HyperFree/Extract_Backbone_Features.py at main · Jingtao-Li-CVer/HyperFree · GitHub

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import sys
import os

sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir, os.pardir)))

import numpy as np
import torch

from HyperFree.utils.spectral_process_utils import read_img, write_img
from HyperFree import SamAutomaticMaskGenerator, HyperFree_model_registry, HyperFree_Predictor
import cv2
import matplotlib.pyplot as plt
from skimage.transform import resize

"""
HyperFree
Output multi-level backbone features for tuning.
"""

device = 'cuda:2'
wavelengths = [
    401.809998, 404.031006, 406.252014, 408.472992, 410.694000, 412.915009,
    415.135986, 417.356995, 419.578003, 421.799988, 424.020996, 426.242004,
    428.463013, 430.683990, 432.904999, 435.126007, 437.346985, 439.567993,
    441.789001, 444.010010, 446.230988, 448.451996, 450.674011, 452.894989,
    455.115997, 457.337006, 459.558014, 461.778992, 464.000000, 466.221008,
    468.441986, 470.662994, 472.884003, 475.105011, 477.326996, 479.548004,
    481.769012, 483.989990, 486.210999, 488.432007, 490.653015, 492.873993,
    495.095001, 497.316010, 499.536987, 501.757996, 503.979004, 506.200989,
    508.421997, 510.643005, 512.864014, 515.085022, 517.306030, 519.526978,
    521.747986, 523.968994, 526.190002, 528.411011, 530.632019, 532.854004,
    535.075012, 537.296021, 539.517029, 541.737976, 543.958984, 546.179993,
    548.401001, 550.622009, 552.843018, 555.064026, 557.284973, 559.505981,
    561.728027, 563.948975, 566.169983, 568.390991, 570.612000, 572.833008,
    575.054016, 577.275024, 579.495972, 581.716980, 583.937988, 586.158997,
    588.380981, 590.601990, 592.822998, 595.044006, 597.265015, 599.486023,
    601.706970, 603.927979, 606.148987, 608.369995, 610.591003, 612.812012,
    615.033020, 617.255005, 619.476013, 621.697021, 623.918030, 626.138977,
    628.359985, 630.580994, 632.802002, 635.023010, 637.244019, 639.465027,
    641.685974, 643.908020, 646.129028, 648.349976, 650.570984, 652.791992,
    655.013000, 657.234009, 659.455017, 661.676025, 663.896973, 666.117981,
    668.338989, 670.559998, 672.781982, 675.002991, 677.223999, 679.445007,
    681.666016, 683.887024, 686.107971, 688.328979, 690.549988, 692.770996,
    694.992004, 697.213013, 699.434998, 701.656006, 703.877014, 706.098022,
    708.318970, 710.539978, 712.760986, 714.981995, 717.203003, 719.424011,
    721.645020, 723.866028, 726.086975, 728.309021, 730.530029, 732.750977,
    734.971985, 737.192993, 739.414001, 741.635010, 743.856018, 746.077026,
    748.297974, 750.518982, 752.739990, 754.961975, 757.182983, 759.403992,
    761.625000, 763.846008, 766.067017, 768.288025, 770.508972, 772.729980,
    774.950989, 777.171997, 779.393005, 781.614014, 783.835999, 786.057007,
    788.278015, 790.499023, 792.719971, 794.940979, 797.161987, 799.382996,
    801.604004, 803.825012, 806.046021, 808.267029, 810.489014, 812.710022,
    814.931030, 817.151978, 819.372986, 821.593994, 823.815002, 826.036011,
    828.257019, 830.478027, 832.698975, 834.919983, 837.140991, 839.362976,
    841.583984, 843.804993, 846.026001, 848.247009, 850.468018, 852.689026,
    854.909973, 857.130981, 859.351990, 861.572998, 863.794006, 866.015991,
    868.237000, 870.458008, 872.679016, 874.900024, 877.120972, 879.341980,
    881.562988, 883.783997, 886.005005, 888.226013, 890.447021, 892.668030,
    894.890015, 897.111023, 899.331970, 901.552979, 903.773987, 905.994995,
    908.216003, 910.437012, 912.658020, 914.879028, 917.099976, 919.320984,
    921.543030, 923.763977, 925.984985, 928.205994, 930.427002, 932.648010,
    934.869019, 937.090027, 939.310974, 941.531982, 943.752991, 945.973999,
    948.195007, 950.416992, 952.638000, 954.859009, 957.080017, 959.301025,
    961.521973, 963.742981, 965.963989, 968.184998, 970.406006, 972.627014,
    974.848022, 977.070007, 979.291016, 981.512024, 983.732971, 985.953979,
    988.174988, 990.395996, 992.617004, 994.838013, 997.059021, 999.280029]
GSD = 0.456  # Ground sampling distance (m/pixel)

data_path = "/home/ljt21/LYY/mmdetection/SpectraF/data/WHU-Hi-LongKou.tif"
ckpt_pth = "/home/ljt21/LYY/mmdetection/SpectraF/ckpts/SpectralF_0716V2.pth"
save_dir = "/home/ljt21/LYY/mmdetection/HyperFree-CVPR2025/Outputs/"

img = read_img(data_path)

height, width = img.shape[0], img.shape[1]

ratio = 1024 / (max(height, width))
GSD = GSD / ratio
GSD = torch.tensor([GSD])

HyperFree = HyperFree_model_registry["vit_b"](checkpoint=ckpt_pth, image_size=1024, vit_patch_size=4, encoder_global_attn_indexes=[5, 8, 11], merge_indexs = [2, 4, 7]).to(device)
HyperFree = HyperFree.to(device)
predictor = HyperFree_Predictor(HyperFree)
predictor.set_image(img, False, wavelengths, GSD,)

multi_scale_features = predictor.multi_scale_features
print(len(multi_scale_features))