66 lines
2.4 KiB
Python
Executable File
66 lines
2.4 KiB
Python
Executable File
#!/usr/bin/python3
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#
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# witzit-load.py
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#
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# Copyright (C) 2022, Jeff Moe
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#
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# This program is free software: you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation, either version 3 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program. If not, see <http://www.gnu.org/licenses/>.
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#
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# wz-load
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# Load a sample from a SciAps LIBS
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#
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# Sample files can be found here:
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# https://ordar.otelo.univ-lorraine.fr/record?id=10.24396/ORDAR-65
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#
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# Usage:
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# witzit-load.py
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# Example:
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# witzit-load.py
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import os
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import json
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import numpy as np
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import pandas as pd
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import datetime
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import tensorflow as tf
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import tensorflow.python.keras
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import matplotlib.pyplot as plt
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from tensorflow.keras.layers import Dense, Conv2D, Flatten, Dropout, MaxPooling2D
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from tensorflow.python.keras import optimizers
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from tensorflow.python.keras import Sequential
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from tensorflow.python.keras.layers import Activation, Dropout, Flatten, Dense
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from tensorflow.python.keras.layers import Convolution2D, MaxPooling2D, ZeroPadding2D
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from tensorflow.python.keras.layers import Input, concatenate
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from tensorflow.python.keras.models import load_model
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from tensorflow.python.keras.models import Model
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from tensorflow.python.keras.preprocessing import image
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from tensorflow.python.keras.preprocessing.image import img_to_array
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from tensorflow.python.keras.preprocessing.image import ImageDataGenerator
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from tensorflow.python.keras.preprocessing.image import load_img
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# from tensorflow.python.keras.utils import plot_model
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from tensorflow.python.keras.callbacks import ModelCheckpoint
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print("Tensorflow Version: ", tf.__version__)
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print("Num GPUs Available: ", len(tf.config.experimental.list_physical_devices("GPU")))
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print("Num CPUs Available: ", len(tf.config.experimental.list_physical_devices("CPU")))
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print(tf.config.experimental.list_physical_devices())
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file_url = "samples/BAJ4B-S4b/BAJ4B-S4b_20200504_095456_AM_Spectrum_PixelData.csv"
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# Read with panda for now...
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dataframe = pd.read_csv(file_url)
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print(dataframe)
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