jizhishutong / yolou Goto Github PK

感谢博主的开源，我想使用yolov5-seg进行实例分割 请问数据格式是什么样的？

When training yolov7, there comes
name 'DownC' is not defined.
Seems some modules not defined

缺少 yolov4 系列的模型，yolov4标准版、yolov4-tiny，以及Scaled-yolov4系列

Hi jizhishutong, do you have a script to do inference with onnx, just to check if the model works normally. Thanks.

命令：python train.py --mode yolov7 --use_aux True --data garbage.yaml --cfg yolov7.yaml --weights weights/yolov7/yolov7.pt --batch-size 8
出现错误
**Logging results to runs/train/exp14
Starting training for 100 epochs...

 Epoch   gpu_mem       box       obj       cls    labels  img_size

0%| | 0/5 [00:01<?, ?it/s]
Traceback (most recent call last):
File "train.py", line 772, in
main(opt)
File "train.py", line 670, in main
train(opt.hyp, opt, device, callbacks)
File "train.py", line 448, in train
loss, loss_items = compute_loss(pred, targets.to(device), imgs) # init loss class
File "YOLOU/utils/loss.py", line 992, in call
bs_aux, as_aux_, gjs_aux, gis_aux, targets_aux, anchors_aux = self.build_targets2(p[:self.nl], targets, imgs)
File "YOLOU/utils/loss.py", line 1202, in build_targets2
indices, anch = self.find_5_positive(p, targets)
File "YOLOU/utils/loss.py", line 1388, in find_5_positive
indices.append((b, a, gj.clamp_(0, gain[3] - 1), gi.clamp_(0, gain[2] - 1))) # image, anchor, grid indices
RuntimeError: result type Float can't be cast to the desired output type long int
**

https://github.com/Linaom1214/TensorRT-For-YOLO-Series/blob/main/Examples.ipynb

export: weights=['./weights/yolov6s.pt'], imgsz=[640, 640], batch_size=1, device=cpu, half=False, inplace=False, train=False, optimize=False, dynamic=True, simplify=True, opset=12, include=['onnx']
YOLOv5 2022-8-25 Python-3.10.5 torch-1.12.0+cpu CPU

Traceback (most recent call last):
File "E:\Code\YOLOU-main\export.py", line 209, in
main(opt)
File "E:\Code\YOLOU-main\export.py", line 204, in main
run(**vars(opt))
File "E:\Code\pythonCode\changeable_region_detection-main\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "E:\Code\YOLOU-main\export.py", line 133, in run
model = attempt_load(weights, device=device, inplace=True, fuse=True) # load FP32 model
File "E:\Code\YOLOU-main\models\experimental.py", line 228, in attempt_load
ckpt = torch.load(attempt_download(w), map_location='cpu') # load
File "E:\Code\pythonCode\changeable_region_detection-main\venv\lib\site-packages\torch\serialization.py", line 712, in load
return _load(opened_zipfile, map_location, pickle_module, **pickle_load_args)
File "E:\Code\pythonCode\changeable_region_detection-main\venv\lib\site-packages\torch\serialization.py", line 1049, in _load
result = unpickler.load()
File "E:\Code\pythonCode\changeable_region_detection-main\venv\lib\site-packages\torch\serialization.py", line 1042, in find_class
return super().find_class(mod_name, name)

ModuleNotFoundError: No module named 'yolov6'

进程已结束,退出代码1

You can find yolo with pose form this. https://github.com/BingfengYan/yolo_pose.
train+test+to tensorRT

这个项目好长时间没有更新了，是不再维护了吗？

使用yolov7训练数据时，出现了下列错误：
RuntimeError: result type Float can't be cast to the desired output type __int64
目前在网上还没有找到yolov7相关解决方案，我的运行环境是pytorch==1.12,cuda==11.3,python==3.7

Does detect.py only support the yolov5 model?

Can I use your source for commercial purposes?

当我尝试运行val_det.py时,提示forward()出现了未知的参数val,然后查看代码

但是去models/common.py中查看DetectMultiBackend()却发现forward()中并没有val这个参数

所以这应该是个小bug或者是没有及时更新的地方,无论是在common.py的forward()中添加一个val参数或者是去掉推理时的val=True都可以解决这个问题.

Hi,

What is the password to access the Baidu Drive ?

yolov7-x 53.7？高出的也太多了？
另外Yolov5精度和官方一模一样，贸然问下是不是就是搬来的权重呢？
而yolox却低了官方很多，是实现上有什么不一样吗？还是没训好呢？

这个工程感觉有几百M，下载有点慢，建议权重文件最好别上传在这个里面啊

size mismatch for model.33.cls_preds.2.bias: copying a param with shape torch.Size([80]) from check point, the shape in current model is torch.Size([14]).

When will other pretrained models for yolox and other yaml profiles for yolov6 be released

Yolov6 is anchor-free，please correct the information.

Your experiment is based on COCO dataset? If it is true, some data is not consistent the official data.

outputs must be a Tensor or an iterable of Tensors

If yes, is it possible to provide a reparameterization script (like reparameterization.ipynb in official yolov7 repo)？

It is inconvenient to download them outside of China. Maybe it is a good idea to upload them in the release, where large files are supported.

Hi jizhishutong, I check the export onnx model of yolov6 and find that some rep module is not reparameterized. Wanna know how to reparameterize when exporting, thanks!

if mode == 'yolox':
if epoch == epochs - no_aug_epochs:
LOGGER.info("--->No mosaic aug now!")
dataset.mosaic = False # close mosaic
LOGGER.info("--->Add additional L1 loss now!")

我自己单步调试的时候发现， dataset.mosaic 在运行过程中还是True

Can the pre-trained model released by the official repository be used normally in this repository?

if there is a download link?

something wrong with yolov7

File "/home/pc/dawn_work_space/yolou/YOLOU/models/yolox.py", line 210, in get_output_and_grid
reg_box[..., :2] = (reg_box[..., :2] + grid) * stride
RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:1 and cuda:0!

How can I get a pretrained weight about YOLOX, will train the model from the beginning?Thank you!

Megvii-BaseDetection/YOLOX#712

https://github.com/hpc203/yolov34-cpp-opencv-dnn
https://github.com/hpc203/yolov5-dnn-cpp-python
https://github.com/hpc203/yolov5-dnn-cpp-python-v2
https://github.com/hpc203/nanodet-opncv-dnn-cpp-python
https://github.com/hpc203/nanodet-plus-opencv
https://github.com/hpc203/yolact-opencv-dnn-cpp-python
https://github.com/hpc203/yolov5-face-landmarks-opencv
https://github.com/hpc203/yolov5-face-landmarks-opencv-v2
https://github.com/hpc203/yolox-opencv-dnn
https://github.com/hpc203/yolo-fastestv2-opencv
https://github.com/hpc203/YOLOP-opencv-dnn
https://github.com/hpc203/yolor-onnxruntime
https://github.com/hpc203/yolov5-detect-car_plate_corner
https://github.com/hpc203/yolov5-lite-onnxruntime
https://github.com/hpc203/picodet-onnxruntime
https://github.com/hpc203/multiyolov5-opencv-onnxrun
https://github.com/hpc203/rotate-yolov5-opencv-onnxrun
https://github.com/hpc203/yolov5-v6.1-opencv-onnxrun
https://github.com/hpc203/yolov5_pose_opencv
https://github.com/hpc203/rotateyolov5-opencv-onnxrun
https://github.com/hpc203/polygonyolov5-opencv-onnxrun
https://github.com/hpc203/pp-yoloe-onnxrun-cpp-py
https://github.com/hpc203/yolov6-opencv-onnxruntime
https://github.com/hpc203/FastestDet-opencv-dnn
https://github.com/hpc203/yolov7-opencv-onnxrun-cpp-py

yolov7 推理的时候，同样的模型同样的图片，与官方的推理代码的结果相差很远。一个是0.5 官方有0.91