Muhammad Haritsah Mukhlis
Muhammad Haritsah Mukhlis
Quick update on this one, I finally got the correct result by **NOT** normalizing the image to [0, 1] for my custom model. On the contrary, by not normalizing the...
> > Quick update on this one, I finally got the correct result by **NOT** normalizing the image to [0, 1] for my custom model. On the contrary, by not...
> Hello, this is the issue from my repo [Hyuto/yolo-nas-onnx](https://github.com/Hyuto/yolo-nas-onnx) to inference YOLO-NAS ONNX model. I found the main problem is the preprocessing steps @Uaena-Wang custom trained model isn't the...
@Uaena-Wang Sorry for the late response, here's is the full code; ``` import cv2 import onnxruntime as ort import numpy as np import torchvision import torch import matplotlib.pyplot as plt...
I suggest you adapt the post-processing to validate your model/application. Then, you can retrain the model again with the correct augmentation pipeline. Note that the result might be different from...
You need to add the `transforms` process as required by [DetectionDataset](https://github.com/Deci-AI/super-gradients/blob/83ce129ef13ee435a0019fceeed4b0b0dc9451cc/src/super_gradients/training/datasets/detection_datasets/detection_dataset.py#LL81C9-L81C19). You can also use the dataloader to load [coco_detection_yolo_format_train](https://github.com/Deci-AI/super-gradients/blob/83ce129ef13ee435a0019fceeed4b0b0dc9451cc/src/super_gradients/training/dataloaders/dataloaders.py#LL323C5-L323C37) or `coco_detection_yolo_format_val`. ``` from super_gradients.training.dataloaders.dataloaders import coco_detection_yolo_format_train, coco_detection_yolo_format_val dataset_params =...
This error also happen when I start the qat distill training. - Number class = 1 - Config: similar to `configs/repopt/yolov6s_opt_qat.py` - Dataset: - `Train: Final numbers of valid images:...
Quick update, the preds output in `preds, s_featmaps = self.model(images)` are tensor of nans. Any idea how this might happen?
@AhmedShahhatAl , I'm not sure about it, but I was able to solve it by using extra class. My model should detect 1 object but I add extra class to...
@AhmedShahhatAl I didn't modified the code. I use real labels since it will affect the detection result