Refactor code #7
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config.py
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| @@ -19,13 +19,16 @@ | |||
| BATCH_SIZE = 32 | |||
| NUM_CLASSES = 4 | |||
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| # epochs | |||
| EPOCHS=50 | |||
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epoch should be lied in above group.
fit_model.py
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| nb_samples = validate_df.shape[0] | ||
| predict = model.predict(validation_generator, steps=np.ceil(nb_samples/BATCH_SIZE)) | ||
| validate_df['pred'] = np.argmax(predict, axis=-1) | ||
| nb_samples = test_df.shape[0] |
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some comments here maybe better
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| # const |
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you should explain its use not its type
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they are constant values so we just comment to understand what it is. their usage will be known where they are used
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when we use uppercase word and underscore between, it is constant, so you dont have to comment like that
generator.py
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| validation_datagen = ImageDataGenerator(rescale=1./255) | ||
| validation_generator = validation_datagen.flow_from_dataframe( | ||
| validate_df, | ||
| test_datagen = ImageDataGenerator(rescale=1./255) |
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some comments here may be better
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like why do you choose 1./255 ?
open_cam.py
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| keras_model = load_model('model.h5') | ||
| # facenet |
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comments its use not its name dude :)
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:) no here is comment for definition not where it take action. only declaration
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i think you can remove this comment, because it's not nescessary
| keras_model = load_model('model.h5') | ||
| # facenet | ||
| facenet = cv2.dnn.readNetFromCaffe(CAFFE_PROTO_FILE, MODEL_FILE) |
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for example, load predictive model from prototype and trained model file caffenet which is for detecting human face
| facenet = cv2.dnn.readNetFromCaffe(CAFFE_PROTO_FILE, MODEL_FILE) | ||
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| # labels |
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maybe explains about the color and structure is better
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here can easily understand sir
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oh really, so why you have to name variable is label ? (51, 153, 255) -> color ?
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| # pca model |
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this code is not running right ?
you can remove it
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change the README.md file also, for example, python3 open_cam.py is no way work because there is no open_cam.py file in current directory |
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@sherlockvn I have resolved all comments. please take a look at my PR again. |
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