First commit for brain tumor prediction app

class_names.txt

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+glioma_tumor
+meningioma_tumor
+no_tumor
+pituitary_tumor

model.py

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+import torch
+import torchvision
+from torch import nn
+
+def create_model(num_classes:int=4,
+                 seed:int=42):
+  # Create Effnet pretrained model
+  weights= torchvision.models.EfficientNet_B0_Weights.DEFAULT
+  transforms= weights.transforms()
+  model= torchvision.models.efficientnet_b0(weights=weights)
+
+  # Freeze all layers in the base model
+  for param in model.parameters():
+    param.requires_grad= False
+
+  # Change the classifier layer
+  torch.manual_seed(seed)
+  model.classifier= nn.Sequential(
+    nn.Dropout(p=0.2, inplace= True),
+    nn.Linear(in_features= 1280, out_features= num_classes)
+    )
+  return model, transforms

pretrained_effnetb0_feature_extractor_brain_tumor.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:8d8e9719814b37a85a389711d67b9b5aed69f433acebba429713765375f16a42
+size 16365077

requirements.txt

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+torch==2.0.1
+torchvision==0.15.2
+gradio==3.35.2