diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..a3ac0ed
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,7 @@
+.env
+*.csv
+*.npy
+*.pth
+*.pkl
+*.pyc
+*.txt
\ No newline at end of file
diff --git a/WiGesture/data_process_example/process1.py b/WiGesture/data_process_example/process1.py
index 36163d3..3096590 100644
--- a/WiGesture/data_process_example/process1.py
+++ b/WiGesture/data_process_example/process1.py
@@ -3,8 +3,8 @@
 import os
 import pandas as pd
 
-root="./data"
-data=[]
+root = "./data"
+data = []
 csi_vaid_subcarrier_index = range(0, 52)
 
 def handle_complex_data(x, valid_indices):
@@ -15,44 +15,95 @@ def handle_complex_data(x, valid_indices):
         imag_parts.append(x[i * 2 - 1])
     return np.array(real_parts) + 1j * np.array(imag_parts)
 
+people_id = 0
+for dataset_dir in os.listdir(root):
+    print(dataset_dir)
+    dataset_path = os.path.join(root, dataset_dir)
+    if not os.path.isdir(dataset_path):
+        continue
+    
+    for static_dir in os.listdir(dataset_path):
+        print(static_dir)
+        static_path = os.path.join(dataset_path, static_dir)
+        if not os.path.isdir(static_path):
+            continue
+        
+        for id_dir in os.listdir(static_path):
+            id_path = os.path.join(static_path, id_dir)
+            if not os.path.isdir(id_path):
+                continue
+            
+            print(f"Processing ID: {id_dir}")
+            action_id = 0
+            
+            # Verifique se há arquivos CSV diretamente no diretório ID
+            for item in os.listdir(id_path):
+                item_path = os.path.join(id_path, item)
+                
+                # Se for um diretório, considere como um diretório de ação
+                if os.path.isdir(item_path):
+                    action_dir = item
+                    print(f"  Action: {action_dir}")
+                    
+                    # Processe os arquivos CSV dentro do diretório de ação
+                    for file in os.listdir(item_path):
+                        if not file.endswith('.csv'):
+                            continue
+                        
+                        file_path = os.path.join(item_path, file)
+                        try:
+                            df = pd.read_csv(file_path)
+                            df.dropna(inplace=True)
+                            df['data'] = df['data'].apply(lambda x: eval(x))
+                            complex_data = df['data'].apply(lambda x: handle_complex_data(x, csi_vaid_subcarrier_index))
+                            magnitude = complex_data.apply(lambda x: np.abs(x))
+                            phase = complex_data.apply(lambda x: np.angle(x, deg=True))
+                            time = np.array(df['timestamp'])
+                            local_time = np.array(df['local_timestamp'])
+                            
+                            data.append({
+                                'csi_time': time,
+                                'csi_local_time': local_time,
+                                'volunteer_name': id_dir,
+                                'volunteer_id': people_id,
+                                'action': action_dir,
+                                'action_id': action_id,
+                                'magnitude': np.array([np.array(a) for a in magnitude]),
+                                'phase': np.array([np.array(a) for a in phase])
+                            })
+                        except Exception as e:
+                            print(f"    Error processing {file_path}: {e}")
+                    
+                    action_id += 1
+                
+                # Se for um arquivo CSV, processe-o diretamente
+                elif item.endswith('.csv'):
+                    try:
+                        df = pd.read_csv(item_path)
+                        df.dropna(inplace=True)
+                        df['data'] = df['data'].apply(lambda x: eval(x))
+                        complex_data = df['data'].apply(lambda x: handle_complex_data(x, csi_vaid_subcarrier_index))
+                        magnitude = complex_data.apply(lambda x: np.abs(x))
+                        phase = complex_data.apply(lambda x: np.angle(x, deg=True))
+                        time = np.array(df['timestamp'])
+                        local_time = np.array(df['local_timestamp'])
+                        
+                        data.append({
+                            'csi_time': time,
+                            'csi_local_time': local_time,
+                            'volunteer_name': id_dir,
+                            'volunteer_id': people_id,
+                            'action': 'unknown',
+                            'action_id': 0,
+                            'magnitude': np.array([np.array(a) for a in magnitude]),
+                            'phase': np.array([np.array(a) for a in phase])
+                        })
+                    except Exception as e:
+                        print(f"  Error processing {item_path}: {e}")
+            
+            people_id += 1
 
-
-people_id=0
-for people in os.listdir(root):
-    print(people)
-    action_id=0
-    path_people=os.path.join(root,people)
-    for action in os.listdir(path_people):
-        count=0
-        print(action)
-        path_action=os.path.join(path_people,action)
-        for file in os.listdir(path_action):
-            count+=1
-            path=os.path.join(path_action,file)
-            df = pd.read_csv(path)
-            df.dropna(inplace=True)
-            df['data'] = df['data'].apply(lambda x: eval(x))
-            complex_data = df['data'].apply(lambda x: handle_complex_data(x, csi_vaid_subcarrier_index))
-            magnitude = complex_data.apply(lambda x: np.abs(x))
-            phase = complex_data.apply(lambda x: np.angle(x, deg=True))
-            time = np.array(df['timestamp'])
-            local_time = np.array(df['local_timestamp'])
-            data.append({
-                'csi_time':time,
-                'csi_local_time':local_time,
-                'volunteer_name': people,
-                'volunteer_id': people_id,
-                'action': action,
-                'action_id': action_id,
-                'magnitude': np.array([np.array(a) for a in magnitude]),
-                'phase': np.array([np.array(a) for a in phase])
-            })
-            # if count==4:
-            #     break
-        action_id+=1
-    people_id+=1
-
-# 保存全局字典为一个pickle文件
+# Salve o dicionário global como um arquivo pickle
 output_file = './csi_data.pkl'
 with open(output_file, 'wb') as f:
-    pickle.dump(data, f)
\ No newline at end of file
+    pickle.dump(data, f)