1:n modified

contrast/feat_infer.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Fri Feb 28 16:27:17 2025
+
+@author: ym
+"""
+
+import os
+import time
+import pickle
+import numpy as np
+from PIL import Image
+from scipy.spatial.distance import cdist
+from feat_extract.config import config as conf
+from feat_extract.inference import FeatsInterface #, inference_image
+
+Encoder = FeatsInterface(conf)
+
+
+    
+
+
+
+def main():
+    imgpaths = r"D:\全实时\202502\result\Yolos_Tracking\20250228-160049-188_6921168558018_6921168558018\a"
+    featDict = {}
+    imgs, imgfiles = [], []
+    for filename in os.listdir(imgpaths):
+        file, ext = os.path.splitext(filename)
+        
+        imgpath = os.path.join(imgpaths, filename)
+        img = Image.open(imgpath)
+        
+        imgs.append(img)
+        imgfiles.append(filename)
+        
+        feature = Encoder.inference([img])
+        feature /= np.linalg.norm(feature, axis=1)[:, None]
+        feature_ft32 = feature.astype(np.float32)
+    
+        
+        
+        featDict[file] = feature_ft32
+        
+    feature = Encoder.inference(imgs)
+    feature /= np.linalg.norm(feature, axis=1)[:, None]
+    feature_ft32 = feature.astype(np.float32)
+    
+    
+    matrix = 1 - cdist(feature, feature, 'cosine')
+        
+    print("do")
+        
+
+
+
+if __name__ == '__main__':
+    main()