I’m sorry, but I don’t speak English, so I use a translator. Until a few days ago, there were no problems with learning. But now I get the following error: :/cb/pytorch_1000000000000/work/aten/src/ATen/native/cuda/IndexKernel.cu:97: block: [0,0,0], thread: [15,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed. C:/cb/pytorch_1000000000000/work/aten/src/ATen/native/cuda/IndexKernel.cu:97: block: [0,0,0], thread: [103,0,0] Assertion ..
I am trying to train different label names to create a dataset for yolov5. However, I am stuck with the following error when editing the file. Can you please tell me how to solve this problem? Thank you very much for your help. import os #cell phone, book, suitcase,handbag,bottle to 2 %cd /content/drive/MyDrive/harada_yolo/1218_data/training_8/data/exp2/labels img_path = ..
In the training step of ByteTrack, I want to use Yolov5 instead of YoloX, so I try to run python3 tools/train.py -f exps/example/mot/yolox_x_mot17_half.py -o -c pretrained/yolov5x6.pt -b 1 -d 1 with yolov5x6 pretrained weights from yolov5 model zoo, and I got this error ModuleNotFoundError: No module named ‘models’ How can I fix this? ByteTrack repo ..
I am converting pytorch model into Tensorflow. For that Pytorch-ONNX-Tensorflow this are the steps I am following, but while exporting Pytorch model into ONNX getting the following error: ModuleNotFoundError: No module named ‘models’ Below is the code snippet: trained_model = Net() trained_model.load_state_dict(torch.load(‘best.pt’)) dummy_input = Variable(torch.randn(1, 1, 28, 28)) torch.onnx.export(trained_model, dummy_input, "best.onnx") Any help would be ..
I have tried all of the answers that reference "exit code -1073741819 (0xC0000005)" (Which means access violation) but none of them work. I followed the exact instructions on the Ultraytics web site on another machine and it works fine, but the machine I must do the work on give me the access violation. The code ..
I am using the Yolov4-DeepSORT library in order to identify certain classes of objects in a source video. In the final output video, the image detection boxes are overlayed on the source video. Is there a way to remove the source video, and show just the object detection boxes, without any overlay in any yolo ..
I have trained a yolov5l model for object detection and classification. I want to use the exported weights to identify images in a program I am creating. I am having trouble finding much of anything on how to use .pt weights in a python program. I believe I use the "torch.load" method from the pytorch ..
I git cloned the full repo (link here) and ran the programme with no further modification. In a new virtual environment with python3.8, and after pip install -r requirements.txt Appended below is the terminal output python3 detect.py –source 0 detect: weights=yolov5s.pt, source=0, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, ..
I have ~50000 images and annotation files for training a YOLOv5 object detection model. I’ve trained a model no problem using just CPU, but it takes too long, so I need GPU training. My problem is, when I try to train with a GPU I keep getting this error: OSError: [WinError 1455] The paging file ..
I am trying to run this github repo found at this link: https://github.com/HowieMa/DeepSORT_YOLOv5_Pytorch After installing the requirements via pip install -r requirements.txt. I am running this in a python 3.8 virtual environment, on a dji manifold 2g which runs on an Nvidia jetson tx2. The following is the terminal output. $ python main.py –cam 0 ..