77 lines
2.0 KiB
Plaintext
77 lines
2.0 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Number of detected faces: 1\n",
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"face0.jpg is saved\n"
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]
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}
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],
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"source": [
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"# import required libraries\n",
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"import cv2\n",
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"\n",
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"# read the input image\n",
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"img = cv2.imread('data/UAM-Andrzej-Wójtowicz.jpg')\n",
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"\n",
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"# convert to grayscale of each frames\n",
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"gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
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"\n",
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"# read the haarcascade to detect the faces in an image\n",
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"face_cascade = cv2.CascadeClassifier('haarcascades/haarcascade_frontalface_default.xml')\n",
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"\n",
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"# detects faces in the input image\n",
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"faces = face_cascade.detectMultiScale(gray, 1.3, 4)\n",
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"print('Number of detected faces:', len(faces))\n",
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"\n",
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"# loop over all detected faces\n",
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"if len(faces) > 0:\n",
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" for i, (x, y, w, h) in enumerate(faces):\n",
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" # To draw a rectangle in a face\n",
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" cv2.rectangle(img, (x, y), (x + w, y + h), (255, 255, 255), 2)\n",
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" face = img[y:y + h, x:x + w]\n",
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" cv2.imshow(\"Cropped Face\", face)\n",
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" cv2.imwrite(f'face{i}.jpg', face)\n",
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" print(f\"face{i}.jpg is saved\")\n",
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" \n",
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"# display the image with detected faces\n",
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"cv2.imshow(\"image\", img)"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3.10.8 64-bit",
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"language": "python",
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"name": "python3"
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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": "3.10.8"
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},
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "767d51c1340bd893661ea55ea3124f6de3c7a262a8b4abca0554b478b1e2ff90"
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}
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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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