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feature_extract.py

+import numpy as np
+from kit.mics import *
+import json
+from tqdm.auto import tqdm
+
+counts = 0
+data_path = 'data/'
+results_path = 'results/'
+pic_dict = np.load(os.path.join(data_path,'materials_pic.npz'),allow_pickle=True)['materials_pic'].item()
+isolabel = json.load(open(os.path.join(data_path,'isolabel.json')))
+
+csv_folder = 'extracted_features/'
+name_list = [x.split(".")[0] for x in os.listdir(os.path.join(data_path,csv_folder))]
+
+new_material = []
+for key in pic_dict.keys():
+    if key not in name_list:
+        new_material.append(key)
+
+for n,key in enumerate(tqdm(new_material)):
+    results_array = np.empty((0,14))  # new empty array for each new material
+    counts = 0
+    for k in tqdm(range(20),leave=False):   #data aug
+        tf = 0 if k == 0 else 1
+        for j,img in enumerate(pic_dict[key]):
+            tmp = get_ae_2d(img,key,isolabel[key],j+counts,tf)
+            results_array = np.vstack((results_array,tmp)) 
+        counts += pic_dict[key].shape[0]
+    all_aug_df = pd.DataFrame(results_array)
+    all_aug_df.columns = ['Sample No',"Material","Layer","Intensity",'Intensity_index','Eccentricity','Ellipse angle','pca_eps','pca_angle','isotropy label','blur','transform','evr1','evr2']
+    all_aug_df.to_csv((os.path.join(data_path,f'{csv_folder}{key}.csv')))
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