qurator-spk/sbb_pixelwise_segmentation
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updating train.py nontransformer backend

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vahidrezanezhad 2024-06-10 22:15:30 +02:00
parent 815e5a1d35
commit 41a0e15e79
2 changed files with 18 additions and 7 deletions
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12
train.py
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@ -97,8 +97,6 @@ def run(_config, n_classes, n_epochs, input_height,
pretraining, learning_rate, task, f1_threshold_classification, classification_classes_name):
if task == "segmentation" or task == "enhancement":
num_patches = transformer_num_patches_xy[0]*transformer_num_patches_xy[1]
if data_is_provided:
dir_train_flowing = os.path.join(dir_output, 'train')
dir_eval_flowing = os.path.join(dir_output, 'eval')
@ -213,7 +211,15 @@ def run(_config, n_classes, n_epochs, input_height,
index_start = 0
if backbone_type=='nontransformer':
model = resnet50_unet(n_classes, input_height, input_width, task, weight_decay, pretraining)
elif backbone_type=='nontransformer':
elif backbone_type=='transformer':
num_patches = transformer_num_patches_xy[0]*transformer_num_patches_xy[1]
if not (num_patches == (input_width / 32) * (input_height / 32)):
print("Error: transformer num patches error. Parameter transformer_num_patches_xy should be set to (input_width/32) = {} and (input_height/32) = {}".format(int(input_width / 32), int(input_height / 32)) )
sys.exit(1)
if not (transformer_patchsize == 1):
print("Error: transformer patchsize error. Parameter transformer_patchsizeshould set to 1" )
sys.exit(1)
model = vit_resnet50_unet(n_classes, transformer_patchsize, num_patches, input_height, input_width, task, weight_decay, pretraining)
#if you want to see the model structure just uncomment model summary.