icey-zhang / SuperYOLO

SuperYOLO is accepted by TGRS
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Welcome to SuperYOLO Discussions! #118

Open icey-zhang opened 4 months ago

icey-zhang commented 4 months ago

Discussed in https://github.com/icey-zhang/SuperYOLO/discussions/117

Originally posted by **icey-zhang** June 9, 2024 > ## 👋 Welcome! > We’re using Discussions as a place to connect with other members of our community. We hope that you: > > * Ask questions you’re wondering about. > * Share ideas. > * Engage with other community members. > * Welcome others and are open-minded. Remember that this is a community we > build together 💪. > > To get started, comment below with an introduction of yourself and tell us about what you do with this community.
jimvanoosten commented 4 months ago

What python did you use?

icey-zhang commented 4 months ago

We run our code with Python 3.7 & 3.8 & 3.9

jacksonwu09 commented 4 months ago

Hello, I would like to ask why training from scratch does not achieve your 80.9% performance. What methods should be adopted to reach this level? Also, why is the image size passed into the MF during testing set to 544?

Nadeen86 commented 3 months ago

Hello, Thanks for sharing the code. I got the following error: AttributeError: module 'numpy' has no attribute 'int'. np.int was a deprecated alias for the builtin int. To avoid this error in existing code, use int by itself. Doing this will not modify any behavior and is safe. When replacing np.int, you may wish to use e.g. np.int64 or np.int32 to specify the precision. If you wish to review your current use, check the release note link for additional information. The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations

what is the best way to solve this problem should I change the environment? can any body give me the right environment versions for the libraries? or I should change the np.int. to np.int32 ?

renfeiy commented 3 months ago

Hello, thanks for sharing the code. I have a question about the code. During the training phase, the --hr_input parameter does not seem to be involved in the create_dataloader() method. I would like to ask where this parameter is applied? Second question: If my data is a non-square image, how should I adjust the parameters?

Nadeen86 commented 3 months ago

are mid-level fusion ready to use? I ran the code but I have errors in mid-level fusion files

corkiyao commented 3 months ago

Meet a problem, in the file SuperYOLO/utils/datasets.py, where the function def img2label_paths(img_paths): def img2label_paths(imgpaths): sa, sb = os.sep + 'images' + os.sep, os.sep + 'labels' + os.sep # /images/, /labels/ substrings return [x.replace(sa, sb, 1).replace('' + x.split('_')[-1], '.txt') for x in img_paths] #replace('.' + x.split('.')[-1], '.txt') However, in the Windows platform, the function cannot work. Debuggin for a long time.........Maybe it works in the linux

icey-zhang commented 2 months ago

About the dataset used in SuperYOLO https://github.com/icey-zhang/GHOST/blob/main/data/transform_dota.py https://github.com/icey-zhang/GHOST/blob/main/data/transform_dior.py https://github.com/icey-zhang/GHOST/blob/main/data/transform_nwpu.py

wang-yt0801 commented 2 months ago

”SuperYOLO-main\dataset\VEDAI_1024\images.cache. Can not train without labels“,What is the solution to this problem for everyone? The data path in the YAML file has also been modified

ca1wenha0 commented 1 month ago

Hello, your results are impressive. May I ask if the input data must be square? My current image size is 640x512

123cjl123 commented 3 weeks ago

train: ./dataset/VEDAI/fold01_write.txt test: ./dataset/VEDAI/fold01test_write.txt val: ./dataset/VEDAI/fold01test_write.txt 配置文件这样 最后会报错找不到label文件 为什莫 就是根据你的代码来的啊 AssertionError: train: No labels in dataset\VEDAI_1024\images.cache. Can not train without labels.

corkiyao commented 3 weeks ago

train: ./dataset/VEDAI/fold01_write.txt test: ./dataset/VEDAI/fold01test_write.txt val: ./dataset/VEDAI/fold01test_write.txt 配置文件这样 最后会报错找不到label文件 为什莫 就是根据你的代码来的啊 AssertionError: train: No labels in dataset\VEDAI_1024\images.cache. Can not train without labels.

debug后发现,其中会有路径加载错误。你自己调试下就知道。

farhaniqbalbajwa commented 1 week ago

i am using Nvidia 2080 super. Is it gonna be factor on accuracy considering u used 3090. training time is almost 8 hours