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Realtime FaceDetection using python
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Python How-To/FaceDetection001.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Face Detection\n",
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"**A real time application for face-detection.**\n",
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"A very simple appliation with 7 lines of code to create a face-detection application.\n",
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"\n",
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"Requires Python version 3.7 or above. Not tested with earlier versions.\n",
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"\n",
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"You will have to install the following modules if not already installed:\n",
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"* opencv-python\n",
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"* tflite for Python 3.7<br>\n",
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" TensorFlow Lite - Please [refer to this website](https://www.tensorflow.org/lite/guide/python) to download the appropriate version for your system, and then install it.\n",
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"* Xailient FaceSDK<br>\n",
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" Please follow the instruction on this [website to install the Xailient FaceSDK](https://sdk.xailient.com).\n",
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" \n",
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" Originally published in www.xailient.com/blog."
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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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"import dnn\n",
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"import cv2 as cv"
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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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"myImage = cv.imread('image.jpg')\n",
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"_, bboxes = dnn.FaceDetector().process_frame(myImage, threshold=0.4)"
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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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"for i in bboxes: \n",
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" cv.rectangle(myImage, (i[0], i[1]), (i[2], i[3]), (0, 255, 0), 3)"
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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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"cv.imwrite('/image_output.jpg', myImage)"
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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",
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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": "3.7.0"
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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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