Tools of CV(Computer Vision)
Project description
Usage Sample ''''''''''''
.. code:: python
from torch import nn
from cvx2 import WidthBlock
from cvx2.wrapper import ImageClassifyModelWrapper
model = nn.Sequential(
WidthBlock(c1=1, c2=32),
nn.MaxPool2d(kernel_size=2, stride=2),
WidthBlock(c1=32, c2=64),
nn.MaxPool2d(kernel_size=2, stride=2),
nn.Flatten(),
nn.Linear(in_features=64*49, out_features=1024),
nn.Dropout(0.2),
nn.SiLU(inplace=True),
nn.Linear(in_features=1024, out_features=2),
)
data_dir
|__train
| |__class1
| | |__001.jpg
| | |__002.jpg
| |__class2
| |__001.jpg
| |__002.jpg
|__test
| |__class1
| | |__001.jpg
| | |__002.jpg
| |__class2
| |__001.jpg
| |__002.jpg
|__val
|__class1
| |__001.jpg
| |__002.jpg
|__class2
|__001.jpg
|__002.jpg
model_wrapper = ImageClassifyModelWrapper(model)
model_wrapper.train(data='data_dir', imgsz=28)
result = model_wrapper.predict('data_dir/test/class1/001.jpg', imgsz=28)
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