зеркало из
				https://github.com/ssciwr/AMMICO.git
				synced 2025-10-31 05:56:05 +02:00 
			
		
		
		
	
		
			
				
	
	
		
			811 строки
		
	
	
		
			24 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
			
		
		
	
	
			811 строки
		
	
	
		
			24 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
| {
 | |
|  "cells": [
 | |
|   {
 | |
|    "cell_type": "markdown",
 | |
|    "id": "d2c4d40d-8aca-4024-8d19-a65c4efe825d",
 | |
|    "metadata": {},
 | |
|    "source": [
 | |
|     "# Facial Expression recognition with DeepFace"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "attachments": {},
 | |
|    "cell_type": "markdown",
 | |
|    "id": "51f8888b-d1a3-4b85-a596-95c0993fa192",
 | |
|    "metadata": {},
 | |
|    "source": [
 | |
|     "This notebooks shows some preliminary work on detecting facial expressions with DeepFace. It is mainly meant to explore its capabilities and to decide on future research directions. We package our code into a `ammico` package that is imported here:"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "code",
 | |
|    "execution_count": 1,
 | |
|    "id": "b21e52a5-d379-42db-aae6-f2ab9ed9a369",
 | |
|    "metadata": {
 | |
|     "execution": {
 | |
|      "iopub.execute_input": "2023-05-05T09:54:19.870574Z",
 | |
|      "iopub.status.busy": "2023-05-05T09:54:19.870121Z",
 | |
|      "iopub.status.idle": "2023-05-05T09:54:32.786156Z",
 | |
|      "shell.execute_reply": "2023-05-05T09:54:32.785349Z"
 | |
|     },
 | |
|     "tags": []
 | |
|    },
 | |
|    "outputs": [],
 | |
|    "source": [
 | |
|     "import ammico\n",
 | |
|     "from ammico import utils as mutils\n",
 | |
|     "from ammico import display as mdisplay"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "markdown",
 | |
|    "id": "a2bd2153",
 | |
|    "metadata": {},
 | |
|    "source": [
 | |
|     "We select a subset of image files to try facial expression detection on. The `find_files` function finds image files within a given directory:"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "code",
 | |
|    "execution_count": 2,
 | |
|    "id": "afe7e638-f09d-47e7-9295-1c374bd64c53",
 | |
|    "metadata": {
 | |
|     "execution": {
 | |
|      "iopub.execute_input": "2023-05-05T09:54:32.790664Z",
 | |
|      "iopub.status.busy": "2023-05-05T09:54:32.789606Z",
 | |
|      "iopub.status.idle": "2023-05-05T09:54:32.795582Z",
 | |
|      "shell.execute_reply": "2023-05-05T09:54:32.794891Z"
 | |
|     },
 | |
|     "tags": []
 | |
|    },
 | |
|    "outputs": [],
 | |
|    "source": [
 | |
|     "images = mutils.find_files(\n",
 | |
|     "    path=\"data/\",\n",
 | |
|     "    limit=10,\n",
 | |
|     ")"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "markdown",
 | |
|    "id": "e149bfe5-90b0-49b2-af3d-688e41aab019",
 | |
|    "metadata": {},
 | |
|    "source": [
 | |
|     "If you want to fine tune the discovery of image files, you can provide more parameters:"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "code",
 | |
|    "execution_count": 3,
 | |
|    "id": "f38bb8ed-1004-4e33-8ed6-793cb5869400",
 | |
|    "metadata": {
 | |
|     "execution": {
 | |
|      "iopub.execute_input": "2023-05-05T09:54:32.799651Z",
 | |
|      "iopub.status.busy": "2023-05-05T09:54:32.799112Z",
 | |
|      "iopub.status.idle": "2023-05-05T09:54:32.856375Z",
 | |
|      "shell.execute_reply": "2023-05-05T09:54:32.855406Z"
 | |
|     }
 | |
|    },
 | |
|    "outputs": [],
 | |
|    "source": [
 | |
|     "?mutils.find_files"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "markdown",
 | |
|    "id": "705e7328",
 | |
|    "metadata": {},
 | |
|    "source": [
 | |
|     "We need to initialize the main dictionary that contains all information for the images and is updated through each subsequent analysis:"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "code",
 | |
|    "execution_count": 4,
 | |
|    "id": "b37c0c91",
 | |
|    "metadata": {
 | |
|     "execution": {
 | |
|      "iopub.execute_input": "2023-05-05T09:54:32.861399Z",
 | |
|      "iopub.status.busy": "2023-05-05T09:54:32.861110Z",
 | |
|      "iopub.status.idle": "2023-05-05T09:54:32.865285Z",
 | |
|      "shell.execute_reply": "2023-05-05T09:54:32.864308Z"
 | |
|     },
 | |
|     "tags": []
 | |
|    },
 | |
|    "outputs": [],
 | |
|    "source": [
 | |
|     "mydict = mutils.initialize_dict(images)"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "markdown",
 | |
|    "id": "a9372561",
 | |
|    "metadata": {},
 | |
|    "source": [
 | |
|     "To check the analysis, you can inspect the analyzed elements here. Loading the results takes a moment, so please be patient. If you are sure of what you are doing, you can skip this and directly export a csv file in the step below.\n",
 | |
|     "Here, we display the face recognition results provided by the DeepFace library. Click on the tabs to see the results in the right sidebar:"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "code",
 | |
|    "execution_count": 5,
 | |
|    "id": "992499ed-33f1-4425-ad5d-738cf565d175",
 | |
|    "metadata": {
 | |
|     "execution": {
 | |
|      "iopub.execute_input": "2023-05-05T09:54:32.869290Z",
 | |
|      "iopub.status.busy": "2023-05-05T09:54:32.869029Z",
 | |
|      "iopub.status.idle": "2023-05-05T09:54:34.108152Z",
 | |
|      "shell.execute_reply": "2023-05-05T09:54:34.107056Z"
 | |
|     },
 | |
|     "tags": []
 | |
|    },
 | |
|    "outputs": [
 | |
|     {
 | |
|      "ename": "AttributeError",
 | |
|      "evalue": "module 'ammico.display' has no attribute 'explore_analysis'",
 | |
|      "output_type": "error",
 | |
|      "traceback": [
 | |
|       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
 | |
|       "\u001b[0;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
 | |
|       "Cell \u001b[0;32mIn[5], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mmdisplay\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexplore_analysis\u001b[49m(mydict, identify\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfaces\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
 | |
|       "\u001b[0;31mAttributeError\u001b[0m: module 'ammico.display' has no attribute 'explore_analysis'"
 | |
|      ]
 | |
|     }
 | |
|    ],
 | |
|    "source": [
 | |
|     "mdisplay.explore_analysis(mydict, identify=\"faces\")"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "markdown",
 | |
|    "id": "6f974341",
 | |
|    "metadata": {},
 | |
|    "source": [
 | |
|     "Directly carry out the analysis and export the result into a csv: Analysis - "
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "code",
 | |
|    "execution_count": 6,
 | |
|    "id": "6f97c7d0",
 | |
|    "metadata": {
 | |
|     "execution": {
 | |
|      "iopub.execute_input": "2023-05-05T09:54:34.114131Z",
 | |
|      "iopub.status.busy": "2023-05-05T09:54:34.113432Z",
 | |
|      "iopub.status.idle": "2023-05-05T09:56:16.560350Z",
 | |
|      "shell.execute_reply": "2023-05-05T09:56:16.558959Z"
 | |
|     },
 | |
|     "tags": []
 | |
|    },
 | |
|    "outputs": [
 | |
|     {
 | |
|      "name": "stderr",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "Downloading data from 'https://github.com/serengil/deepface_models/releases/download/v1.0/retinaface.h5' to file '/home/runner/.cache/pooch/3be32af6e4183fa0156bc33bda371147-retinaface.h5'.\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stderr",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "Downloading data from 'https://github.com/chandrikadeb7/Face-Mask-Detection/raw/v1.0.0/mask_detector.model' to file '/home/runner/.cache/pooch/865b4b1e20f798935b70082440d5fb21-mask_detector.model'.\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stderr",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "Downloading data from 'https://github.com/serengil/deepface_models/releases/download/v1.0/age_model_weights.h5' to file '/home/runner/.cache/pooch/39859d3331cd91ac06154cc306e1acc8-age_model_weights.h5'.\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stderr",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "Downloading data from 'https://github.com/serengil/deepface_models/releases/download/v1.0/facial_expression_model_weights.h5' to file '/home/runner/.cache/pooch/dd5d5d6d8f5cecdc0fa6cb34d4d82d16-facial_expression_model_weights.h5'.\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stderr",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "Downloading data from 'https://github.com/serengil/deepface_models/releases/download/v1.0/gender_model_weights.h5' to file '/home/runner/.cache/pooch/2e0d8fb96c5ee966ade0f3f2360f6478-gender_model_weights.h5'.\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stderr",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "Downloading data from 'https://github.com/serengil/deepface_models/releases/download/v1.0/race_model_single_batch.h5' to file '/home/runner/.cache/pooch/382cb5446128012fa5305ddb9d608751-race_model_single_batch.h5'.\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\r",
 | |
|       "1/1 [==============================] - ETA: 0s"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
 | |
|       "1/1 [==============================] - 0s 391ms/step\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\r",
 | |
|       "1/1 [==============================] - ETA: 0s"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
 | |
|       "1/1 [==============================] - 0s 400ms/step\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\r",
 | |
|       "1/1 [==============================] - ETA: 0s"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
 | |
|       "1/1 [==============================] - 0s 222ms/step\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\r",
 | |
|       "1/1 [==============================] - ETA: 0s"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
 | |
|       "1/1 [==============================] - 0s 224ms/step\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\r",
 | |
|       "1/1 [==============================] - ETA: 0s"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
 | |
|       "1/1 [==============================] - 0s 234ms/step\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\r",
 | |
|       "1/1 [==============================] - ETA: 0s"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
 | |
|       "1/1 [==============================] - 0s 223ms/step\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\r",
 | |
|       "1/1 [==============================] - ETA: 0s"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
 | |
|       "1/1 [==============================] - 0s 393ms/step\n"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\r",
 | |
|       "1/1 [==============================] - ETA: 0s"
 | |
|      ]
 | |
|     },
 | |
|     {
 | |
|      "name": "stdout",
 | |
|      "output_type": "stream",
 | |
|      "text": [
 | |
|       "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r",
 | |
|       "1/1 [==============================] - 0s 104ms/step\n"
 | |
|      ]
 | |
|     }
 | |
|    ],
 | |
|    "source": [
 | |
|     "for key in mydict.keys():\n",
 | |
|     "    mydict[key] = ammico.faces.EmotionDetector(mydict[key]).analyse_image()"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "markdown",
 | |
|    "id": "174357b1",
 | |
|    "metadata": {},
 | |
|    "source": [
 | |
|     "Convert the dictionary of dictionarys into a dictionary with lists:"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "code",
 | |
|    "execution_count": 7,
 | |
|    "id": "604bd257",
 | |
|    "metadata": {
 | |
|     "execution": {
 | |
|      "iopub.execute_input": "2023-05-05T09:56:16.581097Z",
 | |
|      "iopub.status.busy": "2023-05-05T09:56:16.580841Z",
 | |
|      "iopub.status.idle": "2023-05-05T09:56:16.588626Z",
 | |
|      "shell.execute_reply": "2023-05-05T09:56:16.587867Z"
 | |
|     },
 | |
|     "tags": []
 | |
|    },
 | |
|    "outputs": [],
 | |
|    "source": [
 | |
|     "outdict = mutils.append_data_to_dict(mydict)\n",
 | |
|     "df = mutils.dump_df(outdict)"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "markdown",
 | |
|    "id": "8373d9f8",
 | |
|    "metadata": {},
 | |
|    "source": [
 | |
|     "Check the dataframe:"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "code",
 | |
|    "execution_count": 8,
 | |
|    "id": "aa4b518a",
 | |
|    "metadata": {
 | |
|     "execution": {
 | |
|      "iopub.execute_input": "2023-05-05T09:56:16.592081Z",
 | |
|      "iopub.status.busy": "2023-05-05T09:56:16.591666Z",
 | |
|      "iopub.status.idle": "2023-05-05T09:56:16.633425Z",
 | |
|      "shell.execute_reply": "2023-05-05T09:56:16.632503Z"
 | |
|     },
 | |
|     "tags": []
 | |
|    },
 | |
|    "outputs": [
 | |
|     {
 | |
|      "data": {
 | |
|       "text/html": [
 | |
|        "<div>\n",
 | |
|        "<style scoped>\n",
 | |
|        "    .dataframe tbody tr th:only-of-type {\n",
 | |
|        "        vertical-align: middle;\n",
 | |
|        "    }\n",
 | |
|        "\n",
 | |
|        "    .dataframe tbody tr th {\n",
 | |
|        "        vertical-align: top;\n",
 | |
|        "    }\n",
 | |
|        "\n",
 | |
|        "    .dataframe thead th {\n",
 | |
|        "        text-align: right;\n",
 | |
|        "    }\n",
 | |
|        "</style>\n",
 | |
|        "<table border=\"1\" class=\"dataframe\">\n",
 | |
|        "  <thead>\n",
 | |
|        "    <tr style=\"text-align: right;\">\n",
 | |
|        "      <th></th>\n",
 | |
|        "      <th>filename</th>\n",
 | |
|        "      <th>face</th>\n",
 | |
|        "      <th>multiple_faces</th>\n",
 | |
|        "      <th>no_faces</th>\n",
 | |
|        "      <th>wears_mask</th>\n",
 | |
|        "      <th>age</th>\n",
 | |
|        "      <th>gender</th>\n",
 | |
|        "      <th>race</th>\n",
 | |
|        "      <th>emotion</th>\n",
 | |
|        "      <th>emotion (category)</th>\n",
 | |
|        "    </tr>\n",
 | |
|        "  </thead>\n",
 | |
|        "  <tbody>\n",
 | |
|        "    <tr>\n",
 | |
|        "      <th>0</th>\n",
 | |
|        "      <td>data/102141_2_eng.png</td>\n",
 | |
|        "      <td>Yes</td>\n",
 | |
|        "      <td>No</td>\n",
 | |
|        "      <td>1</td>\n",
 | |
|        "      <td>[Yes]</td>\n",
 | |
|        "      <td>[25]</td>\n",
 | |
|        "      <td>[Man]</td>\n",
 | |
|        "      <td>[None]</td>\n",
 | |
|        "      <td>[None]</td>\n",
 | |
|        "      <td>[None]</td>\n",
 | |
|        "    </tr>\n",
 | |
|        "    <tr>\n",
 | |
|        "      <th>1</th>\n",
 | |
|        "      <td>data/106349S_por.png</td>\n",
 | |
|        "      <td>Yes</td>\n",
 | |
|        "      <td>No</td>\n",
 | |
|        "      <td>1</td>\n",
 | |
|        "      <td>[Yes]</td>\n",
 | |
|        "      <td>[24]</td>\n",
 | |
|        "      <td>[Man]</td>\n",
 | |
|        "      <td>[None]</td>\n",
 | |
|        "      <td>[None]</td>\n",
 | |
|        "      <td>[None]</td>\n",
 | |
|        "    </tr>\n",
 | |
|        "    <tr>\n",
 | |
|        "      <th>2</th>\n",
 | |
|        "      <td>data/102730_eng.png</td>\n",
 | |
|        "      <td>Yes</td>\n",
 | |
|        "      <td>No</td>\n",
 | |
|        "      <td>1</td>\n",
 | |
|        "      <td>[No]</td>\n",
 | |
|        "      <td>[27]</td>\n",
 | |
|        "      <td>[Man]</td>\n",
 | |
|        "      <td>[asian]</td>\n",
 | |
|        "      <td>[sad]</td>\n",
 | |
|        "      <td>[Negative]</td>\n",
 | |
|        "    </tr>\n",
 | |
|        "  </tbody>\n",
 | |
|        "</table>\n",
 | |
|        "</div>"
 | |
|       ],
 | |
|       "text/plain": [
 | |
|        "                filename face multiple_faces  no_faces wears_mask   age   \n",
 | |
|        "0  data/102141_2_eng.png  Yes             No         1      [Yes]  [25]  \\\n",
 | |
|        "1   data/106349S_por.png  Yes             No         1      [Yes]  [24]   \n",
 | |
|        "2    data/102730_eng.png  Yes             No         1       [No]  [27]   \n",
 | |
|        "\n",
 | |
|        "  gender     race emotion emotion (category)  \n",
 | |
|        "0  [Man]   [None]  [None]             [None]  \n",
 | |
|        "1  [Man]   [None]  [None]             [None]  \n",
 | |
|        "2  [Man]  [asian]   [sad]         [Negative]  "
 | |
|       ]
 | |
|      },
 | |
|      "execution_count": 8,
 | |
|      "metadata": {},
 | |
|      "output_type": "execute_result"
 | |
|     }
 | |
|    ],
 | |
|    "source": [
 | |
|     "df.head(10)"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "markdown",
 | |
|    "id": "579cd59f",
 | |
|    "metadata": {},
 | |
|    "source": [
 | |
|     "Write the csv file:"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "code",
 | |
|    "execution_count": 9,
 | |
|    "id": "4618decb",
 | |
|    "metadata": {
 | |
|     "execution": {
 | |
|      "iopub.execute_input": "2023-05-05T09:56:16.638758Z",
 | |
|      "iopub.status.busy": "2023-05-05T09:56:16.638479Z",
 | |
|      "iopub.status.idle": "2023-05-05T09:56:16.647377Z",
 | |
|      "shell.execute_reply": "2023-05-05T09:56:16.646685Z"
 | |
|     },
 | |
|     "tags": []
 | |
|    },
 | |
|    "outputs": [],
 | |
|    "source": [
 | |
|     "df.to_csv(\"data/data_out.csv\")"
 | |
|    ]
 | |
|   },
 | |
|   {
 | |
|    "cell_type": "code",
 | |
|    "execution_count": null,
 | |
|    "id": "b1a80023",
 | |
|    "metadata": {},
 | |
|    "outputs": [],
 | |
|    "source": []
 | |
|   }
 | |
|  ],
 | |
|  "metadata": {
 | |
|   "kernelspec": {
 | |
|    "display_name": "Python 3",
 | |
|    "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": "3.9.16"
 | |
|   },
 | |
|   "vscode": {
 | |
|    "interpreter": {
 | |
|     "hash": "da98320027a74839c7141b42ef24e2d47d628ba1f51115c13da5d8b45a372ec2"
 | |
|    }
 | |
|   },
 | |
|   "widgets": {
 | |
|    "application/vnd.jupyter.widget-state+json": {
 | |
|     "state": {
 | |
|      "0a1f129633f44180a7f116ca963e5bb3": {
 | |
|       "model_module": "@jupyter-widgets/output",
 | |
|       "model_module_version": "1.0.0",
 | |
|       "model_name": "OutputModel",
 | |
|       "state": {
 | |
|        "_dom_classes": [],
 | |
|        "_model_module": "@jupyter-widgets/output",
 | |
|        "_model_module_version": "1.0.0",
 | |
|        "_model_name": "OutputModel",
 | |
|        "_view_count": null,
 | |
|        "_view_module": "@jupyter-widgets/output",
 | |
|        "_view_module_version": "1.0.0",
 | |
|        "_view_name": "OutputView",
 | |
|        "layout": "IPY_MODEL_6635cef7ca7346b989599eadeda1c10b",
 | |
|        "msg_id": "",
 | |
|        "outputs": [
 | |
|         {
 | |
|          "name": "stdout",
 | |
|          "output_type": "stream",
 | |
|          "text": "\r1/1 [==============================] - ETA: 0s\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1/1 [==============================] - 1s 822ms/step\n"
 | |
|         }
 | |
|        ],
 | |
|        "tabbable": null,
 | |
|        "tooltip": null
 | |
|       }
 | |
|      },
 | |
|      "6635cef7ca7346b989599eadeda1c10b": {
 | |
|       "model_module": "@jupyter-widgets/base",
 | |
|       "model_module_version": "2.0.0",
 | |
|       "model_name": "LayoutModel",
 | |
|       "state": {
 | |
|        "_model_module": "@jupyter-widgets/base",
 | |
|        "_model_module_version": "2.0.0",
 | |
|        "_model_name": "LayoutModel",
 | |
|        "_view_count": null,
 | |
|        "_view_module": "@jupyter-widgets/base",
 | |
|        "_view_module_version": "2.0.0",
 | |
|        "_view_name": "LayoutView",
 | |
|        "align_content": null,
 | |
|        "align_items": null,
 | |
|        "align_self": null,
 | |
|        "border_bottom": null,
 | |
|        "border_left": null,
 | |
|        "border_right": null,
 | |
|        "border_top": null,
 | |
|        "bottom": null,
 | |
|        "display": null,
 | |
|        "flex": null,
 | |
|        "flex_flow": null,
 | |
|        "grid_area": null,
 | |
|        "grid_auto_columns": null,
 | |
|        "grid_auto_flow": null,
 | |
|        "grid_auto_rows": null,
 | |
|        "grid_column": null,
 | |
|        "grid_gap": null,
 | |
|        "grid_row": null,
 | |
|        "grid_template_areas": null,
 | |
|        "grid_template_columns": null,
 | |
|        "grid_template_rows": null,
 | |
|        "height": null,
 | |
|        "justify_content": null,
 | |
|        "justify_items": null,
 | |
|        "left": null,
 | |
|        "margin": null,
 | |
|        "max_height": null,
 | |
|        "max_width": null,
 | |
|        "min_height": null,
 | |
|        "min_width": null,
 | |
|        "object_fit": null,
 | |
|        "object_position": null,
 | |
|        "order": null,
 | |
|        "overflow": null,
 | |
|        "padding": null,
 | |
|        "right": null,
 | |
|        "top": null,
 | |
|        "visibility": null,
 | |
|        "width": null
 | |
|       }
 | |
|      },
 | |
|      "a79253e9af2341d08916cc03e958b58a": {
 | |
|       "model_module": "@jupyter-widgets/output",
 | |
|       "model_module_version": "1.0.0",
 | |
|       "model_name": "OutputModel",
 | |
|       "state": {
 | |
|        "_dom_classes": [],
 | |
|        "_model_module": "@jupyter-widgets/output",
 | |
|        "_model_module_version": "1.0.0",
 | |
|        "_model_name": "OutputModel",
 | |
|        "_view_count": null,
 | |
|        "_view_module": "@jupyter-widgets/output",
 | |
|        "_view_module_version": "1.0.0",
 | |
|        "_view_name": "OutputView",
 | |
|        "layout": "IPY_MODEL_cf512dd9b96c4c65bc4b83cb6abfac31",
 | |
|        "msg_id": "",
 | |
|        "outputs": [
 | |
|         {
 | |
|          "name": "stdout",
 | |
|          "output_type": "stream",
 | |
|          "text": "\r1/1 [==============================] - ETA: 0s\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1/1 [==============================] - 1s 822ms/step\n"
 | |
|         }
 | |
|        ],
 | |
|        "tabbable": null,
 | |
|        "tooltip": null
 | |
|       }
 | |
|      },
 | |
|      "a9f18bbae0054eb2b297c55351b9b106": {
 | |
|       "model_module": "@jupyter-widgets/output",
 | |
|       "model_module_version": "1.0.0",
 | |
|       "model_name": "OutputModel",
 | |
|       "state": {
 | |
|        "_dom_classes": [],
 | |
|        "_model_module": "@jupyter-widgets/output",
 | |
|        "_model_module_version": "1.0.0",
 | |
|        "_model_name": "OutputModel",
 | |
|        "_view_count": null,
 | |
|        "_view_module": "@jupyter-widgets/output",
 | |
|        "_view_module_version": "1.0.0",
 | |
|        "_view_name": "OutputView",
 | |
|        "layout": "IPY_MODEL_fc39b5265819436da2fd8c81c45fa866",
 | |
|        "msg_id": "",
 | |
|        "outputs": [
 | |
|         {
 | |
|          "name": "stdout",
 | |
|          "output_type": "stream",
 | |
|          "text": "\r1/1 [==============================] - ETA: 0s\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r1/1 [==============================] - 1s 864ms/step\n"
 | |
|         }
 | |
|        ],
 | |
|        "tabbable": null,
 | |
|        "tooltip": null
 | |
|       }
 | |
|      },
 | |
|      "cf512dd9b96c4c65bc4b83cb6abfac31": {
 | |
|       "model_module": "@jupyter-widgets/base",
 | |
|       "model_module_version": "2.0.0",
 | |
|       "model_name": "LayoutModel",
 | |
|       "state": {
 | |
|        "_model_module": "@jupyter-widgets/base",
 | |
|        "_model_module_version": "2.0.0",
 | |
|        "_model_name": "LayoutModel",
 | |
|        "_view_count": null,
 | |
|        "_view_module": "@jupyter-widgets/base",
 | |
|        "_view_module_version": "2.0.0",
 | |
|        "_view_name": "LayoutView",
 | |
|        "align_content": null,
 | |
|        "align_items": null,
 | |
|        "align_self": null,
 | |
|        "border_bottom": null,
 | |
|        "border_left": null,
 | |
|        "border_right": null,
 | |
|        "border_top": null,
 | |
|        "bottom": null,
 | |
|        "display": null,
 | |
|        "flex": null,
 | |
|        "flex_flow": null,
 | |
|        "grid_area": null,
 | |
|        "grid_auto_columns": null,
 | |
|        "grid_auto_flow": null,
 | |
|        "grid_auto_rows": null,
 | |
|        "grid_column": null,
 | |
|        "grid_gap": null,
 | |
|        "grid_row": null,
 | |
|        "grid_template_areas": null,
 | |
|        "grid_template_columns": null,
 | |
|        "grid_template_rows": null,
 | |
|        "height": null,
 | |
|        "justify_content": null,
 | |
|        "justify_items": null,
 | |
|        "left": null,
 | |
|        "margin": null,
 | |
|        "max_height": null,
 | |
|        "max_width": null,
 | |
|        "min_height": null,
 | |
|        "min_width": null,
 | |
|        "object_fit": null,
 | |
|        "object_position": null,
 | |
|        "order": null,
 | |
|        "overflow": null,
 | |
|        "padding": null,
 | |
|        "right": null,
 | |
|        "top": null,
 | |
|        "visibility": null,
 | |
|        "width": null
 | |
|       }
 | |
|      },
 | |
|      "fc39b5265819436da2fd8c81c45fa866": {
 | |
|       "model_module": "@jupyter-widgets/base",
 | |
|       "model_module_version": "2.0.0",
 | |
|       "model_name": "LayoutModel",
 | |
|       "state": {
 | |
|        "_model_module": "@jupyter-widgets/base",
 | |
|        "_model_module_version": "2.0.0",
 | |
|        "_model_name": "LayoutModel",
 | |
|        "_view_count": null,
 | |
|        "_view_module": "@jupyter-widgets/base",
 | |
|        "_view_module_version": "2.0.0",
 | |
|        "_view_name": "LayoutView",
 | |
|        "align_content": null,
 | |
|        "align_items": null,
 | |
|        "align_self": null,
 | |
|        "border_bottom": null,
 | |
|        "border_left": null,
 | |
|        "border_right": null,
 | |
|        "border_top": null,
 | |
|        "bottom": null,
 | |
|        "display": null,
 | |
|        "flex": null,
 | |
|        "flex_flow": null,
 | |
|        "grid_area": null,
 | |
|        "grid_auto_columns": null,
 | |
|        "grid_auto_flow": null,
 | |
|        "grid_auto_rows": null,
 | |
|        "grid_column": null,
 | |
|        "grid_gap": null,
 | |
|        "grid_row": null,
 | |
|        "grid_template_areas": null,
 | |
|        "grid_template_columns": null,
 | |
|        "grid_template_rows": null,
 | |
|        "height": null,
 | |
|        "justify_content": null,
 | |
|        "justify_items": null,
 | |
|        "left": null,
 | |
|        "margin": null,
 | |
|        "max_height": null,
 | |
|        "max_width": null,
 | |
|        "min_height": null,
 | |
|        "min_width": null,
 | |
|        "object_fit": null,
 | |
|        "object_position": null,
 | |
|        "order": null,
 | |
|        "overflow": null,
 | |
|        "padding": null,
 | |
|        "right": null,
 | |
|        "top": null,
 | |
|        "visibility": null,
 | |
|        "width": null
 | |
|       }
 | |
|      }
 | |
|     },
 | |
|     "version_major": 2,
 | |
|     "version_minor": 0
 | |
|    }
 | |
|   }
 | |
|  },
 | |
|  "nbformat": 4,
 | |
|  "nbformat_minor": 5
 | |
| }
 | 
