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人工智能系统实战第三期/实战代码/深度学习项目实战/神经网络实现鸢尾花分类/data_loader.py

+from torch.utils.data import Dataset  
+from torch.utils.data import Dataset  
+import os
+import pandas as pd
+import numpy as np 
+import torch 
+
+class iris_dataload(Dataset):
+    def __init__(self, data_path: str, transform=None):
+        self.data_path = data_path 
+        self.transform = transform
+ 
+        assert os.path.exists(data_path), "dataset root: {} does not exist.".format(data_path) 
+        df = pd.read_csv(self.data_path , names=[0,1,2,3,4])
+        d = {'Iris-setosa':0, 'Iris-versicolor':1, 'Iris-virginica':2}
+        df[4]=df[4].map(d)
+        data=df.iloc[:,0:4]
+        label=df.iloc[:,4:]
+
+        data=np.array(data)
+        data = (data - np.mean(data) )/ np.std(data) 
+        label=np.array(label) 
+
+        self.data=torch.from_numpy(np.array(data,dtype='float32') )   
+        self.label= torch.from_numpy(np.array(label,dtype='int64') ) 
+
+        self.data_num = len(label)  # 存储训练集的所有图片路径
+        print("{} images were found in the dataset.".format(self.data_num))
+
+    def __len__(self):
+        return self.data_num
+    
+    def __getitem__(self, idx):
+        self.data = list(self.data)
+        self.label = list(self.label)
+        return self.data[idx], self.label[idx]
+
+
+# if __name__ == '__main__':
+#     custom_dataset = iris_dataload( "./Iris_data.txt")
+#     print(custom_dataset)
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