Comments (3)
Hi Yuanduo,
Yes, we always work on advanced features and new training recipes for all of our models, and the ddrnet models' recipes and pre-trained weights will be updated.
If you have more suggestions for us we will love to talk and hear your thoughts!
Also if you liked our work, we would be thankful if you will star our repo and share it among your colleagues :)
from super-gradients.
Hi Yuanduo,
In the next few days, we will upload new recipes and checkpoints for ddrnet_23 and ddrnet_23_slim with higher mIoU and better runtime performance.
we received on cityscapes these results
ddrnet23: 79.7%
ddrnet23slim: 77.99%
from super-gradients.
Hi Yuanduo, In the next few days, we will upload new recipes and checkpoints for ddrnet_23 and ddrnet_23_slim with higher mIoU and better runtime performance. we received on cityscapes these results ddrnet23: 79.7% ddrnet23slim: 77.99%
Thanks for your great work and efforts. Look forward to the new model and hope it can help semantic segmentation in self-driving.
from super-gradients.
Related Issues (20)
- pth or onnx -> pb HOT 1
- Error in Quick Start
- Bad support on some medical images with non RGB format HOT 4
- Using class specific score threshold given during training for inference HOT 4
- unidentified image error in model.predict() HOT 1
- How to use the knowledge distillation on yolo_nas_pose? HOT 1
- Cache removal HOT 1
- How to improve api access speed HOT 3
- how to apply post process on openvino inference? HOT 2
- yolo-nas performace HOT 4
- Installation error: error: subprocess-exited-with-error HOT 1
- removing label names and confidence in predicted picture HOT 1
- AttributeError: 'EarlyStop' object has no attribute 'append' HOT 1
- Yolo Onnx Export -> Experiencing Worse Accuracy HOT 10
- Python 3.11 HOT 2
- YOLO-NAS - TorchScript output tensor format HOT 1
- onnx export error: MemoryError: std::bad_alloc in onnxsim HOT 2
- YOLO NAS: inference time depending on training? HOT 4
- How to set the lr_warmup_epochs to be greater than 10 ? HOT 2
- Onnx model supporting batch prediction HOT 3
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