基于TensorFlow2.3深度学习框架所开发，可以识别多种花朵，整体识别率达到95%左右.zip

absl-py==1.2.0 astor==0.8.1 astunparse==1.6.3 atomicwrites==1.4.1 attrs==22.1.0 cachetools==4.2.4 charset-normalizer==2.1.0 colorama==0.4.5 contextlib2==21.6.0 cycler==0.11.0 execnet==1.9.0 fonttools==4.34.4 gast==0.3.3 google-auth==1.35.0 google-auth-oauthlib==0.4.6 google-pasta==0.2.0 grpcio==1.48.0 h5py==2.10.0 idna==3.3 importlib-metadata==4.12.0 iniconfig==1.1.1 Keras-Applications==1.0.8 Keras-Preprocessing==1.1.2 kiwisolver==1.4.4 Markdown==3.4.1 MarkupSafe==2.1.1 matplotlib==3.5.2 mock==4.0.3 numpy==1.18.5 oauthlib==3.2.0 opencv-python==4.6.0.66 opt-einsum==3.3.0 packaging==21.3 path==16.4.0 path.py==12.5.0 Pillow==9.2.0 pluggy==1.0.0 protobuf==3.19.4 py==1.11.0 pyasn1==0.4.8 pyasn1-modules==0.2.8 pyparsing==3.0.9 PyQt5==5.15.7 PyQt5-Qt5==5.15.2 PyQt5-sip==12.11.0 pytest==7.1.2 python-dateutil==2.8.2 requests==2.28.1 requests-oauthlib==1.3.1 rsa==4.9 scipy==1.4.1 six==1.16.0 tensorboard==2.9.1 tensorboard-data-server==0.6.1 tensorboard-plugin-wit==1.8.1 tensorflow==2.3.0 tensorflow-estimator==2.3.0 termcolor==1.1.0 tomli==2.0.1 typing_extensions==4.3.0 urllib3==1.26.11 Werkzeug==2.2.1 wincertstore==0.2 wrapt==1.14.1 XlsxWriter==3.0.3 zipp==3.8.1