Zadanie Biblioteka_DL
This commit is contained in:
parent
51236af46f
commit
0f7264d4d1
250
Biblioteka_DL_predykcja.ipynb
Normal file
250
Biblioteka_DL_predykcja.ipynb
Normal file
@ -0,0 +1,250 @@
|
|||||||
|
{
|
||||||
|
"cells": [
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "0f5b3979-7704-4ea7-ac84-424f73e9a62d",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"# Predykcja na modelu zapisanym w pliku"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "ef017730-4bbd-4fad-926a-2800fa636ccd",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Import bibliotek"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 1,
|
||||||
|
"id": "a330d65d-8876-49b8-9507-27ee9f50d1e6",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"import keras\n",
|
||||||
|
"import pandas as pd\n",
|
||||||
|
"from sklearn.preprocessing import MinMaxScaler, OneHotEncoder\n",
|
||||||
|
"import numpy as np\n",
|
||||||
|
"from sklearn.model_selection import train_test_split"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "4bd52369-8c81-45a1-b091-5edae9bc2673",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Pobranie modelu z pliku"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 2,
|
||||||
|
"id": "aa7d4e1f-2924-4c84-a06b-f19b451e923b",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"model = keras.models.load_model('./model.keras')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "1c94dca7-7670-4ed9-b6ca-5c59c734cc44",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Przygotowanie danych do testowania modelu"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 3,
|
||||||
|
"id": "3e72f7ea-91a6-45ac-9f38-872175ad2a8d",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"dataset = pd.read_csv('./lettuce-growth-days/lettuce_dataset_updated.csv', encoding='ISO-8859-1')"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 4,
|
||||||
|
"id": "9f52a6e7-ae62-4ea6-bde5-e2b221fa2d7a",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"ph_level = dataset['pH Level'].values.tolist()\n",
|
||||||
|
"temp_F = dataset['Temperature (F)'].values.tolist()\n",
|
||||||
|
"humid = dataset['Humidity'].values.tolist()\n",
|
||||||
|
"days = dataset['Growth Days'].values.tolist()\n",
|
||||||
|
"plant_id = dataset['Plant_ID'].values.tolist()"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 5,
|
||||||
|
"id": "a720aa83-bb5a-4c6f-89a5-f6e1fb7cf0e2",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"X = []\n",
|
||||||
|
"Y = []\n",
|
||||||
|
"\n",
|
||||||
|
"id = plant_id[0]\n",
|
||||||
|
"temp_sum = 0\n",
|
||||||
|
"humid_sum = 0\n",
|
||||||
|
"ph_level_sum = 0\n",
|
||||||
|
"day = 1\n",
|
||||||
|
"\n",
|
||||||
|
"for i in range(0, len(plant_id)):\n",
|
||||||
|
" if plant_id[i] == id:\n",
|
||||||
|
" temp_sum += temp_F[i]\n",
|
||||||
|
" humid_sum += humid[i]\n",
|
||||||
|
" ph_level_sum += ph_level[i]\n",
|
||||||
|
" day = days[i]\n",
|
||||||
|
" else:\n",
|
||||||
|
" temp = []\n",
|
||||||
|
" temp.append(temp_sum/day)\n",
|
||||||
|
" temp.append(humid_sum/day)\n",
|
||||||
|
" temp.append(ph_level_sum/day)\n",
|
||||||
|
" X.append(temp)\n",
|
||||||
|
" Y.append(day)\n",
|
||||||
|
" temp_sum = 0\n",
|
||||||
|
" humid_sum = 0\n",
|
||||||
|
" ph_level_sum = 0\n",
|
||||||
|
" day = 1\n",
|
||||||
|
" id = plant_id[i]"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 6,
|
||||||
|
"id": "d8ef6898-38bb-4191-b7b9-bc47dd1ae5d8",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"name": "stderr",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"C:\\Users\\obses\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\sklearn\\preprocessing\\_encoders.py:808: FutureWarning: `sparse` was renamed to `sparse_output` in version 1.2 and will be removed in 1.4. `sparse_output` is ignored unless you leave `sparse` to its default value.\n",
|
||||||
|
" warnings.warn(\n"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"scaler = MinMaxScaler()\n",
|
||||||
|
"X = scaler.fit_transform(X)\n",
|
||||||
|
"X = np.array(X)\n",
|
||||||
|
"Y = np.array(Y)\n",
|
||||||
|
"\n",
|
||||||
|
"encoder = OneHotEncoder(sparse=False)\n",
|
||||||
|
"y_onehot = encoder.fit_transform(Y.reshape(-1,1))\n",
|
||||||
|
"\n",
|
||||||
|
"X_train, X_test, y_train, y_test = train_test_split(X, y_onehot, test_size=0.4, random_state=42)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "72650088-d370-4814-b381-6e5a5e01fe58",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Testowanie modelu"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 7,
|
||||||
|
"id": "ed8d7cb0-eefd-4e64-80e1-4ea4ff6bb369",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 216ms/step - accuracy: 0.8571 - loss: 0.7300\n",
|
||||||
|
"Dokładność testowa: 85.71%\n"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"test_loss, test_accuracy = model.evaluate(X_test, y_test)\n",
|
||||||
|
"print(f\"Dokładność testowa: {test_accuracy:.2%}\")"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "5f0bceec-f95e-4192-aced-c9997eafee28",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Predykcja na zbiorze testowym"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 8,
|
||||||
|
"id": "6ce776f4-859b-42d9-a756-bd29b11d1b56",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"name": "stdout",
|
||||||
|
"output_type": "stream",
|
||||||
|
"text": [
|
||||||
|
"\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 32ms/step\n"
|
||||||
|
]
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"source": [
|
||||||
|
"predictions = model.predict(X_test)"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "markdown",
|
||||||
|
"id": "9908472c-08ae-4e46-afe3-27eefb43f671",
|
||||||
|
"metadata": {},
|
||||||
|
"source": [
|
||||||
|
"## Zapisanie wyników predykcji do pliku tekstowego"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": 9,
|
||||||
|
"id": "738043a9-a312-4f96-af22-593362bc9624",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": [
|
||||||
|
"with open(\"predictions.txt\", \"w\") as txt_file:\n",
|
||||||
|
" for line in predictions:\n",
|
||||||
|
" txt_file.write(\" \".join(str(line)) + \"\\n\") "
|
||||||
|
]
|
||||||
|
},
|
||||||
|
{
|
||||||
|
"cell_type": "code",
|
||||||
|
"execution_count": null,
|
||||||
|
"id": "da604cf2-d13d-4dd3-a596-7b24ba5d92ef",
|
||||||
|
"metadata": {},
|
||||||
|
"outputs": [],
|
||||||
|
"source": []
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"metadata": {
|
||||||
|
"kernelspec": {
|
||||||
|
"display_name": "Python 3 (ipykernel)",
|
||||||
|
"language": "python",
|
||||||
|
"name": "python3"
|
||||||
|
},
|
||||||
|
"language_info": {
|
||||||
|
"codemirror_mode": {
|
||||||
|
"name": "ipython",
|
||||||
|
"version": 3
|
||||||
|
},
|
||||||
|
"file_extension": ".py",
|
||||||
|
"mimetype": "text/x-python",
|
||||||
|
"name": "python",
|
||||||
|
"nbconvert_exporter": "python",
|
||||||
|
"pygments_lexer": "ipython3",
|
||||||
|
"version": "3.10.0"
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"nbformat": 4,
|
||||||
|
"nbformat_minor": 5
|
||||||
|
}
|
||||||
1492
Biblioteka_DL_trenowanie.ipynb
Normal file
1492
Biblioteka_DL_trenowanie.ipynb
Normal file
File diff suppressed because one or more lines are too long
BIN
model.keras
Normal file
BIN
model.keras
Normal file
Binary file not shown.
28
predictions.txt
Normal file
28
predictions.txt
Normal file
@ -0,0 +1,28 @@
|
|||||||
|
[ 0 . 8 2 0 6 9 7 3 7 0 . 0 6 0 7 2 1 0 3 0 . 0 5 8 7 7 2 5 4 0 . 0 5 9 8 0 9 0 1 ]
|
||||||
|
[ 0 . 8 1 9 4 0 3 0 . 0 6 0 1 6 5 9 2 0 . 0 5 9 7 4 9 6 9 0 . 0 6 0 6 8 1 3 7 ]
|
||||||
|
[ 0 . 8 2 0 4 8 6 5 0 . 0 6 1 0 7 1 7 5 0 . 0 5 8 4 5 9 1 8 0 . 0 5 9 9 8 2 6 2 ]
|
||||||
|
[ 0 . 8 2 0 9 4 1 6 0 . 0 6 0 8 1 3 3 7 0 . 0 5 8 6 2 1 7 1 0 . 0 5 9 6 2 3 2 4 ]
|
||||||
|
[ 0 . 8 1 7 8 2 1 7 0 . 0 6 0 7 7 7 4 3 0 . 0 5 9 4 8 8 8 8 0 . 0 6 1 9 1 2 0 2 ]
|
||||||
|
[ 0 . 8 2 2 5 0 9 0 5 0 . 0 6 0 3 7 7 2 1 0 . 0 5 8 6 7 3 3 1 0 . 0 5 8 4 4 0 4 ]
|
||||||
|
[ 0 . 8 2 0 6 0 2 5 0 . 0 6 0 9 0 9 4 4 0 . 0 5 8 6 2 1 3 3 0 . 0 5 9 8 6 6 8 3 ]
|
||||||
|
[ 0 . 8 1 9 5 1 0 3 0 . 0 6 1 5 2 3 2 0 . 0 5 8 1 0 4 4 1 0 . 0 6 0 8 6 2 0 7 ]
|
||||||
|
[ 0 . 8 1 9 9 4 1 3 0 . 0 6 1 2 0 8 3 6 0 . 0 5 8 4 2 5 1 0 . 0 6 0 4 2 5 2 4 ]
|
||||||
|
[ 0 . 8 2 0 2 4 8 3 7 0 . 0 6 0 7 7 6 7 0 . 0 5 8 8 3 0 0 6 0 . 0 6 0 1 4 4 8 2 ]
|
||||||
|
[ 0 . 8 2 2 0 1 4 0 . 0 6 0 6 2 5 0 9 0 . 0 5 8 5 2 6 2 2 0 . 0 5 8 8 3 4 7 6 ]
|
||||||
|
[ 0 . 8 2 1 5 5 4 1 0 . 0 6 0 6 1 0 7 1 0 . 0 5 8 6 5 6 6 2 0 . 0 5 9 1 7 8 5 3 ]
|
||||||
|
[ 0 . 8 2 4 2 7 4 3 6 0 . 0 5 8 8 5 8 9 8 0 . 0 5 7 7 4 6 2 1 0 . 0 5 9 1 2 0 4 3 ]
|
||||||
|
[ 0 . 8 2 0 0 5 1 9 0 . 0 6 0 7 4 2 2 6 0 . 0 5 8 9 1 1 5 0 . 0 6 0 2 9 4 3 1 ]
|
||||||
|
[ 0 . 8 1 8 1 1 7 9 0 . 0 6 0 7 9 4 2 2 0 . 0 5 9 3 5 3 4 0 . 0 6 1 7 3 4 4 7 ]
|
||||||
|
[ 0 . 8 2 0 5 7 1 5 0 . 0 6 0 4 4 2 9 4 0 . 0 5 9 0 6 4 4 7 0 . 0 5 9 9 2 1 1 ]
|
||||||
|
[ 0 . 8 1 8 6 6 0 1 4 0 . 0 6 0 5 3 2 2 2 0 . 0 5 9 2 6 8 3 7 0 . 0 6 1 5 3 9 3 5 ]
|
||||||
|
[ 0 . 8 2 1 7 4 3 9 7 0 . 0 6 0 8 7 3 9 1 0 . 0 5 8 3 5 3 0 6 0 . 0 5 9 0 2 9 1 1 ]
|
||||||
|
[ 0 . 8 1 9 0 0 0 1 0 . 0 6 0 4 3 0 5 1 0 . 0 5 9 1 0 2 3 6 0 . 0 6 1 4 6 6 9 9 ]
|
||||||
|
[ 0 . 8 2 2 7 3 4 1 0 . 0 6 0 7 8 6 7 1 0 . 0 5 8 2 3 6 8 3 0 . 0 5 8 2 4 2 3 9 ]
|
||||||
|
[ 0 . 8 2 0 9 7 1 9 7 0 . 0 6 0 9 6 9 1 4 0 . 0 5 8 4 5 4 2 6 0 . 0 5 9 6 0 4 5 6 ]
|
||||||
|
[ 0 . 8 2 1 9 8 5 4 0 . 0 6 0 7 6 9 5 7 0 . 0 5 8 3 9 8 4 4 0 . 0 5 8 8 4 6 4 8 ]
|
||||||
|
[ 0 . 8 1 9 3 3 4 7 0 . 0 6 1 4 1 3 1 2 0 . 0 5 8 3 1 4 6 1 0 . 0 6 0 9 3 7 6 9 ]
|
||||||
|
[ 0 . 8 2 1 2 3 6 3 0 . 0 6 0 4 1 5 1 6 0 . 0 5 8 9 3 4 0 2 0 . 0 5 9 4 1 4 4 9 ]
|
||||||
|
[ 0 . 8 2 1 6 6 5 0 5 0 . 0 6 0 5 1 5 5 3 0 . 0 5 8 7 1 7 7 2 0 . 0 5 9 1 0 1 5 9 ]
|
||||||
|
[ 0 . 8 2 0 3 2 4 0 . 0 6 0 1 8 1 9 6 0 . 0 5 8 6 6 6 9 3 0 . 0 6 0 8 2 7 1 3 ]
|
||||||
|
[ 0 . 8 1 9 5 5 6 6 5 0 . 0 6 0 9 5 2 7 0 . 0 5 8 8 3 7 6 8 0 . 0 6 0 6 5 3 ]
|
||||||
|
[ 0 . 8 1 9 3 3 4 2 7 0 . 0 6 1 3 1 9 7 4 0 . 0 5 8 4 4 8 6 4 0 . 0 6 0 8 9 7 3 9 ]
|
||||||
Loading…
Reference in New Issue
Block a user