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Reformat python files

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Matúš Námešný
2024-05-30 19:31:28 +02:00
parent 229929a464
commit 09e64f8037
2 changed files with 7 additions and 33 deletions
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25
examples/alexnet/alexnet.py
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@@ -1,35 +1,10 @@
import sys import sys
import torch
import torchvision import torchvision
from PIL import Image
from torchvision import transforms
sys.path.append('../../tools') # Ugly hack sys.path.append('../../tools') # Ugly hack
from utils import export_model_weights, print_model_parameters from utils import export_model_weights, print_model_parameters
def predict(model, image_path):
input_image = Image.open(image_path)
preprocess = transforms.Compose([
transforms.Resize(256),
transforms.CenterCrop(227),
transforms.ToTensor(),
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
])
input_tensor = preprocess(input_image)
input_batch = input_tensor.unsqueeze(0) # create a mini-batch as expected by the model
# move the input and model to GPU for speed if available
if torch.cuda.is_available():
input_batch = input_batch.to('cuda')
model.to('cuda')
with torch.no_grad():
output = model(input_batch)
print(torch.argmax(output))
if __name__ == "__main__": if __name__ == "__main__":
alexnet = torchvision.models.alexnet(weights=torchvision.models.AlexNet_Weights.DEFAULT) alexnet = torchvision.models.alexnet(weights=torchvision.models.AlexNet_Weights.DEFAULT)
print_model_parameters(alexnet) # print layer names and number of parameters print_model_parameters(alexnet) # print layer names and number of parameters

15
examples/inception_v3/inception_v3.py
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@@ -1,16 +1,15 @@
import torchvision import torchvision
import sys import sys
sys.path.append('../../tools') # Ugly hack sys.path.append("../../tools") # Ugly hack
from utils import export_model_weights, print_model_parameters, predict from utils import export_model_weights, print_model_parameters
if __name__ == "__main__": if __name__ == "__main__":
inception = torchvision.models.inception_v3(weights=torchvision.models.Inception_V3_Weights.DEFAULT) inception = torchvision.models.inception_v3(
weights=torchvision.models.Inception_V3_Weights.DEFAULT
)
inception.eval() inception.eval()
# print_model_parameters(inception) # print layer names and number of parameters print_model_parameters(inception) # print layer names and number of parameters
export_model_weights(inception, "inception_v3_weights.bin")
# export_model_weights(inception, 'inception_v3_weights.bin')
print(predict(inception, "./margot.jpg"))