From f01e80b6ae48571444db0b95f5b00f9fe55bd0ac Mon Sep 17 00:00:00 2001
From: Schneider Leo <leo.schneider@etu.ec-lyon.fr>
Date: Fri, 18 Apr 2025 14:44:46 +0200
Subject: [PATCH] fix : dataset ray base
---
dataset/dataset.py | 13 +++++++------
main_ray.py | 4 ++--
2 files changed, 9 insertions(+), 8 deletions(-)
diff --git a/dataset/dataset.py b/dataset/dataset.py
index 9f84e63..5e05428 100644
--- a/dataset/dataset.py
+++ b/dataset/dataset.py
@@ -34,6 +34,11 @@ class Random_shift_rt():
pass
+def npy_loader(path):
+ sample = torch.from_numpy(np.load(path))
+ sample = sample.unsqueeze(0)
+ return sample
+
def load_data(base_dir, batch_size, shuffle=True, noise_threshold=0):
train_transform = transforms.Compose(
[transforms.Grayscale(num_output_channels=1),
@@ -52,8 +57,8 @@ def load_data(base_dir, batch_size, shuffle=True, noise_threshold=0):
Log_normalisation(),
transforms.Normalize(0.5, 0.5)])
print('Default val transform')
- train_dataset = torchvision.datasets.ImageFolder(root=base_dir, transform=train_transform)
- val_dataset = torchvision.datasets.ImageFolder(root=base_dir, transform=val_transform)
+ train_dataset = torchvision.datasets.ImageFolder(root=base_dir, transform=train_transform,loader=npy_loader)
+ val_dataset = torchvision.datasets.ImageFolder(root=base_dir, transform=val_transform, loader=npy_loader)
train_dataset, _ = train_test_split(train_dataset, test_size=None, train_size=None, random_state=42, shuffle=True,
stratify=True)
@@ -86,10 +91,6 @@ def load_data(base_dir, batch_size, shuffle=True, noise_threshold=0):
def default_loader(path):
return Image.open(path).convert('RGB')
-def npy_loader(path):
- sample = torch.from_numpy(np.load(path))
- sample = sample.unsqueeze(0)
- return sample
def remove_aer_ana(l):
l = map(lambda x : x.split('_')[0],l)
diff --git a/main_ray.py b/main_ray.py
index 6734eca..2a32229 100644
--- a/main_ray.py
+++ b/main_ray.py
@@ -26,7 +26,7 @@ def train_model(config,args):
)
# load model
- model = Classification_model_duo(model=args.model, n_class=len(data_train.dataset.classes))
+ model = Classification_model_duo(model=args.model, n_class=len(data_train.dataset.dataset.classes))
# move parameters to GPU
model.float()
@@ -144,7 +144,7 @@ def test_model(best_result, args):
noise_threshold=best_result.config['noise'])
# load model
- model = Classification_model_duo(model=args.model, n_class=len(data_test.dataset.classes))
+ model = Classification_model_duo(model=args.model, n_class=len(data_test.dataset.dataset.classes))
model.float()
# load weight
checkpoint_path = os.path.join(best_result.checkpoint.to_directory(), "checkpoint.pt")
--
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