|
| 1 | +{ |
| 2 | + "cells": [ |
| 3 | + { |
| 4 | + "cell_type": "code", |
| 5 | + "execution_count": 1, |
| 6 | + "id": "33424fde", |
| 7 | + "metadata": {}, |
| 8 | + "outputs": [ |
| 9 | + { |
| 10 | + "ename": "ModuleNotFoundError", |
| 11 | + "evalue": "No module named 'cv2'", |
| 12 | + "output_type": "error", |
| 13 | + "traceback": [ |
| 14 | + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", |
| 15 | + "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", |
| 16 | + "Cell \u001b[0;32mIn[1], line 4\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpd\u001b[39;00m \n\u001b[1;32m 3\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mmatplotlib\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mpyplot\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mplt\u001b[39;00m\n\u001b[0;32m----> 4\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mcv2\u001b[39;00m\n\u001b[1;32m 5\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mtensorflow\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mtf\u001b[39;00m\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mPIL\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m Image\n", |
| 17 | + "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'cv2'" |
| 18 | + ] |
| 19 | + } |
| 20 | + ], |
| 21 | + "source": [ |
| 22 | + "import numpy as np \n", |
| 23 | + "import pandas as pd \n", |
| 24 | + "import matplotlib.pyplot as plt\n", |
| 25 | + "import cv2\n", |
| 26 | + "import tensorflow as tf\n", |
| 27 | + "from PIL import Image\n", |
| 28 | + "import os\n", |
| 29 | + "from sklearn.model_selection import train_test_split\n", |
| 30 | + "from keras.utils import to_categorical\n", |
| 31 | + "from keras.models import Sequential, load_model\n", |
| 32 | + "from keras.layers import Conv2D, MaxPool2D, Dense, Flatten, Dropout" |
| 33 | + ] |
| 34 | + }, |
| 35 | + { |
| 36 | + "cell_type": "code", |
| 37 | + "execution_count": null, |
| 38 | + "id": "65f36fb3", |
| 39 | + "metadata": {}, |
| 40 | + "outputs": [], |
| 41 | + "source": [] |
| 42 | + } |
| 43 | + ], |
| 44 | + "metadata": { |
| 45 | + "kernelspec": { |
| 46 | + "display_name": "Python 3 (ipykernel)", |
| 47 | + "language": "python", |
| 48 | + "name": "python3" |
| 49 | + }, |
| 50 | + "language_info": { |
| 51 | + "codemirror_mode": { |
| 52 | + "name": "ipython", |
| 53 | + "version": 3 |
| 54 | + }, |
| 55 | + "file_extension": ".py", |
| 56 | + "mimetype": "text/x-python", |
| 57 | + "name": "python", |
| 58 | + "nbconvert_exporter": "python", |
| 59 | + "pygments_lexer": "ipython3", |
| 60 | + "version": "3.10.10" |
| 61 | + } |
| 62 | + }, |
| 63 | + "nbformat": 4, |
| 64 | + "nbformat_minor": 5 |
| 65 | +} |
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