dima806/military_aircraft_image_detection

🤗 Hugging Face 来源image-classificationapache-2.086M 参数343 MBsafetensors✓ 77 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo dima806/military_aircraft_image_detection ./model-folder
需要做种者 →

Returns military aircraft type given cropped image with about 76% accuracy.

See https://www.kaggle.com/code/dima806/military-aircraft-detection-vit for more details.

Classification report:

              precision    recall  f1-score   support

         A10     0.8156    0.8889    0.8507       612
       A400M     0.8641    0.7794    0.8196       612
       AG600     0.9452    0.9592    0.9521       612
        AV8B     0.4991    0.9003    0.6422       612
          B1     0.8358    0.8154    0.8255       612
          B2     0.8924    0.9624    0.9261       612
         B52     0.9354    0.7337    0.8223       612
       Be200     0.8491    0.8922    0.8701       612
        C130     0.9104    0.4984    0.6441       612
         C17     0.8045    0.5310    0.6398       612
          C2     0.7765    0.8971    0.8324       612
          C5     0.6826    0.7239    0.7026       612
          E2     0.8866    0.9706    0.9267       612
          E7     0.8045    0.9951    0.8897       612
      EF2000     0.7348    0.2173    0.3354       612
        F117     0.8298    0.9722    0.8954       612
         F14     0.6531    0.7075    0.6792       612
         F15     0.6058    0.2059    0.3073       612
         F16     0.5390    0.2598    0.3506       612
         F18     0.5905    0.5866    0.5885       612
         F22     0.6273    0.7369    0.6777       612
         F35     0.5764    0.6536    0.6126       612
          F4     0.6749    0.3562    0.4663       612
          H6     0.9245    0.9199    0.9222       612
         J10     0.5846    0.6209    0.6022       612
         J20     0.8477    0.5458    0.6640       612
       JAS39     0.5615    0.4771    0.5159       612
        JF17     0.4866    0.9477    0.6430       612
       KC135     0.7706    0.9167    0.8373       612
         MQ9     0.8618    0.9167    0.8884       612
       Mig31     0.7900    0.6699    0.7250       612
  Mirage2000     0.8333    0.3758    0.5180       612
          P3     0.7997    0.9265    0.8584       612
         RQ4     0.8433    0.9412    0.8896       612
      Rafale     0.4622    0.5801    0.5145       612
        SR71     0.9030    0.9281    0.9154       612
        Su24     0.7059    0.6275    0.6644       612
        Su25     0.8569    0.8023    0.8287       612
        Su34     0.8042    0.8856    0.8429       612
        Su57     0.7061    0.8873    0.7864       612
     Tornado     0.6004    0.5523    0.5753       612
       Tu160     0.8468    0.9575    0.8988       612
       Tu22M     0.7758    0.9444    0.8519       612
        Tu95     0.9271    0.8938    0.9101       612
          U2     0.9094    0.7712    0.8347       612
         US2     0.7837    0.9118    0.8429       612
         V22     0.8788    0.9363    0.9066       612
      Vulcan     0.8971    0.8693    0.8830       612
        XB70     0.8857    1.0000    0.9394       612
        YF23     0.8673    0.9935    0.9261       612

    accuracy                         0.7608     30600
   macro avg     0.7690    0.7608    0.7488     30600
weighted avg     0.7690    0.7608    0.7488     30600