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[icey-zhang]

Discussed in #117

^{Originally posted by icey-zhang June 9, 2024}

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[jimvanoosten]

What python did you use?

[icey-zhang]

We run our code with Python 3.7 & 3.8 & 3.9

[jacksonwu09]

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]

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]

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]

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

[corkiyao]

Meet a problem, in the file SuperYOLO/utils/datasets.py, where the function
def img2label_paths(img_paths):
def img2label_paths(img_paths):
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]

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]

”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]

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

[123cjl123]

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]

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。

[1358028281]

abel文件 为什莫 就是根据你的代码来的啊

你好，问题解决了吗

[caijincc]

WARNING: Dataset not found, nonexistent paths: ['E:\home\data\zhangjiaqing\dataset\VEDAI\fold01test_write.txt'] in train.py,But this path does not exist in train.py

[haattrick]

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.

我也碰到这个问题了

[icey-zhang]

关于数据集读取的问题，可以参考#45