --conf 0.7

You might need to reduce the --confto 0.1 to see any output. Then play with it until you are satisfied with precision/recall in your output.

Answer 2

How large is your dataset? I trained yolov5s with only around 30 images with 30 to 40 labels of numbers "0" to "9" per image, it worked poorly, but when I collected more images(66 images), the network reached [email protected] to around 0.99.