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Photovoltaic_Fault_Detector/GPS_Panel/Classifier/Train_Classifier_AllDeep.ipynb
Daniel Saavedra 0248207c91 SVM
2020-10-08 22:09:30 -03:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# import the necessary packages\n",
"from imutils import paths\n",
"import numpy as np\n",
"import argparse\n",
"import imutils\n",
"import pickle\n",
"import cv2\n",
"import os\n",
"from sklearn.preprocessing import LabelEncoder\n",
"from sklearn.svm import SVC\n",
"from imutils.video import VideoStream\n",
"from imutils.video import FPS\n",
"import time\n",
"import tensorflow as tf\n",
"from tensorflow.keras.layers import *\n",
"from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
"from tensorflow.keras.callbacks import ModelCheckpoint, EarlyStopping\n",
"\n",
"tf.keras.backend.clear_session()"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Found directory: .\n",
"\tTrain_Classifier_AllDeep.ipynb\n",
"\tTrain_Classifier_DEEP_SVC.ipynb\n",
"Found directory: ./.ipynb_checkpoints\n",
"\tTrain_Classifier_AllDeep-checkpoint.ipynb\n",
"\tTrain_Classifier_DEEP_SVC-checkpoint.ipynb\n",
"Found directory: ./dataset_prueba_1\n",
"Found directory: ./dataset_prueba_1/model_SVM\n",
"\tembeddings.pickle\n",
"\tmodel_SVM.h5\n",
"\tle.pickle\n",
"\trecognizer.pickle\n",
"Found directory: ./dataset_prueba_1/7- Soiling\n",
"\tSoling 19 Pampa Camarones M4 2019.jpg\n",
"\tSoling 6 El Aguila M1 2019.jpg\n",
"\tSoling 2 El Aguila M1 2019.jpg\n",
"\tSoling 3 El Aguila M1 2019.jpg\n",
"\tSoling 15 Pampa Camarones M3 2019.jpg\n",
"\tSoling 12 Pampa Camarones M2 2019.jpg\n",
"\tSoling 1 El Aguila M1 2019.jpg\n",
"\tSoling 20 Pampa Camarones M4 2019.jpg\n",
"\tSoling 5 El Aguila M1 2019.jpg\n",
"\tSoling 10 Pampa Camarones M1 2019.jpg\n",
"\tSoling 9 Pampa Camarones M1 2019.jpg\n",
"\tSoling 21 Cerro Dominador M1 2019.jpg\n",
"\tSoling 13 Pampa Camarones M3 2019.jpg\n",
"\tSoling 4 El Aguila M1 2019.jpg\n",
"\tSoling 18 Pampa Camarones M4 2019.jpg\n",
"\tSoling 16 Pampa Camarones M3 2019.jpg\n",
"\tSoling 7 Pampa Camarones M1 2019.jpg\n",
"\tSoling 14 Pampa Camarones M3 2019.jpg\n",
"\tSoling 8 Pampa Camarones M1 2019.jpg\n",
"\tSoling 22 Valle de la Luna M1 2019.jpg\n",
"\tSoling 17 Pampa Camarones M4 2019.jpg\n",
"Found directory: ./dataset_prueba_1/1- Una-Mas Celdas\n",
"\tCinco-Mas Celdas 1 El Aguila M1 2019.jpg\n",
"\tDos-Cuatro Celdas 14 Maria Elena M1 2018.jpg\n",
"\tUna Celda 22 LLano de LLampos M4 2019.jpg\n",
"\tCinco-Mas 4 Cerro Demonidor M2 2019.jpg\n",
"\tUna Celda 10 Cerro Dominador M1 2019.jpg\n",
"\tCinco-Mas Celdas 5 Llano de LLampos M5 2019.jpg\n",
"\tDos-Cuatro Celdas 10 LLano de LLampos M3 2019.jpg\n",
"\tUna Celda 17 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 7 Pampa Camarones M2 2019.jpg\n",
"\tCinco-Mas Celdas 19 Maria Elena M6 2018.jpg\n",
"\tUna Celda 14 Cerro Dominador M1 2019.jpg\n",
"\tDos-Cuatro Celdas 15 Maria Elena M2 2018.jpg\n",
"\tDos-Cuatro Celdas 7 El Aguila M1 2019.jpg\n",
"\tCinco-Mas Celdas 17 Maria Elena M6 2018.jpg\n",
"\tDos-Cuatro Celdas 4 El Aguila M1 2019.jpg\n",
"\tUna Celda 12 Cerro Dominador M1 2019.jpg\n",
"\tDos-Cuatro Celdas 11 LLano de LLampos M5 2019.jpg\n",
"\tDos-Cuatro Celdas 2 El Aguila M1 2019.jpg\n",
"\tDos-Cuatro Celdas 8 Pampa Camarones M2 2019.jpg\n",
"\tCinco-Mas Celdas 20 Maria Elena M6 2018.jpg\n",
"\tCinco-Mas Celdas 11 Maria Elena M1 2018.jpg\n",
"\tCinco-Mas Celdas 18 Maria Elena M6 2018.jpg\n",
"\tCinco-Mas Celdas 15 Maria Elena M3 2018.jpg\n",
"\tDos-Cuatro Celdas 3 El Aguila M1 2019.jpg\n",
"\tDos-Cuatro Celdas 1 El Aguila M1 2019.jpg\n",
"\tDos-Cuatro Celdas 21 Maria Elena M7 2018.jpg\n",
"\tUna Celda 2 - El Aguila M1 2019.jpg\n",
"\tUna Celda 3 El Aguila M1 2019.jpg\n",
"\tCinco-Mas Celdas 14 Maria Elena M3 2018.jpg\n",
"\tDos-Cuatro Celdas 14 Maria Elena M2 2018.jpg\n",
"\tUna Celda 18 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 15 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 19 Cerro Dominador M1 2019.jpg\n",
"\tDos-Cuatro Celdas 12 Maria Elena M1 2018.jpg\n",
"\tCinco-Mas Celdas 9 Maria Elena M1 2018.jpg\n",
"\tCinco-Mas Celdas 7 Maria Elena M1 2018.jpg\n",
"\tCinco-Mas Celdas 6 Maria Elena M1 2018.jpg\n",
"\tUna Celda 1 - Citrino.jpg\n",
"\tUna Celda 23 Valle de la Luna M1 2019.jpg\n",
"\tUna Celda 21 Cerro Dominador M2 2019.jpg\n",
"\tUna Celda 20 Cerro Dominador M2 2019.jpg\n",
"\tUna Celda 9 Pampa Camarones M4 2019.jpg\n",
"\tUna Celda 5 El Aguila M1 2019.jpg\n",
"\tUna Celda 13 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 16 Cerro Dominador M1 2019.jpg\n",
"\tDos-Cuatro Celdas 13 Maria Elena M1 2018.jpg\n",
"\tUna Celda 4 El Aguila M1 2019.jpg\n",
"\tDos-Cuatro Celdas 6 El Aguila M1 2019.jpg\n",
"\tCinco-Mas Celdas 16 Maria Elena M6 2018.jpg\n",
"\tUna Celda 11 Cerro Dominador M1 2019.jpg\n",
"\tCinco-Mas Celdas 8 Maria Elena M1 2018.jpg\n",
"\tCinco-Mas 3 LLano de LLampos M3 2019.jpg\n",
"\tDos-Cuatro Celdas 9 Pampa Camarones M3 2019.jpg\n",
"\tUna Celda 6 El Aguila M1 2019.jpg\n",
"\tCinco-Mas Celdas 13 Maria Elena M3 2018.jpg\n",
"\tDos-Cuatro Celdas 19 Maria Elena M2 2018.jpg\n",
"\tUna Celda 8 Pampa Camarones M3 2019.jpg\n",
"\tDos-Cuatro Celdas 16 Maria Elena M2 2018.jpg\n",
"\tDos-Cuatro Celdas 18 Maria Elena M2 2018.jpg\n",
"\tDos-Cuatro Celdas 20 Maria Elena M3 2018.jpg\n",
"\tCinco-Mas Celdas 12 Maria Elena M1 2018.jpg\n",
"\tCinco-Mas 2 LLano de LLampos M3 2019.jpg\n",
"\tDos-Cuatro Celdas 5 El Aguila M1 2019.jpg\n",
"\tCinco-Mas Celdas 10 Maria Elena M1 2018.jpg\n",
"\tDos-Cuatro Celdas 17 Maria Elena M2 2018.jpg\n",
"Found directory: ./dataset_prueba_1/4- Falla Diodos\n",
"\tUn Diodo 25 Casuto M4 2019.jpg\n",
"\tUn Diodo 7 Pampa Camarones M2 2019.jpg\n",
"\tUn Diodo 19 Pampa Camarones M4 2019.jpg\n",
"\tUn Diodo 14 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 18 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 26 Lllano de LLampos M4 2019.jpg\n",
"\tDos Diodos 2 Tiltil M2 2019.jpg\n",
"\tUn Diodo 11 Pampa Camarones M2 2019.jpg\n",
"\tUn Diodo 6 Pampa Camarones M2 2019.jpg\n",
"\tUn Diodo 22 Tiltil M4 2019.jpg\n",
"\tUn Diodo 1 El Aguila M1 2019.jpg\n",
"\tUn Diodo 23 Tiltil M4 2019.jpg\n",
"\tUn Diodo 24 Casuto M4 2019.jpg\n",
"\tUn Diodo 21 Tiltil M4 2019.jpg\n",
"\tUn Diodo 3 Pampa Camarones M1 2019.jpg\n",
"\tUn Diodo 9 Pampa Camarones M2 2019.jpg\n",
"\tUn Diodo 16 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 15 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 4 Pampa Camarones M1 2019.jpg\n",
"\tUn Diodo 13 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 12 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 1 Pampa Camarones M1 2019.jpg\n",
"\tUn Diodo 8 Pampa Camarones M2 2019.jpg\n",
"\tUn Diodo 20 Pampa Camarones M4 2019.jpg\n",
"\tUn Diodo 10 Pampa Camarones M2 2019.jpg\n",
"\tDos Diodos 1 Tiltil M2 2019.jpg\n",
"\tUn Diodo 17 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 5 Pampa Camarones M2 2019.jpg\n",
"Found directory: ./dataset_prueba_1/9- No es Panel\n",
"\tNo es panel 12 Casuto M1 2019.jpg\n",
"\tNo es panel 5 El Aguila M1 2019.jpg\n",
"\tNo es panel 16 Llano de Llampos M1 2019.jpg\n",
"\tNo es panel 9 Casuto M1 2019.jpg\n",
"\tNo es panel 13 Casuto M1 2019.jpg\n",
"\tNo es panel 3 El Aguila M1 2019.jpg\n",
"\tNo es panel 7 Casuto M1 2019.jpg\n",
"\tNo es panel 15 Casuto M1 2019.jpg\n",
"\tNo es panel 1 El Aguila M1 2019.jpg\n",
"\tNo es panel 2 El Aguila M1 2019.jpg\n",
"\tNo es panel 6 El Aguila M1 2019.jpg\n",
"\tNo es panel 11 Casuto M1 2019.jpg\n",
"\tNo es panel 10 Casuto M1 2019.jpg\n",
"\tNo es panel 14 Casuto M1 2019.jpg\n",
"\tNo es panel 4 El Aguila M1 2019.jpg\n",
"\tNo es panel 17 Cerro Dominador M1 2019.jpg\n",
"\tNo es panel 8 Casuto M1 2019.jpg\n",
"Found directory: ./dataset_prueba_1/8- Tracker dañado\n",
"\tTracker dañado 8 Maria Elena M3 2018.jpg\n",
"\tTracker dañado 13 Maria Elena M3 2018.jpg\n",
"\tTracker dañado 20 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 9 Maria Elena M3 2018.jpg\n",
"\tTracker dañado 11 Maria Elena M3 2018.jpg\n",
"\tTracker dañado 2 Pampa Camarones M1 2019.jpg\n",
"\tTracker dañado 19 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 10 Maria Elena M3 2018.jpg\n",
"\tTracker dañado 4 Pampa Camarones M1 2019.jpg\n",
"\tTracker dañado 15 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 17 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 7 Pampa Camarones M1 2019.jpg\n",
"\tTracker dañado 5 Pampa Camarones M1 2019.jpg\n",
"\tTracker dañado 6 Pampa Camarones M1 2019.jpg\n",
"\tTracker dañado 18 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 13 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 16 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 12 Maria Elena M3 2018.jpg\n",
"\tTracker dañado 1 Pampa Camarones M1 2019.jpg\n",
"\tTracker dañado 3 Pampa Camarones M1 2019.jpg\n",
"Found directory: ./dataset_prueba_1/0- Normal\n",
"\tNormal 30 Valle de La Luna M1 2019.jpg\n",
"\tNormal 16 Tiltil M2 2019.jpg\n",
"\tNormal 3 Citrino.jpg\n",
"\tNormal 20 Casuto M1 2019.jpg\n",
"\tNormal 12 Tiltil M1 2019.jpg\n",
"\tNormal 2 Citrino.jpg\n",
"\tNormal 15 Tiltil M1 2019.jpg\n",
"\tNormal 11 Pampa Camarones M3 2019.jpg\n",
"\tNormal 1 Citrino.jpg\n",
"\tNormal 17 Casuto M1 2019.jpg\n",
"\tNormal 21 Casuto M1 2019.jpg\n",
"\tNormal 5 El Aguila M1 2019.jpg\n",
"\tNormal 14 Tiltil M1 2019.jpg\n",
"\tNormal 6 El Aguila M1 2019.jpg\n",
"\tNormal 25 Llano de Llampos M1 2019.jpg\n",
"\tNormal 10 Pampa Camarones M1 2019.jpg\n",
"\tNormal 9 El Aguila M1 2019.jpg\n",
"\tNormal 27 Llano de Llampos M1 2019.jpg\n",
"\tNormal 19 Casuto M1 2019.jpg\n",
"\tNormal 18 Casuto M1 2019.jpg\n",
"\tNormal 8 El Aguila M1 2019.jpg\n",
"\tNormal 28 Cerro Dominado M1 2019.jpg\n",
"\tNormal 22 Casuto M1 2019.jpg\n",
"\tNormal 4 Citrino.jpg\n",
"\tNormal 24 Llano de Llampos M1 2019.jpg\n",
"\tNormal 23 Casuto M1 2019.jpg\n",
"\tNormal 26 Llano de Llampos M1 2019.jpg\n",
"\tNormal 13 Tiltil M1 2019.jpg\n",
"\tNormal 7 El Aguila M1 2019.jpg\n",
"Found directory: ./dataset_catdog\n",
"Found directory: ./dataset_catdog/train\n",
"\tcat.2414.jpg\n",
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"\tdog.734.jpg\n",
"\tdog.3707.jpg\n",
"\tdog.6569.jpg\n",
"\tdog.3490.jpg\n",
"\tdog.12161.jpg\n",
"\tdog.1144.jpg\n",
"\tdog.4674.jpg\n",
"\tdog.829.jpg\n",
"\tdog.7518.jpg\n",
"\tdog.299.jpg\n",
"\tdog.5397.jpg\n",
"\tdog.11094.jpg\n",
"\tdog.9994.jpg\n",
"\tdog.4891.jpg\n",
"\tdog.9693.jpg\n",
"\tdog.11367.jpg\n",
"\tdog.8106.jpg\n",
"\tdog.4244.jpg\n",
"\tdog.534.jpg\n",
"\tdog.4178.jpg\n",
"\tdog.10256.jpg\n",
"\tdog.3175.jpg\n",
"\tdog.2365.jpg\n",
"\tdog.10919.jpg\n",
"\tdog.8267.jpg\n",
"\tdog.4646.jpg\n",
"\tdog.11457.jpg\n",
"\tdog.7537.jpg\n",
"\tdog.9476.jpg\n",
"\tdog.7911.jpg\n",
"\tdog.2413.jpg\n",
"\tdog.4517.jpg\n",
"\tdog.4863.jpg\n",
"\tdog.1190.jpg\n",
"\tdog.8223.jpg\n",
"\tdog.12270.jpg\n",
"\tdog.1322.jpg\n",
"\tdog.9113.jpg\n",
"\tdog.3318.jpg\n",
"\tdog.197.jpg\n",
"\tdog.8450.jpg\n",
"\tdog.3731.jpg\n",
"\tdog.7586.jpg\n",
"\tdog.10403.jpg\n",
"\tdog.3053.jpg\n",
"\tdog.1983.jpg\n",
"\tdog.1511.jpg\n",
"\tdog.2008.jpg\n",
"\tdog.9762.jpg\n",
"\tdog.72.jpg\n",
"\tdog.6078.jpg\n",
"\tdog.10987.jpg\n",
"\tdog.5352.jpg\n",
"\tdog.3828.jpg\n",
"\tdog.3388.jpg\n",
"\tdog.10960.jpg\n",
"\tdog.4928.jpg\n",
"\tdog.1392.jpg\n",
"\tdog.1501.jpg\n",
"\tdog.1140.jpg\n",
"\tdog.4921.jpg\n",
"\tdog.2314.jpg\n",
"\tdog.3527.jpg\n",
"\tdog.1230.jpg\n",
"\tdog.12123.jpg\n",
"\tdog.6664.jpg\n",
"\tdog.3924.jpg\n",
"\tdog.3456.jpg\n",
"\tdog.4471.jpg\n",
"\tdog.10751.jpg\n",
"\tdog.1419.jpg\n",
"\tdog.8386.jpg\n",
"\tdog.3390.jpg\n",
"\tdog.7533.jpg\n",
"\tdog.330.jpg\n",
"\tdog.231.jpg\n",
"\tdog.1311.jpg\n",
"\tdog.8615.jpg\n",
"\tdog.3758.jpg\n",
"\tdog.7063.jpg\n",
"\tdog.2122.jpg\n",
"\tdog.10511.jpg\n",
"\tdog.6269.jpg\n",
"\tdog.7980.jpg\n",
"\tdog.4587.jpg\n",
"\tdog.287.jpg\n",
"\tdog.8757.jpg\n",
"\tdog.12188.jpg\n",
"\tdog.4317.jpg\n",
"\tdog.1513.jpg\n",
"\tdog.7958.jpg\n",
"\tdog.8786.jpg\n",
"\tdog.5603.jpg\n",
"\tdog.5989.jpg\n",
"\tdog.28.jpg\n",
"\tdog.4685.jpg\n",
"\tdog.4070.jpg\n",
"\tdog.4462.jpg\n",
"\tdog.12287.jpg\n",
"\tdog.2803.jpg\n",
"\tdog.6015.jpg\n",
"\tdog.5893.jpg\n",
"\tdog.11156.jpg\n",
"\tdog.1455.jpg\n",
"\tdog.6807.jpg\n",
"\tdog.9068.jpg\n",
"Found directory: ./dataset_panel\n",
"\tembeddings.pickle\n",
"\tle.pickle\n",
"\trecognizer.pickle\n",
"Found directory: ./dataset_panel/2- Dos-Cuatro Celdas\n",
"\tDos-Cuatro Celdas 14 Maria Elena M1 2018.jpg\n",
"\tDos-Cuatro Celdas 10 LLano de LLampos M3 2019.jpg\n",
"\tDos-Cuatro Celdas 15 Maria Elena M2 2018.jpg\n",
"\tDos-Cuatro Celdas 7 El Aguila M1 2019.jpg\n",
"\tDos-Cuatro Celdas 4 El Aguila M1 2019.jpg\n",
"\tDos-Cuatro Celdas 11 LLano de LLampos M5 2019.jpg\n",
"\tDos-Cuatro Celdas 2 El Aguila M1 2019.jpg\n",
"\tDos-Cuatro Celdas 8 Pampa Camarones M2 2019.jpg\n",
"\tDos-Cuatro Celdas 3 El Aguila M1 2019.jpg\n",
"\tDos-Cuatro Celdas 1 El Aguila M1 2019.jpg\n",
"\tDos-Cuatro Celdas 21 Maria Elena M7 2018.jpg\n",
"\tDos-Cuatro Celdas 14 Maria Elena M2 2018.jpg\n",
"\tDos-Cuatro Celdas 12 Maria Elena M1 2018.jpg\n",
"\tDos-Cuatro Celdas 13 Maria Elena M1 2018.jpg\n",
"\tDos-Cuatro Celdas 6 El Aguila M1 2019.jpg\n",
"\tDos-Cuatro Celdas 9 Pampa Camarones M3 2019.jpg\n",
"\tDos-Cuatro Celdas 19 Maria Elena M2 2018.jpg\n",
"\tDos-Cuatro Celdas 16 Maria Elena M2 2018.jpg\n",
"\tDos-Cuatro Celdas 18 Maria Elena M2 2018.jpg\n",
"\tDos-Cuatro Celdas 20 Maria Elena M3 2018.jpg\n",
"\tDos-Cuatro Celdas 5 El Aguila M1 2019.jpg\n",
"\tDos-Cuatro Celdas 17 Maria Elena M2 2018.jpg\n",
"Found directory: ./dataset_panel/6- Caja Conexion\n",
"\tCaja Conexion 2 Pampa Camarones M3 2019.jpg\n",
"\tCaja Conexion 3 Pampa Camarones M3 2019.jpg\n",
"\tCaja Conexion 1 El Aguila M1 2019.jpg\n",
"\tCaja Conexión 11 Pampa Camarones M1 2019.jpg\n",
"\tCaja Conexión 12 Llano de Llampos M2 2019.jpg\n",
"Found directory: ./dataset_panel/7- Soiling\n",
"\tSoling 19 Pampa Camarones M4 2019.jpg\n",
"\tSoling 6 El Aguila M1 2019.jpg\n",
"\tSoling 2 El Aguila M1 2019.jpg\n",
"\tSoling 3 El Aguila M1 2019.jpg\n",
"\tSoling 15 Pampa Camarones M3 2019.jpg\n",
"\tSoling 12 Pampa Camarones M2 2019.jpg\n",
"\tSoling 1 El Aguila M1 2019.jpg\n",
"\tSoling 20 Pampa Camarones M4 2019.jpg\n",
"\tSoling 5 El Aguila M1 2019.jpg\n",
"\tSoling 10 Pampa Camarones M1 2019.jpg\n",
"\tSoling 9 Pampa Camarones M1 2019.jpg\n",
"\tSoling 21 Cerro Dominador M1 2019.jpg\n",
"\tSoling 13 Pampa Camarones M3 2019.jpg\n",
"\tSoling 4 El Aguila M1 2019.jpg\n",
"\tSoling 18 Pampa Camarones M4 2019.jpg\n",
"\tSoling 16 Pampa Camarones M3 2019.jpg\n",
"\tSoling 7 Pampa Camarones M1 2019.jpg\n",
"\tSoling 14 Pampa Camarones M3 2019.jpg\n",
"\tSoling 8 Pampa Camarones M1 2019.jpg\n",
"\tSoling 22 Valle de la Luna M1 2019.jpg\n",
"\tSoling 17 Pampa Camarones M4 2019.jpg\n",
"Found directory: ./dataset_panel/4- Falla Diodos\n",
"\tUn Diodo 25 Casuto M4 2019.jpg\n",
"\tUn Diodo 7 Pampa Camarones M2 2019.jpg\n",
"\tUn Diodo 19 Pampa Camarones M4 2019.jpg\n",
"\tUn Diodo 14 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 18 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 26 Lllano de LLampos M4 2019.jpg\n",
"\tDos Diodos 2 Tiltil M2 2019.jpg\n",
"\tUn Diodo 11 Pampa Camarones M2 2019.jpg\n",
"\tUn Diodo 6 Pampa Camarones M2 2019.jpg\n",
"\tUn Diodo 22 Tiltil M4 2019.jpg\n",
"\tUn Diodo 1 El Aguila M1 2019.jpg\n",
"\tUn Diodo 23 Tiltil M4 2019.jpg\n",
"\tUn Diodo 24 Casuto M4 2019.jpg\n",
"\tUn Diodo 21 Tiltil M4 2019.jpg\n",
"\tUn Diodo 3 Pampa Camarones M1 2019.jpg\n",
"\tUn Diodo 9 Pampa Camarones M2 2019.jpg\n",
"\tUn Diodo 16 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 15 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 4 Pampa Camarones M1 2019.jpg\n",
"\tUn Diodo 13 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 12 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 1 Pampa Camarones M1 2019.jpg\n",
"\tUn Diodo 8 Pampa Camarones M2 2019.jpg\n",
"\tUn Diodo 20 Pampa Camarones M4 2019.jpg\n",
"\tUn Diodo 10 Pampa Camarones M2 2019.jpg\n",
"\tDos Diodos 1 Tiltil M2 2019.jpg\n",
"\tUn Diodo 17 Pampa Camarones M3 2019.jpg\n",
"\tUn Diodo 5 Pampa Camarones M2 2019.jpg\n",
"Found directory: ./dataset_panel/3- Cinco-Mas Celdas\n",
"\tCinco-Mas Celdas 1 El Aguila M1 2019.jpg\n",
"\tCinco-Mas 4 Cerro Demonidor M2 2019.jpg\n",
"\tCinco-Mas Celdas 5 Llano de LLampos M5 2019.jpg\n",
"\tCinco-Mas Celdas 19 Maria Elena M6 2018.jpg\n",
"\tCinco-Mas Celdas 17 Maria Elena M6 2018.jpg\n",
"\tCinco-Mas Celdas 20 Maria Elena M6 2018.jpg\n",
"\tCinco-Mas Celdas 11 Maria Elena M1 2018.jpg\n",
"\tCinco-Mas Celdas 18 Maria Elena M6 2018.jpg\n",
"\tCinco-Mas Celdas 15 Maria Elena M3 2018.jpg\n",
"\tCinco-Mas Celdas 14 Maria Elena M3 2018.jpg\n",
"\tCinco-Mas Celdas 9 Maria Elena M1 2018.jpg\n",
"\tCinco-Mas Celdas 7 Maria Elena M1 2018.jpg\n",
"\tCinco-Mas Celdas 6 Maria Elena M1 2018.jpg\n",
"\tCinco-Mas Celdas 16 Maria Elena M6 2018.jpg\n",
"\tCinco-Mas Celdas 8 Maria Elena M1 2018.jpg\n",
"\tCinco-Mas 3 LLano de LLampos M3 2019.jpg\n",
"\tCinco-Mas Celdas 13 Maria Elena M3 2018.jpg\n",
"\tCinco-Mas Celdas 12 Maria Elena M1 2018.jpg\n",
"\tCinco-Mas 2 LLano de LLampos M3 2019.jpg\n",
"\tCinco-Mas Celdas 10 Maria Elena M1 2018.jpg\n",
"Found directory: ./dataset_panel/1- Una Celda\n",
"\tUna Celda 22 LLano de LLampos M4 2019.jpg\n",
"\tUna Celda 10 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 17 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 7 Pampa Camarones M2 2019.jpg\n",
"\tUna Celda 14 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 12 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 2 - El Aguila M1 2019.jpg\n",
"\tUna Celda 3 El Aguila M1 2019.jpg\n",
"\tUna Celda 18 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 15 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 19 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 1 - Citrino.jpg\n",
"\tUna Celda 23 Valle de la Luna M1 2019.jpg\n",
"\tUna Celda 21 Cerro Dominador M2 2019.jpg\n",
"\tUna Celda 20 Cerro Dominador M2 2019.jpg\n",
"\tUna Celda 9 Pampa Camarones M4 2019.jpg\n",
"\tUna Celda 5 El Aguila M1 2019.jpg\n",
"\tUna Celda 13 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 16 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 4 El Aguila M1 2019.jpg\n",
"\tUna Celda 11 Cerro Dominador M1 2019.jpg\n",
"\tUna Celda 6 El Aguila M1 2019.jpg\n",
"\tUna Celda 8 Pampa Camarones M3 2019.jpg\n",
"Found directory: ./dataset_panel/9- No es Panel\n",
"\tNo es panel 12 Casuto M1 2019.jpg\n",
"\tNo es panel 5 El Aguila M1 2019.jpg\n",
"\tNo es panel 16 Llano de Llampos M1 2019.jpg\n",
"\tNo es panel 9 Casuto M1 2019.jpg\n",
"\tNo es panel 13 Casuto M1 2019.jpg\n",
"\tNo es panel 3 El Aguila M1 2019.jpg\n",
"\tNo es panel 7 Casuto M1 2019.jpg\n",
"\tNo es panel 15 Casuto M1 2019.jpg\n",
"\tNo es panel 1 El Aguila M1 2019.jpg\n",
"\tNo es panel 2 El Aguila M1 2019.jpg\n",
"\tNo es panel 6 El Aguila M1 2019.jpg\n",
"\tNo es panel 11 Casuto M1 2019.jpg\n",
"\tNo es panel 10 Casuto M1 2019.jpg\n",
"\tNo es panel 14 Casuto M1 2019.jpg\n",
"\tNo es panel 4 El Aguila M1 2019.jpg\n",
"\tNo es panel 17 Cerro Dominador M1 2019.jpg\n",
"\tNo es panel 8 Casuto M1 2019.jpg\n",
"Found directory: ./dataset_panel/5- Panel Desconectado\n",
"\tPanel Desconectado 24 Llano de LLampos M3 2019.jpg\n",
"\tPanel Desconectado 6 Pampa Camarones M1 2019.jpg\n",
"\tPanel Desconectado 19 Pampa Camarones M3 2019.jpg\n",
"\tPanel Desconectado 9 Pampa Camarones M2 2019.jpg\n",
"\tPanel Desconectado 12 Pampa Camarones M3 2019.jpg\n",
"\tPanel Desconectado 10 Pampa Camarones M2 2019.jpg\n",
"\tPanel Desconectado 21 Pampa Camarones M3 2019.jpg\n",
"\tPanel Desconectado 4 Pampa Camarones M1 2019.jpg\n",
"\tPanel Desconectado 25 Llano de LLampos M3 2019.jpg\n",
"\tPanel Desconectado 23 Llano de LLampos M2 2019.jpg\n",
"\tPanel Desconectado 20 Pampa Camarones M3 2019.jpg\n",
"\tPanel Desconectado 11 Pampa Camarones M2 2019.jpg\n",
"\tPanel Desconectado 15 Pampa Camarones M3 2019.jpg\n",
"\tPanel Desconectado 1 El Aguila M2 2019.jpg\n",
"\tPanel Desconectado 16 Pampa Camarones M3 2019.jpg\n",
"\tPanel Desconectado 14 Pampa Camarones M3 2019.jpg\n",
"\tPanel Desconectado 18 Pampa Camarones M3 2019.jpg\n",
"\tPanel Desconectado 22 Tiltil M2 2019.jpg\n",
"\tPanel Desconectado 13 Pampa Camarones M3 2019.jpg\n",
"\tPanel Desconectado 17 Pampa Camarones M3 2019.jpg\n",
"\tPanel Desconectado 3 Pampa Camarones M1 2019.jpg\n",
"\tPanel Desconectado 5 Pampa Camarones M1 2019.jpg\n",
"\tPanel Desconectado 7 Pampa Camarones M1 2019.jpg\n",
"\tPanel Desconectado 2 El Aguila M2 2019.jpg\n",
"\tPanel Desconectado 8 Pampa Camarones M1 2019.jpg\n",
"Found directory: ./dataset_panel/8- Tracker dañado\n",
"\tTracker dañado 8 Maria Elena M3 2018.jpg\n",
"\tTracker dañado 13 Maria Elena M3 2018.jpg\n",
"\tTracker dañado 20 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 9 Maria Elena M3 2018.jpg\n",
"\tTracker dañado 11 Maria Elena M3 2018.jpg\n",
"\tTracker dañado 2 Pampa Camarones M1 2019.jpg\n",
"\tTracker dañado 19 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 10 Maria Elena M3 2018.jpg\n",
"\tTracker dañado 4 Pampa Camarones M1 2019.jpg\n",
"\tTracker dañado 15 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 17 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 7 Pampa Camarones M1 2019.jpg\n",
"\tTracker dañado 5 Pampa Camarones M1 2019.jpg\n",
"\tTracker dañado 6 Pampa Camarones M1 2019.jpg\n",
"\tTracker dañado 18 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 13 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 16 Maria Elena M13 2018.jpg\n",
"\tTracker dañado 12 Maria Elena M3 2018.jpg\n",
"\tTracker dañado 1 Pampa Camarones M1 2019.jpg\n",
"\tTracker dañado 3 Pampa Camarones M1 2019.jpg\n",
"Found directory: ./dataset_panel/10- Reflejos\n",
"\tReflejo 3 Citrino.jpg\n",
"\tReflejo 10 Pampa Camarones M1 2019.jpg\n",
"\tReflejo 4 Citrino.jpg\n",
"\tReflejo 11 Pampa Camarones M1 2019.jpg\n",
"\tReflejo 23 Maria Elena M3 2018.jpg\n",
"\tReflejo 22 LLano de LLampos M2 2019.jpg\n",
"\tReflejo 18 LLano de LLampos M2 2019.jpg\n",
"\tReflejo 5 El Aguila M1 2019.jpg\n",
"\tReflejo 21 LLano de LLampos M2 2019.jpg\n",
"\tReflejo 7 Pampa Camarones M1 2019.jpg\n",
"\tReflejo 2 Citrino.jpg\n",
"\tReflejo 16 Pampa Camarones M2 2019.jpg\n",
"\tReflejo 6 Pampa Camarones M1 2019.jpg\n",
"\tReflejo 8 Pampa Camarones M1 2019.jpg\n",
"\tReflejo 19 LLano de LLampos M2 2019.jpg\n",
"\tReflejo 15 Pampa Camarones M1 2019.jpg\n",
"\tReflejo 9 Pampa Camarones M1 2019.jpg\n",
"\tReflejo 13 Pampa Camarones M1 2019.jpg\n",
"\tReflejo 17 Pampa Camarones M2 2019.jpg\n",
"\tReflejo 1 Citrino.jpg\n",
"\tReflejo 14 Pampa Camarones M1 2019.jpg\n",
"\tReflejo 20 LLano de LLampos M2 2019.jpg\n",
"\tReflejo 12 Pampa Camarones M1 2019.jpg\n",
"Found directory: ./dataset_panel/0- Normal\n",
"\tNormal 30 Valle de La Luna M1 2019.jpg\n",
"\tNormal 16 Tiltil M2 2019.jpg\n",
"\tNormal 3 Citrino.jpg\n",
"\tNormal 20 Casuto M1 2019.jpg\n",
"\tNormal 12 Tiltil M1 2019.jpg\n",
"\tNormal 2 Citrino.jpg\n",
"\tNormal 15 Tiltil M1 2019.jpg\n",
"\tNormal 11 Pampa Camarones M3 2019.jpg\n",
"\tNormal 1 Citrino.jpg\n",
"\tNormal 17 Casuto M1 2019.jpg\n",
"\tNormal 21 Casuto M1 2019.jpg\n",
"\tNormal 5 El Aguila M1 2019.jpg\n",
"\tNormal 14 Tiltil M1 2019.jpg\n",
"\tNormal 6 El Aguila M1 2019.jpg\n",
"\tNormal 25 Llano de Llampos M1 2019.jpg\n",
"\tNormal 10 Pampa Camarones M1 2019.jpg\n",
"\tNormal 9 El Aguila M1 2019.jpg\n",
"\tNormal 27 Llano de Llampos M1 2019.jpg\n",
"\tNormal 19 Casuto M1 2019.jpg\n",
"\tNormal 18 Casuto M1 2019.jpg\n",
"\tNormal 8 El Aguila M1 2019.jpg\n",
"\tNormal 28 Cerro Dominado M1 2019.jpg\n",
"\tNormal 22 Casuto M1 2019.jpg\n",
"\tNormal 4 Citrino.jpg\n",
"\tNormal 24 Llano de Llampos M1 2019.jpg\n",
"\tNormal 23 Casuto M1 2019.jpg\n",
"\tNormal 26 Llano de Llampos M1 2019.jpg\n",
"\tNormal 13 Tiltil M1 2019.jpg\n",
"\tNormal 7 El Aguila M1 2019.jpg\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Found directory: ./model\n",
"\tmodel.json\n",
"\ttop_model_weights.h5\n",
"\tmodel_weights.h5\n",
"Found directory: ./preview\n"
]
}
],
"source": [
"\n",
"# Set the directory you want to start from\n",
"rootDir = '.'\n",
"for dirName, subdirList, fileList in os.walk(rootDir):\n",
" print('Found directory: %s' % dirName)\n",
" for fname in fileList:\n",
" print('\\t%s' % fname)\n",
" \n",
"\n",
"# load our serialized face detector from disk\n",
"# fix seed for reproducible results (only works on CPU, not GPU)\n",
"seed = 1\n",
"np.random.seed(seed=seed)\n",
"tf.random.set_seed(seed=seed)\n",
"\n",
"# hyper parameters for model\n",
"nb_classes = 5 # number of classes\n",
"based_model_last_block_layer_number = 126 # value is based on based model selected.\n",
"img_width, img_height = 224, 224 # change based on the shape/structure of your images\n",
"batch_size = 2 # try 4, 8, 16, 32, 64, 128, 256 dependent on CPU/GPU memory capacity (powers of 2 values).\n",
"nb_epoch = 100 # number of iteration the algorithm gets trained.\n",
"learn_rate = 1e-4 # sgd learning rate\n",
"momentum = .9 # sgd momentum to avoid local minimum\n",
"transformation_ratio = .0001 # how aggressive will be the data augmentation/transformation\n",
"patience = 10\n",
"\n",
"train_data_dir = './dataset_prueba_1/' # Inside, each class should have it's own folder\n",
"#validation_data_dir = './dataset/' # each class should have it's own folder\n",
"model_path = './model/'"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Model: \"model\"\n",
"__________________________________________________________________________________________________\n",
"Layer (type) Output Shape Param # Connected to \n",
"==================================================================================================\n",
"input_1 (InputLayer) [(None, 224, 224, 3) 0 \n",
"__________________________________________________________________________________________________\n",
"block1_conv1 (Conv2D) (None, 111, 111, 32) 864 input_1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block1_conv1_bn (BatchNormaliza (None, 111, 111, 32) 128 block1_conv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block1_conv1_act (Activation) (None, 111, 111, 32) 0 block1_conv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block1_conv2 (Conv2D) (None, 109, 109, 64) 18432 block1_conv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block1_conv2_bn (BatchNormaliza (None, 109, 109, 64) 256 block1_conv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block1_conv2_act (Activation) (None, 109, 109, 64) 0 block1_conv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block2_sepconv1 (SeparableConv2 (None, 109, 109, 128 8768 block1_conv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block2_sepconv1_bn (BatchNormal (None, 109, 109, 128 512 block2_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block2_sepconv2_act (Activation (None, 109, 109, 128 0 block2_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block2_sepconv2 (SeparableConv2 (None, 109, 109, 128 17536 block2_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block2_sepconv2_bn (BatchNormal (None, 109, 109, 128 512 block2_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"conv2d (Conv2D) (None, 55, 55, 128) 8192 block1_conv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block2_pool (MaxPooling2D) (None, 55, 55, 128) 0 block2_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"batch_normalization (BatchNorma (None, 55, 55, 128) 512 conv2d[0][0] \n",
"__________________________________________________________________________________________________\n",
"add (Add) (None, 55, 55, 128) 0 block2_pool[0][0] \n",
" batch_normalization[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_sepconv1_act (Activation (None, 55, 55, 128) 0 add[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_sepconv1 (SeparableConv2 (None, 55, 55, 256) 33920 block3_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_sepconv1_bn (BatchNormal (None, 55, 55, 256) 1024 block3_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_sepconv2_act (Activation (None, 55, 55, 256) 0 block3_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_sepconv2 (SeparableConv2 (None, 55, 55, 256) 67840 block3_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_sepconv2_bn (BatchNormal (None, 55, 55, 256) 1024 block3_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"conv2d_1 (Conv2D) (None, 28, 28, 256) 32768 add[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_pool (MaxPooling2D) (None, 28, 28, 256) 0 block3_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"batch_normalization_1 (BatchNor (None, 28, 28, 256) 1024 conv2d_1[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_1 (Add) (None, 28, 28, 256) 0 block3_pool[0][0] \n",
" batch_normalization_1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_sepconv1_act (Activation (None, 28, 28, 256) 0 add_1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_sepconv1 (SeparableConv2 (None, 28, 28, 728) 188672 block4_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_sepconv1_bn (BatchNormal (None, 28, 28, 728) 2912 block4_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_sepconv2_act (Activation (None, 28, 28, 728) 0 block4_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_sepconv2 (SeparableConv2 (None, 28, 28, 728) 536536 block4_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_sepconv2_bn (BatchNormal (None, 28, 28, 728) 2912 block4_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"conv2d_2 (Conv2D) (None, 14, 14, 728) 186368 add_1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_pool (MaxPooling2D) (None, 14, 14, 728) 0 block4_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"batch_normalization_2 (BatchNor (None, 14, 14, 728) 2912 conv2d_2[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_2 (Add) (None, 14, 14, 728) 0 block4_pool[0][0] \n",
" batch_normalization_2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv1_act (Activation (None, 14, 14, 728) 0 add_2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv1 (SeparableConv2 (None, 14, 14, 728) 536536 block5_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv1_bn (BatchNormal (None, 14, 14, 728) 2912 block5_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv2_act (Activation (None, 14, 14, 728) 0 block5_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv2 (SeparableConv2 (None, 14, 14, 728) 536536 block5_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv2_bn (BatchNormal (None, 14, 14, 728) 2912 block5_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv3_act (Activation (None, 14, 14, 728) 0 block5_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv3 (SeparableConv2 (None, 14, 14, 728) 536536 block5_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv3_bn (BatchNormal (None, 14, 14, 728) 2912 block5_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_3 (Add) (None, 14, 14, 728) 0 block5_sepconv3_bn[0][0] \n",
" add_2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv1_act (Activation (None, 14, 14, 728) 0 add_3[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv1 (SeparableConv2 (None, 14, 14, 728) 536536 block6_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv1_bn (BatchNormal (None, 14, 14, 728) 2912 block6_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv2_act (Activation (None, 14, 14, 728) 0 block6_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv2 (SeparableConv2 (None, 14, 14, 728) 536536 block6_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv2_bn (BatchNormal (None, 14, 14, 728) 2912 block6_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv3_act (Activation (None, 14, 14, 728) 0 block6_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv3 (SeparableConv2 (None, 14, 14, 728) 536536 block6_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv3_bn (BatchNormal (None, 14, 14, 728) 2912 block6_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_4 (Add) (None, 14, 14, 728) 0 block6_sepconv3_bn[0][0] \n",
" add_3[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv1_act (Activation (None, 14, 14, 728) 0 add_4[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv1 (SeparableConv2 (None, 14, 14, 728) 536536 block7_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv1_bn (BatchNormal (None, 14, 14, 728) 2912 block7_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv2_act (Activation (None, 14, 14, 728) 0 block7_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv2 (SeparableConv2 (None, 14, 14, 728) 536536 block7_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv2_bn (BatchNormal (None, 14, 14, 728) 2912 block7_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv3_act (Activation (None, 14, 14, 728) 0 block7_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv3 (SeparableConv2 (None, 14, 14, 728) 536536 block7_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv3_bn (BatchNormal (None, 14, 14, 728) 2912 block7_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_5 (Add) (None, 14, 14, 728) 0 block7_sepconv3_bn[0][0] \n",
" add_4[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv1_act (Activation (None, 14, 14, 728) 0 add_5[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv1 (SeparableConv2 (None, 14, 14, 728) 536536 block8_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv1_bn (BatchNormal (None, 14, 14, 728) 2912 block8_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv2_act (Activation (None, 14, 14, 728) 0 block8_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv2 (SeparableConv2 (None, 14, 14, 728) 536536 block8_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv2_bn (BatchNormal (None, 14, 14, 728) 2912 block8_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv3_act (Activation (None, 14, 14, 728) 0 block8_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv3 (SeparableConv2 (None, 14, 14, 728) 536536 block8_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv3_bn (BatchNormal (None, 14, 14, 728) 2912 block8_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_6 (Add) (None, 14, 14, 728) 0 block8_sepconv3_bn[0][0] \n",
" add_5[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv1_act (Activation (None, 14, 14, 728) 0 add_6[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv1 (SeparableConv2 (None, 14, 14, 728) 536536 block9_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv1_bn (BatchNormal (None, 14, 14, 728) 2912 block9_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv2_act (Activation (None, 14, 14, 728) 0 block9_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv2 (SeparableConv2 (None, 14, 14, 728) 536536 block9_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv2_bn (BatchNormal (None, 14, 14, 728) 2912 block9_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv3_act (Activation (None, 14, 14, 728) 0 block9_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv3 (SeparableConv2 (None, 14, 14, 728) 536536 block9_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv3_bn (BatchNormal (None, 14, 14, 728) 2912 block9_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_7 (Add) (None, 14, 14, 728) 0 block9_sepconv3_bn[0][0] \n",
" add_6[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv1_act (Activatio (None, 14, 14, 728) 0 add_7[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv1 (SeparableConv (None, 14, 14, 728) 536536 block10_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv1_bn (BatchNorma (None, 14, 14, 728) 2912 block10_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv2_act (Activatio (None, 14, 14, 728) 0 block10_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv2 (SeparableConv (None, 14, 14, 728) 536536 block10_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv2_bn (BatchNorma (None, 14, 14, 728) 2912 block10_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv3_act (Activatio (None, 14, 14, 728) 0 block10_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv3 (SeparableConv (None, 14, 14, 728) 536536 block10_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv3_bn (BatchNorma (None, 14, 14, 728) 2912 block10_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_8 (Add) (None, 14, 14, 728) 0 block10_sepconv3_bn[0][0] \n",
" add_7[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv1_act (Activatio (None, 14, 14, 728) 0 add_8[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv1 (SeparableConv (None, 14, 14, 728) 536536 block11_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv1_bn (BatchNorma (None, 14, 14, 728) 2912 block11_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv2_act (Activatio (None, 14, 14, 728) 0 block11_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv2 (SeparableConv (None, 14, 14, 728) 536536 block11_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv2_bn (BatchNorma (None, 14, 14, 728) 2912 block11_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv3_act (Activatio (None, 14, 14, 728) 0 block11_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv3 (SeparableConv (None, 14, 14, 728) 536536 block11_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv3_bn (BatchNorma (None, 14, 14, 728) 2912 block11_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_9 (Add) (None, 14, 14, 728) 0 block11_sepconv3_bn[0][0] \n",
" add_8[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv1_act (Activatio (None, 14, 14, 728) 0 add_9[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv1 (SeparableConv (None, 14, 14, 728) 536536 block12_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv1_bn (BatchNorma (None, 14, 14, 728) 2912 block12_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv2_act (Activatio (None, 14, 14, 728) 0 block12_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv2 (SeparableConv (None, 14, 14, 728) 536536 block12_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv2_bn (BatchNorma (None, 14, 14, 728) 2912 block12_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv3_act (Activatio (None, 14, 14, 728) 0 block12_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv3 (SeparableConv (None, 14, 14, 728) 536536 block12_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv3_bn (BatchNorma (None, 14, 14, 728) 2912 block12_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_10 (Add) (None, 14, 14, 728) 0 block12_sepconv3_bn[0][0] \n",
" add_9[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_sepconv1_act (Activatio (None, 14, 14, 728) 0 add_10[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_sepconv1 (SeparableConv (None, 14, 14, 728) 536536 block13_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_sepconv1_bn (BatchNorma (None, 14, 14, 728) 2912 block13_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_sepconv2_act (Activatio (None, 14, 14, 728) 0 block13_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_sepconv2 (SeparableConv (None, 14, 14, 1024) 752024 block13_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_sepconv2_bn (BatchNorma (None, 14, 14, 1024) 4096 block13_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"conv2d_3 (Conv2D) (None, 7, 7, 1024) 745472 add_10[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_pool (MaxPooling2D) (None, 7, 7, 1024) 0 block13_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"batch_normalization_3 (BatchNor (None, 7, 7, 1024) 4096 conv2d_3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_11 (Add) (None, 7, 7, 1024) 0 block13_pool[0][0] \n",
" batch_normalization_3[0][0] \n",
"__________________________________________________________________________________________________\n",
"block14_sepconv1 (SeparableConv (None, 7, 7, 1536) 1582080 add_11[0][0] \n",
"__________________________________________________________________________________________________\n",
"block14_sepconv1_bn (BatchNorma (None, 7, 7, 1536) 6144 block14_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block14_sepconv1_act (Activatio (None, 7, 7, 1536) 0 block14_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block14_sepconv2 (SeparableConv (None, 7, 7, 2048) 3159552 block14_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block14_sepconv2_bn (BatchNorma (None, 7, 7, 2048) 8192 block14_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block14_sepconv2_act (Activatio (None, 7, 7, 2048) 0 block14_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"global_average_pooling2d (Globa (None, 2048) 0 block14_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"dense (Dense) (None, 5) 10245 global_average_pooling2d[0][0] \n",
"==================================================================================================\n",
"Total params: 20,871,725\n",
"Trainable params: 20,817,197\n",
"Non-trainable params: 54,528\n",
"__________________________________________________________________________________________________\n",
"None\n",
"Found 146 images belonging to 7 classes.\n",
"Found 34 images belonging to 7 classes.\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"WARNING:tensorflow:sample_weight modes were coerced from\n",
" ...\n",
" to \n",
" ['...']\n",
"WARNING:tensorflow:sample_weight modes were coerced from\n",
" ...\n",
" to \n",
" ['...']\n",
"Train for 58 steps, validate for 13 steps\n",
"Epoch 1/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.7914 - accuracy: 0.0614\n",
"Epoch 00001: val_loss improved from inf to 16.76773, saving model to /home/dlsaavedra/Desktop/Rentadrone.cl-ai-test&SomeCode/model-definition/GPS_Panel/Classifier/model/top_model_weights.h5\n",
"58/58 [==============================] - 50s 862ms/step - loss: 15.5191 - accuracy: 0.0603 - val_loss: 16.7677 - val_accuracy: 0.0000e+00\n",
"Epoch 2/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.5472 - accuracy: 0.0088\n",
"Epoch 00002: val_loss did not improve from 16.76773\n",
"58/58 [==============================] - 49s 837ms/step - loss: 15.7657 - accuracy: 0.0086 - val_loss: 22.9064 - val_accuracy: 0.0000e+00\n",
"Epoch 3/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.3652 - accuracy: 0.0175\n",
"Epoch 00003: val_loss did not improve from 16.76773\n",
"58/58 [==============================] - 50s 871ms/step - loss: 15.2392 - accuracy: 0.0172 - val_loss: 157.1759 - val_accuracy: 0.1154\n",
"Epoch 4/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.9721 - accuracy: 0.0439\n",
"Epoch 00004: val_loss did not improve from 16.76773\n",
"58/58 [==============================] - 52s 895ms/step - loss: 15.7661 - accuracy: 0.0431 - val_loss: 1889.7077 - val_accuracy: 0.0000e+00\n",
"Epoch 5/20\n",
"57/58 [============================>.] - ETA: 1s - loss: 16.8935 - accuracy: 0.0175\n",
"Epoch 00005: val_loss did not improve from 16.76773\n",
"58/58 [==============================] - 73s 1s/step - loss: 16.7411 - accuracy: 0.0172 - val_loss: 139.8746 - val_accuracy: 0.0000e+00\n",
"Epoch 6/20\n",
"57/58 [============================>.] - ETA: 1s - loss: 14.6952 - accuracy: 0.0088\n",
"Epoch 00006: val_loss did not improve from 16.76773\n",
"58/58 [==============================] - 76s 1s/step - loss: 14.5113 - accuracy: 0.0086 - val_loss: 60.4487 - val_accuracy: 0.0000e+00\n",
"Epoch 7/20\n",
"57/58 [============================>.] - ETA: 1s - loss: 15.6087 - accuracy: 0.0000e+00\n",
"Epoch 00007: val_loss did not improve from 16.76773\n",
"58/58 [==============================] - 74s 1s/step - loss: 15.5478 - accuracy: 0.0000e+00 - val_loss: 16.9469 - val_accuracy: 0.1538\n",
"Epoch 8/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 14.4803 - accuracy: 0.0088\n",
"Epoch 00008: val_loss did not improve from 16.76773\n",
"58/58 [==============================] - 57s 978ms/step - loss: 14.5081 - accuracy: 0.0086 - val_loss: 22.4798 - val_accuracy: 0.0769\n",
"Epoch 9/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.5354 - accuracy: 0.0088\n",
"Epoch 00009: val_loss did not improve from 16.76773\n",
"58/58 [==============================] - 55s 955ms/step - loss: 15.6145 - accuracy: 0.0086 - val_loss: 17.0278 - val_accuracy: 0.0000e+00\n",
"Epoch 10/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.6774 - accuracy: 0.0439\n",
"Epoch 00010: val_loss improved from 16.76773 to 16.71888, saving model to /home/dlsaavedra/Desktop/Rentadrone.cl-ai-test&SomeCode/model-definition/GPS_Panel/Classifier/model/top_model_weights.h5\n",
"58/58 [==============================] - 57s 977ms/step - loss: 15.5459 - accuracy: 0.0431 - val_loss: 16.7189 - val_accuracy: 0.8846\n",
"Epoch 11/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.9579 - accuracy: 0.0702\n",
"Epoch 00011: val_loss improved from 16.71888 to 16.71781, saving model to /home/dlsaavedra/Desktop/Rentadrone.cl-ai-test&SomeCode/model-definition/GPS_Panel/Classifier/model/top_model_weights.h5\n",
"58/58 [==============================] - 53s 914ms/step - loss: 16.0992 - accuracy: 0.0690 - val_loss: 16.7178 - val_accuracy: 0.0000e+00\n",
"Epoch 12/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 16.5248 - accuracy: 0.1228\n",
"Epoch 00012: val_loss did not improve from 16.71781\n",
"58/58 [==============================] - 51s 871ms/step - loss: 16.3787 - accuracy: 0.1207 - val_loss: 16.7196 - val_accuracy: 0.0000e+00\n",
"Epoch 13/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.2509 - accuracy: 0.0439\n",
"Epoch 00013: val_loss did not improve from 16.71781\n",
"58/58 [==============================] - 51s 885ms/step - loss: 15.3349 - accuracy: 0.0431 - val_loss: 16.7209 - val_accuracy: 0.0000e+00\n",
"Epoch 14/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.8867 - accuracy: 0.0351\n",
"Epoch 00014: val_loss did not improve from 16.71781\n",
"58/58 [==============================] - 59s 1s/step - loss: 15.7515 - accuracy: 0.0345 - val_loss: 17.0744 - val_accuracy: 0.0000e+00\n",
"Epoch 15/20\n",
"57/58 [============================>.] - ETA: 1s - loss: 15.5322 - accuracy: 0.0088 \n",
"Epoch 00015: val_loss did not improve from 16.71781\n",
"58/58 [==============================] - 64s 1s/step - loss: 15.4726 - accuracy: 0.0086 - val_loss: 18.1466 - val_accuracy: 0.0000e+00\n",
"Epoch 16/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.5316 - accuracy: 0.0000e+00\n",
"Epoch 00016: val_loss did not improve from 16.71781\n",
"58/58 [==============================] - 58s 993ms/step - loss: 15.7495 - accuracy: 0.0000e+00 - val_loss: 17.3060 - val_accuracy: 0.0000e+00\n",
"Epoch 17/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.5314 - accuracy: 0.0000e+00\n",
"Epoch 00017: val_loss did not improve from 16.71781\n",
"58/58 [==============================] - 51s 881ms/step - loss: 15.6105 - accuracy: 0.0000e+00 - val_loss: 18.0962 - val_accuracy: 0.0000e+00\n",
"Epoch 18/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.3194 - accuracy: 0.0000e+00\n",
"Epoch 00018: val_loss did not improve from 16.71781\n",
"58/58 [==============================] - 54s 935ms/step - loss: 15.2634 - accuracy: 0.0000e+00 - val_loss: 22.3874 - val_accuracy: 0.0000e+00\n",
"Epoch 19/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 15.8838 - accuracy: 0.0175\n",
"Epoch 00019: val_loss did not improve from 16.71781\n",
"58/58 [==============================] - 54s 932ms/step - loss: 16.0262 - accuracy: 0.0259 - val_loss: 20.3104 - val_accuracy: 0.0000e+00\n",
"Epoch 20/20\n",
"57/58 [============================>.] - ETA: 0s - loss: 16.5897 - accuracy: 0.0175\n",
"Epoch 00020: val_loss did not improve from 16.71781\n",
"58/58 [==============================] - 55s 951ms/step - loss: 16.5119 - accuracy: 0.0172 - val_loss: 16.8419 - val_accuracy: 0.0769\n"
]
}
],
"source": [
"\n",
"\n",
"base_model = tf.keras.applications.Xception(input_shape=(img_width, img_height, 3), weights='imagenet', include_top=False)\n",
"#base_model = tf.keras.applications.MobileNetV2(input_shape=(img_width, img_height, 3), weights='imagenet', include_top=False)\n",
"#base_model = tf.keras.applications.NASNetMobile(input_shape=(img_width, img_height, 3), weights='imagenet', include_top=False)\n",
"\n",
"\n",
"# Top Model Block\n",
"x = base_model.output\n",
"x = GlobalAveragePooling2D()(x)\n",
"predictions = Dense(nb_classes, activation='softmax')(x)\n",
"\n",
"# add your top layer block to your base model\n",
"model = tf.keras.Model(base_model.input, predictions)\n",
"\n",
"\n",
"# # let's visualize layer names and layer indices to see how many layers/blocks to re-train\n",
"# # uncomment when choosing based_model_last_block_layer\n",
"# for i, layer in enumerate(model.layers):\n",
"# print(i, layer.name)\n",
"\n",
"# first: train only the top layers (which were randomly initialized)\n",
"# i.e. freeze all layers of the based model that is already pre-trained.\n",
"for layer in base_model.layers:\n",
" layer.trainable = True\n",
"\n",
"print(model.summary())\n",
"# Read Data and Augment it: Make sure to select augmentations that are appropriate to your images.\n",
"# To save augmentations un-comment save lines and add to your flow parameters.\n",
"train_datagen = ImageDataGenerator(rescale=1. / 255,\n",
" rotation_range=transformation_ratio,\n",
" shear_range=transformation_ratio,\n",
" zoom_range=transformation_ratio,\n",
" cval=transformation_ratio,\n",
" horizontal_flip=True,\n",
" vertical_flip=True,\n",
" validation_split=0.2)\n",
"\n",
"\n",
"\n",
"train_generator = train_datagen.flow_from_directory(train_data_dir,\n",
" target_size=(img_height, img_width),\n",
" batch_size=batch_size,\n",
" class_mode='binary',\n",
" subset='training') # set as training data\n",
"\n",
"validation_generator = train_datagen.flow_from_directory(train_data_dir, # same directory as training data\n",
" target_size=(img_height, img_width),\n",
" batch_size=batch_size,\n",
" class_mode='binary',\n",
" subset='validation') # set as validation data\n",
"\n",
"model.compile(optimizer='adam',\n",
" loss='categorical_crossentropy', # categorical_crossentropy if multi-class classifier\n",
" metrics=['accuracy'])\n",
"\n",
"# save weights of best training epoch: monitor either val_loss or val_acc\n",
"\n",
"top_weights_path = os.path.join(os.path.abspath(model_path), 'top_model_weights.h5')\n",
"callbacks_list = [\n",
" ModelCheckpoint(top_weights_path, monitor='val_loss', verbose=1, save_best_only=True),\n",
" EarlyStopping(monitor='val_loss', patience= patience, verbose=0)\n",
"]\n",
"\n",
"# Train Simple CNN\n",
"hist = model.fit(train_generator,\n",
" steps_per_epoch= int(train_generator.samples/batch_size*.8),\n",
" epochs=int (nb_epoch / 5),\n",
" validation_data=validation_generator,\n",
" validation_steps = int(validation_generator.samples /batch_size*.8),\n",
" validation_freq=1,\n",
" callbacks=callbacks_list)\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Starting to Fine Tune Model\n",
"\n",
"Model: \"model\"\n",
"__________________________________________________________________________________________________\n",
"Layer (type) Output Shape Param # Connected to \n",
"==================================================================================================\n",
"input_1 (InputLayer) [(None, 224, 224, 3) 0 \n",
"__________________________________________________________________________________________________\n",
"block1_conv1 (Conv2D) (None, 111, 111, 32) 864 input_1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block1_conv1_bn (BatchNormaliza (None, 111, 111, 32) 128 block1_conv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block1_conv1_act (Activation) (None, 111, 111, 32) 0 block1_conv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block1_conv2 (Conv2D) (None, 109, 109, 64) 18432 block1_conv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block1_conv2_bn (BatchNormaliza (None, 109, 109, 64) 256 block1_conv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block1_conv2_act (Activation) (None, 109, 109, 64) 0 block1_conv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block2_sepconv1 (SeparableConv2 (None, 109, 109, 128 8768 block1_conv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block2_sepconv1_bn (BatchNormal (None, 109, 109, 128 512 block2_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block2_sepconv2_act (Activation (None, 109, 109, 128 0 block2_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block2_sepconv2 (SeparableConv2 (None, 109, 109, 128 17536 block2_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block2_sepconv2_bn (BatchNormal (None, 109, 109, 128 512 block2_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"conv2d (Conv2D) (None, 55, 55, 128) 8192 block1_conv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block2_pool (MaxPooling2D) (None, 55, 55, 128) 0 block2_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"batch_normalization (BatchNorma (None, 55, 55, 128) 512 conv2d[0][0] \n",
"__________________________________________________________________________________________________\n",
"add (Add) (None, 55, 55, 128) 0 block2_pool[0][0] \n",
" batch_normalization[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_sepconv1_act (Activation (None, 55, 55, 128) 0 add[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_sepconv1 (SeparableConv2 (None, 55, 55, 256) 33920 block3_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_sepconv1_bn (BatchNormal (None, 55, 55, 256) 1024 block3_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_sepconv2_act (Activation (None, 55, 55, 256) 0 block3_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_sepconv2 (SeparableConv2 (None, 55, 55, 256) 67840 block3_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_sepconv2_bn (BatchNormal (None, 55, 55, 256) 1024 block3_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"conv2d_1 (Conv2D) (None, 28, 28, 256) 32768 add[0][0] \n",
"__________________________________________________________________________________________________\n",
"block3_pool (MaxPooling2D) (None, 28, 28, 256) 0 block3_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"batch_normalization_1 (BatchNor (None, 28, 28, 256) 1024 conv2d_1[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_1 (Add) (None, 28, 28, 256) 0 block3_pool[0][0] \n",
" batch_normalization_1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_sepconv1_act (Activation (None, 28, 28, 256) 0 add_1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_sepconv1 (SeparableConv2 (None, 28, 28, 728) 188672 block4_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_sepconv1_bn (BatchNormal (None, 28, 28, 728) 2912 block4_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_sepconv2_act (Activation (None, 28, 28, 728) 0 block4_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_sepconv2 (SeparableConv2 (None, 28, 28, 728) 536536 block4_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_sepconv2_bn (BatchNormal (None, 28, 28, 728) 2912 block4_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"conv2d_2 (Conv2D) (None, 14, 14, 728) 186368 add_1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block4_pool (MaxPooling2D) (None, 14, 14, 728) 0 block4_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"batch_normalization_2 (BatchNor (None, 14, 14, 728) 2912 conv2d_2[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_2 (Add) (None, 14, 14, 728) 0 block4_pool[0][0] \n",
" batch_normalization_2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv1_act (Activation (None, 14, 14, 728) 0 add_2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv1 (SeparableConv2 (None, 14, 14, 728) 536536 block5_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv1_bn (BatchNormal (None, 14, 14, 728) 2912 block5_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv2_act (Activation (None, 14, 14, 728) 0 block5_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv2 (SeparableConv2 (None, 14, 14, 728) 536536 block5_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv2_bn (BatchNormal (None, 14, 14, 728) 2912 block5_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv3_act (Activation (None, 14, 14, 728) 0 block5_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv3 (SeparableConv2 (None, 14, 14, 728) 536536 block5_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block5_sepconv3_bn (BatchNormal (None, 14, 14, 728) 2912 block5_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_3 (Add) (None, 14, 14, 728) 0 block5_sepconv3_bn[0][0] \n",
" add_2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv1_act (Activation (None, 14, 14, 728) 0 add_3[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv1 (SeparableConv2 (None, 14, 14, 728) 536536 block6_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv1_bn (BatchNormal (None, 14, 14, 728) 2912 block6_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv2_act (Activation (None, 14, 14, 728) 0 block6_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv2 (SeparableConv2 (None, 14, 14, 728) 536536 block6_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv2_bn (BatchNormal (None, 14, 14, 728) 2912 block6_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv3_act (Activation (None, 14, 14, 728) 0 block6_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv3 (SeparableConv2 (None, 14, 14, 728) 536536 block6_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block6_sepconv3_bn (BatchNormal (None, 14, 14, 728) 2912 block6_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_4 (Add) (None, 14, 14, 728) 0 block6_sepconv3_bn[0][0] \n",
" add_3[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv1_act (Activation (None, 14, 14, 728) 0 add_4[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv1 (SeparableConv2 (None, 14, 14, 728) 536536 block7_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv1_bn (BatchNormal (None, 14, 14, 728) 2912 block7_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv2_act (Activation (None, 14, 14, 728) 0 block7_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv2 (SeparableConv2 (None, 14, 14, 728) 536536 block7_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv2_bn (BatchNormal (None, 14, 14, 728) 2912 block7_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv3_act (Activation (None, 14, 14, 728) 0 block7_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv3 (SeparableConv2 (None, 14, 14, 728) 536536 block7_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block7_sepconv3_bn (BatchNormal (None, 14, 14, 728) 2912 block7_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_5 (Add) (None, 14, 14, 728) 0 block7_sepconv3_bn[0][0] \n",
" add_4[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv1_act (Activation (None, 14, 14, 728) 0 add_5[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv1 (SeparableConv2 (None, 14, 14, 728) 536536 block8_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv1_bn (BatchNormal (None, 14, 14, 728) 2912 block8_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv2_act (Activation (None, 14, 14, 728) 0 block8_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv2 (SeparableConv2 (None, 14, 14, 728) 536536 block8_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv2_bn (BatchNormal (None, 14, 14, 728) 2912 block8_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv3_act (Activation (None, 14, 14, 728) 0 block8_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv3 (SeparableConv2 (None, 14, 14, 728) 536536 block8_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block8_sepconv3_bn (BatchNormal (None, 14, 14, 728) 2912 block8_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_6 (Add) (None, 14, 14, 728) 0 block8_sepconv3_bn[0][0] \n",
" add_5[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv1_act (Activation (None, 14, 14, 728) 0 add_6[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv1 (SeparableConv2 (None, 14, 14, 728) 536536 block9_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv1_bn (BatchNormal (None, 14, 14, 728) 2912 block9_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv2_act (Activation (None, 14, 14, 728) 0 block9_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv2 (SeparableConv2 (None, 14, 14, 728) 536536 block9_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv2_bn (BatchNormal (None, 14, 14, 728) 2912 block9_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv3_act (Activation (None, 14, 14, 728) 0 block9_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv3 (SeparableConv2 (None, 14, 14, 728) 536536 block9_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block9_sepconv3_bn (BatchNormal (None, 14, 14, 728) 2912 block9_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_7 (Add) (None, 14, 14, 728) 0 block9_sepconv3_bn[0][0] \n",
" add_6[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv1_act (Activatio (None, 14, 14, 728) 0 add_7[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv1 (SeparableConv (None, 14, 14, 728) 536536 block10_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv1_bn (BatchNorma (None, 14, 14, 728) 2912 block10_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv2_act (Activatio (None, 14, 14, 728) 0 block10_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv2 (SeparableConv (None, 14, 14, 728) 536536 block10_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv2_bn (BatchNorma (None, 14, 14, 728) 2912 block10_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv3_act (Activatio (None, 14, 14, 728) 0 block10_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv3 (SeparableConv (None, 14, 14, 728) 536536 block10_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block10_sepconv3_bn (BatchNorma (None, 14, 14, 728) 2912 block10_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_8 (Add) (None, 14, 14, 728) 0 block10_sepconv3_bn[0][0] \n",
" add_7[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv1_act (Activatio (None, 14, 14, 728) 0 add_8[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv1 (SeparableConv (None, 14, 14, 728) 536536 block11_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv1_bn (BatchNorma (None, 14, 14, 728) 2912 block11_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv2_act (Activatio (None, 14, 14, 728) 0 block11_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv2 (SeparableConv (None, 14, 14, 728) 536536 block11_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv2_bn (BatchNorma (None, 14, 14, 728) 2912 block11_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv3_act (Activatio (None, 14, 14, 728) 0 block11_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv3 (SeparableConv (None, 14, 14, 728) 536536 block11_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block11_sepconv3_bn (BatchNorma (None, 14, 14, 728) 2912 block11_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_9 (Add) (None, 14, 14, 728) 0 block11_sepconv3_bn[0][0] \n",
" add_8[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv1_act (Activatio (None, 14, 14, 728) 0 add_9[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv1 (SeparableConv (None, 14, 14, 728) 536536 block12_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv1_bn (BatchNorma (None, 14, 14, 728) 2912 block12_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv2_act (Activatio (None, 14, 14, 728) 0 block12_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv2 (SeparableConv (None, 14, 14, 728) 536536 block12_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv2_bn (BatchNorma (None, 14, 14, 728) 2912 block12_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv3_act (Activatio (None, 14, 14, 728) 0 block12_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv3 (SeparableConv (None, 14, 14, 728) 536536 block12_sepconv3_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block12_sepconv3_bn (BatchNorma (None, 14, 14, 728) 2912 block12_sepconv3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_10 (Add) (None, 14, 14, 728) 0 block12_sepconv3_bn[0][0] \n",
" add_9[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_sepconv1_act (Activatio (None, 14, 14, 728) 0 add_10[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_sepconv1 (SeparableConv (None, 14, 14, 728) 536536 block13_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_sepconv1_bn (BatchNorma (None, 14, 14, 728) 2912 block13_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_sepconv2_act (Activatio (None, 14, 14, 728) 0 block13_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_sepconv2 (SeparableConv (None, 14, 14, 1024) 752024 block13_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_sepconv2_bn (BatchNorma (None, 14, 14, 1024) 4096 block13_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"conv2d_3 (Conv2D) (None, 7, 7, 1024) 745472 add_10[0][0] \n",
"__________________________________________________________________________________________________\n",
"block13_pool (MaxPooling2D) (None, 7, 7, 1024) 0 block13_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"batch_normalization_3 (BatchNor (None, 7, 7, 1024) 4096 conv2d_3[0][0] \n",
"__________________________________________________________________________________________________\n",
"add_11 (Add) (None, 7, 7, 1024) 0 block13_pool[0][0] \n",
" batch_normalization_3[0][0] \n",
"__________________________________________________________________________________________________\n",
"block14_sepconv1 (SeparableConv (None, 7, 7, 1536) 1582080 add_11[0][0] \n",
"__________________________________________________________________________________________________\n",
"block14_sepconv1_bn (BatchNorma (None, 7, 7, 1536) 6144 block14_sepconv1[0][0] \n",
"__________________________________________________________________________________________________\n",
"block14_sepconv1_act (Activatio (None, 7, 7, 1536) 0 block14_sepconv1_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"block14_sepconv2 (SeparableConv (None, 7, 7, 2048) 3159552 block14_sepconv1_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"block14_sepconv2_bn (BatchNorma (None, 7, 7, 2048) 8192 block14_sepconv2[0][0] \n",
"__________________________________________________________________________________________________\n",
"block14_sepconv2_act (Activatio (None, 7, 7, 2048) 0 block14_sepconv2_bn[0][0] \n",
"__________________________________________________________________________________________________\n",
"global_average_pooling2d (Globa (None, 2048) 0 block14_sepconv2_act[0][0] \n",
"__________________________________________________________________________________________________\n",
"dense (Dense) (None, 5) 10245 global_average_pooling2d[0][0] \n",
"==================================================================================================\n",
"Total params: 20,871,725\n",
"Trainable params: 20,817,197\n",
"Non-trainable params: 54,528\n",
"__________________________________________________________________________________________________\n",
"None\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"WARNING:tensorflow:sample_weight modes were coerced from\n",
" ...\n",
" to \n",
" ['...']\n",
"WARNING:tensorflow:sample_weight modes were coerced from\n",
" ...\n",
" to \n",
" ['...']\n",
"Train for 58.400000000000006 steps, validate for 13.600000000000001 steps\n",
"Epoch 1/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 16.7909 - accuracy: 0.1207\n",
"Epoch 00001: val_loss improved from inf to 17.16391, saving model to /home/dlsaavedra/Desktop/Rentadrone.cl-ai-test&SomeCode/model-definition/GPS_Panel/Classifier/model/model_weights.h5\n",
"59/58 [==============================] - 75s 1s/step - loss: 16.5745 - accuracy: 0.1186 - val_loss: 17.1639 - val_accuracy: 0.4286\n",
"Epoch 2/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 16.1648 - accuracy: 0.0948\n",
"Epoch 00002: val_loss did not improve from 17.16391\n",
"59/58 [==============================] - 56s 948ms/step - loss: 16.1636 - accuracy: 0.0932 - val_loss: 17.1654 - val_accuracy: 0.1429\n",
"Epoch 3/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 15.5401 - accuracy: 0.0690\n",
"Epoch 00003: val_loss did not improve from 17.16391\n",
"59/58 [==============================] - 57s 959ms/step - loss: 15.4813 - accuracy: 0.0678 - val_loss: 17.1791 - val_accuracy: 0.0714\n",
"Epoch 4/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 15.4705 - accuracy: 0.0690\n",
"Epoch 00004: val_loss did not improve from 17.16391\n",
"59/58 [==============================] - 56s 950ms/step - loss: 15.3447 - accuracy: 0.0678 - val_loss: 17.1779 - val_accuracy: 0.0000e+00\n",
"Epoch 5/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 16.3031 - accuracy: 0.0517\n",
"Epoch 00005: val_loss did not improve from 17.16391\n",
"59/58 [==============================] - 57s 960ms/step - loss: 16.7087 - accuracy: 0.0508 - val_loss: 17.2318 - val_accuracy: 0.0000e+00\n",
"Epoch 6/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 16.1641 - accuracy: 0.0776\n",
"Epoch 00006: val_loss did not improve from 17.16391\n",
"59/58 [==============================] - 55s 933ms/step - loss: 15.9583 - accuracy: 0.0847 - val_loss: 17.1775 - val_accuracy: 0.0000e+00\n",
"Epoch 7/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 15.4702 - accuracy: 0.0172\n",
"Epoch 00007: val_loss did not improve from 17.16391\n",
"59/58 [==============================] - 56s 947ms/step - loss: 15.2762 - accuracy: 0.0254 - val_loss: 17.1652 - val_accuracy: 0.0000e+00\n",
"Epoch 8/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 15.8864 - accuracy: 0.0086\n",
"Epoch 00008: val_loss improved from 17.16391 to 17.16194, saving model to /home/dlsaavedra/Desktop/Rentadrone.cl-ai-test&SomeCode/model-definition/GPS_Panel/Classifier/model/model_weights.h5\n",
"59/58 [==============================] - 71s 1s/step - loss: 15.6854 - accuracy: 0.0085 - val_loss: 17.1619 - val_accuracy: 0.1429\n",
"Epoch 9/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 15.8172 - accuracy: 0.0517\n",
"Epoch 00009: val_loss did not improve from 17.16194\n",
"59/58 [==============================] - 57s 973ms/step - loss: 15.6855 - accuracy: 0.0508 - val_loss: 17.8925 - val_accuracy: 0.1786\n",
"Epoch 10/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 15.3315 - accuracy: 0.0517\n",
"Epoch 00010: val_loss did not improve from 17.16194\n",
"59/58 [==============================] - 56s 957ms/step - loss: 15.2081 - accuracy: 0.0508 - val_loss: 17.3912 - val_accuracy: 0.4643\n",
"Epoch 11/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 15.2621 - accuracy: 0.0517\n",
"Epoch 00011: val_loss did not improve from 17.16194\n",
"59/58 [==============================] - 58s 978ms/step - loss: 15.1398 - accuracy: 0.0508 - val_loss: 17.1633 - val_accuracy: 0.1429\n",
"Epoch 12/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 15.5397 - accuracy: 0.0345\n",
"Epoch 00012: val_loss did not improve from 17.16194\n",
"59/58 [==============================] - 56s 953ms/step - loss: 15.6173 - accuracy: 0.0339 - val_loss: 18.1601 - val_accuracy: 0.1429\n",
"Epoch 13/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 15.4702 - accuracy: 0.0690\n",
"Epoch 00013: val_loss did not improve from 17.16194\n",
"59/58 [==============================] - 58s 986ms/step - loss: 15.4808 - accuracy: 0.0678 - val_loss: 17.4696 - val_accuracy: 0.0000e+00\n",
"Epoch 14/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 15.1233 - accuracy: 0.1034\n",
"Epoch 00014: val_loss did not improve from 17.16194\n",
"59/58 [==============================] - 55s 931ms/step - loss: 15.0034 - accuracy: 0.1017 - val_loss: 19.5240 - val_accuracy: 0.1429\n",
"Epoch 15/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 15.8864 - accuracy: 0.1293\n",
"Epoch 00015: val_loss did not improve from 17.16194\n",
"59/58 [==============================] - 58s 985ms/step - loss: 15.6854 - accuracy: 0.1271 - val_loss: 17.6684 - val_accuracy: 0.0357\n",
"Epoch 16/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 16.1640 - accuracy: 0.1293\n",
"Epoch 00016: val_loss did not improve from 17.16194\n",
"59/58 [==============================] - 57s 963ms/step - loss: 16.2992 - accuracy: 0.1271 - val_loss: 17.4060 - val_accuracy: 1.0000\n",
"Epoch 17/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 16.3026 - accuracy: 0.0517\n",
"Epoch 00017: val_loss did not improve from 17.16194\n",
"59/58 [==============================] - 57s 960ms/step - loss: 16.0945 - accuracy: 0.0508 - val_loss: 17.9671 - val_accuracy: 0.1071\n",
"Epoch 18/100\n",
"58/58 [============================>.] - ETA: 0s - loss: 16.0946 - accuracy: 0.0948\n",
"Epoch 00018: val_loss did not improve from 17.16194\n",
"59/58 [==============================] - 56s 955ms/step - loss: 16.0946 - accuracy: 0.0932 - val_loss: 17.1750 - val_accuracy: 0.0000e+00\n"
]
}
],
"source": [
"# verbose\n",
"print(\"\\nStarting to Fine Tune Model\\n\")\n",
"\n",
"# add the best weights from the train top model\n",
"# at this point we have the pre-train weights of the base model and the trained weight of the new/added top model\n",
"# we re-load model weights to ensure the best epoch is selected and not the last one.\n",
"model.load_weights(top_weights_path)\n",
"\n",
"print(model.summary())\n",
"# based_model_last_block_layer_number points to the layer in your model you want to train.\n",
"# For example if you want to train the last block of a 19 layer VGG16 model this should be 15\n",
"# If you want to train the last Two blocks of an Inception model it should be 172\n",
"# layers before this number will used the pre-trained weights, layers above and including this number\n",
"# will be re-trained based on the new data.\n",
"for layer in model.layers[:based_model_last_block_layer_number]:\n",
" layer.trainable = True\n",
"for layer in model.layers[based_model_last_block_layer_number:]:\n",
" layer.trainable = True\n",
"\n",
"# compile the model with a SGD/momentum optimizer\n",
"# and a very slow learning rate.\n",
"model.compile(optimizer='nadam',\n",
" loss='categorical_crossentropy',\n",
" metrics=['accuracy'])\n",
"\n",
"# save weights of best training epoch: monitor either val_loss or val_acc\n",
"final_weights_path = os.path.join(os.path.abspath(model_path), 'model_weights.h5')\n",
"callbacks_list = [\n",
" ModelCheckpoint(final_weights_path, monitor='val_loss', verbose=1, save_best_only=True),\n",
" EarlyStopping(monitor='val_loss', patience=patience, verbose=0)\n",
"]\n",
"\n",
"# fine-tune the model\n",
"hist = model.fit(train_generator,\n",
" steps_per_epoch=train_generator.samples/batch_size * .8,\n",
" epochs=nb_epoch,\n",
" validation_data=validation_generator,\n",
" validation_steps = validation_generator.samples/batch_size*.8,\n",
" callbacks=callbacks_list)\n",
"\n",
"# save model\n",
"model_json = model.to_json()\n",
"with open(os.path.join(os.path.abspath(model_path), 'model.json'), 'w') as json_file:\n",
" json_file.write(model_json)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"WARNING:tensorflow:From <ipython-input-5-94ce6e05c1eb>:10: Model.predict_generator (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.\n",
"Instructions for updating:\n",
"Please use Model.predict, which supports generators.\n",
"WARNING:tensorflow:Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least `steps_per_epoch * epochs` batches (in this case, 18 batches). You may need to use the repeat() function when building your dataset.\n",
"Confusion Matrix\n",
"[[0 4 1 0 0 0]\n",
" [0 7 5 1 0 0]\n",
" [0 2 1 1 1 0]\n",
" [0 1 3 0 0 0]\n",
" [0 2 0 0 2 0]\n",
" [0 2 0 1 0 0]]\n",
"Classification Report\n"
]
},
{
"ename": "ValueError",
"evalue": "Number of classes, 6, does not match size of target_names, 7. Try specifying the labels parameter",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-5-94ce6e05c1eb>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 14\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Classification Report'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0mtarget_names\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtrain_generator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclass_indices\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 16\u001b[0;31m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mclassification_report\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalidation_generator\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclasses\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_pred\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtarget_names\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtarget_names\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m~/anaconda3/envs/new/lib/python3.7/site-packages/sklearn/utils/validation.py\u001b[0m in \u001b[0;36minner_f\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m 71\u001b[0m FutureWarning)\n\u001b[1;32m 72\u001b[0m \u001b[0mkwargs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marg\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mzip\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 73\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 74\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0minner_f\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 75\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m~/anaconda3/envs/new/lib/python3.7/site-packages/sklearn/metrics/_classification.py\u001b[0m in \u001b[0;36mclassification_report\u001b[0;34m(y_true, y_pred, labels, target_names, sample_weight, digits, output_dict, zero_division)\u001b[0m\n\u001b[1;32m 1951\u001b[0m \u001b[0;34m\"Number of classes, {0}, does not match size of \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1952\u001b[0m \u001b[0;34m\"target_names, {1}. Try specifying the labels \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1953\u001b[0;31m \u001b[0;34m\"parameter\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlabels\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtarget_names\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1954\u001b[0m )\n\u001b[1;32m 1955\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtarget_names\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mValueError\u001b[0m: Number of classes, 6, does not match size of target_names, 7. Try specifying the labels parameter"
]
}
],
"source": [
"from sklearn.metrics import classification_report, confusion_matrix\n",
"\n",
"json_file = open(os.path.join(os.path.abspath(model_path), 'model.json'), 'r')\n",
"loaded_model_json = json_file.read()\n",
"json_file.close()\n",
"loaded_model = tf.keras.models.model_from_json(loaded_model_json)\n",
"\n",
"\n",
"#Confution Matrix and Classification Report\n",
"Y_pred = model.predict_generator(validation_generator, validation_generator.samples // batch_size+1)\n",
"y_pred = np.argmax(Y_pred, axis=1)\n",
"print('Confusion Matrix')\n",
"print(confusion_matrix(validation_generator.classes, y_pred))\n",
"print('Classification Report')\n",
"target_names = train_generator.class_indices.keys()\n",
"print(classification_report(validation_generator.classes, y_pred, target_names=target_names))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
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"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
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