109 lines
2.6 KiB
Plaintext
109 lines
2.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from keras.datasets import mnist\n",
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"from tensorflow.python.keras.backend import set_session\n",
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"from tensorflow.python.keras.models import load_model\n",
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"from tensorflow.keras.models import Model, load_model, Sequential\n",
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"from tensorflow.keras.layers import Conv2D, Dense, MaxPooling2D, Softmax, Activation, BatchNormalization, Flatten, Dropout, DepthwiseConv2D\n",
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"from tensorflow.keras.layers import MaxPool2D, AvgPool2D, AveragePooling2D, GlobalAveragePooling2D,ZeroPadding2D,Input,Embedding,PReLU\n",
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"from keras.callbacks import ModelCheckpoint\n",
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"from keras.callbacks import TensorBoard\n",
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"from keras.utils import np_utils\n",
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"from keras.preprocessing.image import ImageDataGenerator\n",
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"import keras.backend as K\n",
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"import tensorflow as tf\n",
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"import time\n",
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"from PIL import Image\n",
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"\n",
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"from os import environ\n",
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"environ['CUDA_VISIBLE_DEVICES'] = '0'"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"model = tf.keras.applications.MobileNet(\n",
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" input_shape=(128,128,3),\n",
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" alpha=0.25,\n",
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" depth_multiplier=1,\n",
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" dropout=0.001,\n",
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" include_top=True,\n",
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" weights=\"imagenet\",\n",
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" input_tensor=None,\n",
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" pooling=None,\n",
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" classes=1000,\n",
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" classifier_activation=\"softmax\",\n",
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")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"model.save(\"mbnet128_0.25.h5\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "tf20",
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"language": "python",
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"name": "tf20"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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