Comments (4)
Hello, same problem . I would appreciate pretrained models as well.
Thanks,
Juraj
from yolor.
@nethy-x , @hievor, @AlexeyAB , did you find the solution for related problem?
May be @WongKinYiu already answered you?
Thanks in advance,
Andrey
from yolor.
hello @aanoskov
in the meanwhile I found out that you can find the pretrained models under releases (https://github.com/WongKinYiu/yolor/releases)
I had to switch to the paper branch to use them for inferencing, else I got an error with the main branch code.
If I remember correctly training wasn't working properly with them, but I haven't tried further as I just need todo inferencing.
Also @HERIUN has shared weights in another topic here, maybe try these (#288 (comment))
Greets Michael
from yolor.
@hievor , I already ran model with weights on releases page and the show worse accuracy, so I just started to use yolov7 from the same contributor, there weights are still opened
from yolor.
Related Issues (20)
- Pickling error - _pickle.UnpicklingError: invalid load key, '<'. HOT 4
- RuntimeError: result type Float can't be cast to the desired output type long int HOT 2
- rm: cannot remove './cookie': No such file or directory HOT 1
- Traceback (most recent call last): File "train.py", line 506, in <module> opt.data, opt.cfg, opt.hyp = check_file(opt.data), check_file(opt.cfg), check_file(opt.hyp) # check files File "/content/yolor/utils/general.py", line 74, in check_file assert len(files) == 1, "Multiple files match '%s', specify exact path: %s" % (file, files) # assert unique AssertionError: Multiple files match '../Rdata.yaml', specify exact path: ['./mish-cuda/../Rdata.yaml', './darknet/../Rdata.yaml', './scripts/../Rdata.yaml', './figure/../Rdata.yaml', './valid/../Rdata.yaml', './test/../Rdata.yaml', './data/../Rdata.yaml', './pytorch_wavelets/../Rdata.yaml', './models/../Rdata.yaml', './cfg/../Rdata.yaml', './train/../Rdata.yaml', './__pycache__/../Rdata.yaml', './inference/../Rdata.yaml', './utils/../Rdata.yaml']
- AssertionError: > 5 label columns:
- Issue with using W & B HOT 1
- what should be the ideal mAP0.95 should be? HOT 2
- Custom Dataset Finetuning training and Targets value is not real
- how do I integrate my custom Yolor model with flask
- Bounding box size is off HOT 2
- Inference result blank for both branches HOT 1
- YoloR-CSP Test with yolor-csp.cfg not working
- RuntimeError: indices should be either on cpu or on the same device as the indexed tensor (cpu) HOT 1
- Question: what is the function of pretrained weight
- Can model be defined by nn.Sequential or does it need to use nn.ModuleList HOT 5
- YOLOR-CSP Weights Link/Download HOT 3
- metrics are zero during training
- YoloR_w6.pt does not open
- Problem on running detect.py on Jetson B01
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