Hey, why do you call this as a instance segmentation? isn't it just a semantic segmentation? here you have same id for all the classes belong to same class.
After cloning yolov8 from git repository how we will train it by python train.py its working fine but doesnt show any progress showing no result after execution
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 47 but got size 0 for tensor number 1 in the list. Sentry is attempting to send 1 pending events I am getting this error continuously when I train it
Hey thanks for your incredible work! I did this custom training and try to put a video in the "source" and didnt worked.... specifically i get the error "Sentry is attempting to send 2 pending events Waiting up to 2 seconds Press Ctrl-C to quit" Do you have any idea on this??
Sorry but this is my honest opinion: This is the worst video on training int segmentation on custom dataset, you simply used the example notebook from ultralytics, and just worded off as whatsoever was there in the notebook and downloaded a already configured dataset for instance segmentation and trained the model on it.
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 47 but got size 0 for tensor number 1 in the list. Sentry is attempting to send 1 pending events
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 47 but got size 0 for tensor number 1 in the list. Sentry is attempting to send 1 pending events
Thanks for the video.
Hey, why do you call this as a instance segmentation? isn't it just a semantic segmentation? here you have same id for all the classes belong to same class.
I need a pre-training model with a resolution size of 4096 * 4096. The default size is 640.. how to handle this larger image sizes in yolov8
After cloning yolov8 from git repository how we will train it by python train.py its working fine but doesnt show any progress showing no result after execution
how can we get high accuracy?
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 47 but got size 0 for tensor number 1 in the list.
Sentry is attempting to send 1 pending events
I am getting this error continuously when I train it
Hey thanks for your incredible work! I did this custom training and try to put a video in the "source" and didnt worked....
specifically i get the error "Sentry is attempting to send 2 pending events
Waiting up to 2 seconds
Press Ctrl-C to quit"
Do you have any idea on this??
Sorry but this is my honest opinion: This is the worst video on training int segmentation on custom dataset, you simply used the example notebook from ultralytics, and just worded off as whatsoever was there in the notebook and downloaded a already configured dataset for instance segmentation and trained the model on it.
Thanks for the video, any idea how to remove the bounding box (the thick frame) around the object that is segmented?
please make videos about Encoder Decoder,Attention Models, Transformers.
if I want just segmentation in yolov8 and I don't need a bounding box what i have to do @DSwithBappy
how to perform classification on custom dataset?
will create soon.
@@dswithbappy thank you. Plz upload that part as soon as possible..
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 47 but got size 0 for tensor number 1 in the list.
Sentry is attempting to send 1 pending events
Thank you sir
Thanks.
😍😍😍
❤❤
In my code it is showing -
Ultralytics YOLOv8.0.28 🚀 Python-3.10.12 torch-2.3.0+cu121 CPU
yolo/engine/trainer: task=segment, mode=train, model=yolov8s-seg.pt, data=data.yaml, epochs=10, patience=50, batch=16, imgsz=640, save=True, cache=False, device=None, workers=8, project=None, name=None, exist_ok=False, pretrained=False, optimizer=SGD, verbose=True, seed=0, deterministic=True, single_cls=False, image_weights=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, show=False, save_txt=False, save_conf=False, save_crop=False, hide_labels=False, hide_conf=False, vid_stride=1, line_thickness=3, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, boxes=True, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, fl_gamma=0.0, label_smoothing=0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0, cfg=None, v5loader=False, save_dir=runs/segment/train24
Traceback (most recent call last):
File "/usr/local/bin/yolo", line 8, in
sys.exit(entrypoint())
File "/usr/local/lib/python3.10/dist-packages/ultralytics/yolo/cfg/__init__.py", line 266, in entrypoint
getattr(model, mode)(**vars(cfg))
File "/usr/local/lib/python3.10/dist-packages/ultralytics/yolo/engine/model.py", line 210, in train
self.trainer = self.TrainerClass(overrides=overrides)
File "/usr/local/lib/python3.10/dist-packages/ultralytics/yolo/v8/segment/train.py", line 25, in __init__
super().__init__(cfg, overrides)
File "/usr/local/lib/python3.10/dist-packages/ultralytics/yolo/engine/trainer.py", line 121, in __init__
self.data = check_det_dataset(self.data)
File "/usr/local/lib/python3.10/dist-packages/ultralytics/yolo/data/utils.py", line 190, in check_det_dataset
data = check_file(dataset)
File "/usr/local/lib/python3.10/dist-packages/ultralytics/yolo/utils/checks.py", line 258, in check_file
raise FileNotFoundError(f"'{file}' does not exist")
FileNotFoundError: 'data.yaml' does not exist
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 47 but got size 0 for tensor number 1 in the list.
Sentry is attempting to send 1 pending events
same brother what to do for this