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