python 与机器学习实战， 修订源码，python3

[1]:https://github.com/carefree0910/ImageRecognition/tree/master [2]:https://storage.googleapis.com/download.tensorflow.org/models/inception_dec_2015.zip "Inception-v3" # Image Recognition Dependency: numpy, matplotlib, Tensorflow, cv2(For visualization) A Stand-alone version for this project can be found [here][1] + Inception-v3 model for this project can be downloaded [here][2] + Extract the zipped file and put Inception-v3 model (which should be renamed from 'tensorflow_inception_graph.pb' to 'Model.pb') to 'Models/Extractor/v3' folder + Put your training set **FOLDERS** into '_Data' folder, please use English names for your folders to ensure that cv2 works correctly + Each folder name should be treated as the 'label' of the pictures contained in the folder + Put your test set **PICTURES** into 'Test' folder + If possible, put a **ONE-HOT** answer naming '_answer.npy' into 'Test' folder as well for better visualization + If you don't want to struggle for these, just leave 'Test' folder empty (Reference the Notice below) + Run 'Main.py'! + Run 'Main.py' in PyCharm will be perfectly correct. If you want to run it by double-clicking, some import statements may need to be modified + You may want a [Stand-alone version][1] for this project, where you can run it by double-clicking 'Main.py' without modifying any import statement! ## Notice That: + If 'Test' folder remains empty when the program is running, `min(196, 0.2 * n_data)`pictures will be **MOVED** from '_Data' folder to 'Test' folder if 'gen_test' FLAG is True + An '_answer.npy' ndarray will also be generated automatically! + After processing all images in '_Data' folder, a '_Cache' folder which contains 'features.npy' and 'labels.npy' (shuffled) will be generated + If you want to train on new dataset, '_Cache' folder should be deleted + You can train your own classifier using 'features.npy' and 'labels.npy' + After the program is done, a Predictor will be stored in 'Models/Predictors/v3' folder. If you want to train on new dataset, this folder should be deleted --args: parser.add_argument( "--gen_test", type=bool, default=True, help="Whether generate test images" ) parser.add_argument( "--images_dir", type=str, default="Test", help="Path to test set" ) parser.add_argument( "--extract_only", type=bool, default=False, help="Whether extract features only" ) parser.add_argument( "--visualize_only", type=bool, default=False, help="Whether visualize only" ) parser.add_argument( "--overview", type=bool, default=True, help="Whether use cv2 to overview" ) ## Visualization   *(Not so elegant, but (maybe) better than nothing...)*