Tsardoz
Tsardoz
Is the annotation format the same for all? eg. ADE20K seems to be color images. I have COCO format original annotation data (grey scale) but it appears I need to...
Hi this looks great but I am a bit confused. I want to use a pretrained topformer model for inference for evaluation then maybe to use it for custom training....
I want to use these weights as a pretrained model for use with a smaller subset of cocostuff data. When I change pretrained = 'pretrained/beit_large_patch16_224_pt22k_ft22k.pth' to pretrained = 'pretrained/mask2former_beit_adapter_large_896_80k_cocostuff164k.pth.tar' I...
!CUDA_VISIBLE_DEVICES=0 python image_demo.py \ configs/coco_stuff164k/mask2former_beit_adapter_large_896_80k_cocostuff164k_ss.py \ pretrained/mask2former_beit_adapter_large_896_80k_cocostuff164k.pth.tar \ /data/sample1.jpg \ --palette coco_stuff Traceback (most recent call last): File "image_demo.py", line 58, in main() File "image_demo.py", line 42, in main model.CLASSES...
### Search before asking - [X] I have searched the YOLOv8 [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/ultralytics/ultralytics/discussions) and found no similar questions. ### Question OK I found albumentations in yolo/data/augment.py. It says #...
### 💡 Your Question There is much written about using INT8 quantization (QAT and PTQ) with YOLO-NAS. However, I can find nothing about using it with NPUs. It seems to...
### 🐛 Describe the bug Using AWS P3.8xlarge or P3.16xlarge, num_gpus = 4 or 8. device = 'cuda' torch 1.13.1+cu117 super_gradients.__version__ = 3.1.1 The setup_device line causes it to go...
data
Is this the same data as was used in the paper "A Survey on Behavior Recognition Using WiFi Channel State Information"? The methods used in that paper were sketchy. Have...
I have looked over the code for the part that streams to localhost but cannot find it. Is this it (in MainStreamer)? ` VideoCapture cap(VIDEO_FILE, CAP_FFMPEG); if(!cap.isOpened()){ FrameError=true; goto Ferr;...
Time series data should never be split randomly as you have done. Sliding windows ensure most of the validation set is at least 80% similar to the training set. You...