/R16 9.9626 Tf /Font 58 0 R students class pytorch classification face-detection hci head head-detection headpose head-detect yolov5.
The entire script has two sections: for training and for testing . 6 0 obj [ (Human) -304.008 (pose) -304.015 (estimation) -304.018 (is) -302.994 (the) -303.979 (process) -304.018 (of) -303.988 (detecting) -304.003 (k) 10.0032 (e) 15.0122 (y\055) ] TJ /Contents 81 0 R [ (gi) 24.9885 (v) 14.9828 (en) -368.017 (limited) -368.015 (computational) -368.002 (resources\056) -664.982 (Our) -368.012 (contrib) 20.0163 (utions) ] TJ Face Detection detects multiple faces within an image along with the associated key facial attributes such as emotional state or wearing headwear . Found inside – Page 123Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow Matthew Rever ... Note the following code: print("Detection {}: Left: {} Top:{} Right: {} Bottom: {}".format( k, d.left(), d.top(), d.right(), ... Found inside – Page 74Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Conf. Comp. Vis. and Patt. Recogn., vol. 1, pp. 886–893 (2005) 3. Fanelli, G., Gall, J., Van Gool, L.: Real time head pose estimation with random ... 1 1 1 rg This software is used to detect and count people in the premises. [ (sion) -322.982 (with) -322.003 (se) 25.0173 (v) 14.9828 (eral) -323.01 (applications) -321.983 (ranging) -322.985 (from) -322.015 (pedestrian) -322.985 (de\055) ] TJ << Popular method of conve… [ (estimation) -259.006 (is) -259.003 (used) -259.984 (in) -259.003 (applications) -259.011 (relating) -258.996 (to) -259.986 (ac) 1.00964 (ti) 24.9909 (vity) -260.011 (recog\055) ] TJ A related problem is Head Pose Estimation where we use the facial landmarks to obtain the 3D orientation of a human head with respect to the camera. >> YOLO (You Only Look Once) is a real-time object detection algorithm that is a single deep convolutional neural network that splits the input image into a set of grid cells, so unlike image . -11.9551 -11.9551 Td Found inside – Page 667In: Proceedings of the Python for scientific computing conference (SciPy), vol. 4, p. 3 (2010) 4. ... 3253–3261 (2015) Vu, T.H., Osokin, A., Laptev, I.: Context-aware CNNs for person head detection. In: Proceedings of the IEEE ... /Count 9 In this article, we will focus on human pose estimation, where it is required to detect and localize the major parts/joints of the body ( e.g. [ (that) -352.005 (are) -351.993 (fully) -351.017 (or) -352.017 (partially) -351.995 (occluded\056) -615.02 (This) -351.995 (is) -352.005 (specially) ] TJ /a0 gs The framework for this code came from here. You can now use the information on the entities tagged for further analysis. /R10 9.9626 Tf Input: Output: True. /Type /Page /Resources << In Jetson Xavier Nx, it can achieve 33 FPS. RichardoMrMu / class_yolov5_head. Face detection is a computer vision technology that helps to locate/visualize human faces in digital images. /Rotate 0 Face Detection using OpenCV in Python Performing face detection using both Haar Cascades and Single Shot MultiBox Detector methods with OpenCV's dnn module in Python. stream The code is a demo for Object detection which on execution will use the specified 'ssd_mobilenet_v1_coco_2017_11_17' model to classify two test . /ExtGState << The first book of its kind dedicated to the challenge of person re-identification, this text provides an in-depth, multidisciplinary discussion of recent developments and state-of-the-art methods. /ExtGState 39 0 R 48.406 3.066 515.188 33.723 re /ProcSet [ /PDF /Text ] /R10 9.9626 Tf T* Fig. /R8 11.9552 Tf 9.96211 0 Td T* [ (gestion) -359.987 (analysis) -359.99 (in) -360.986 (surv) 14.9901 (eillance) -360.01 (videos\056) -639.984 (There) -361.001 (are) -359.991 (se) 25.0179 (v) 14.9828 (eral) ] TJ /Contents 69 0 R /R14 24 0 R Star 2. When the Python program detects any motion, it will draw a blue rectangle around the moving object. Question: How to do head detection (not face detection) using OpenCV - For example in a photo of inside a bus or a room? endobj To use this live, I made the following changes to screener(): Finding the right params for your pattern to play out may take experimentation. 87.273 24.305 l /ExtGState 70 0 R /Resources << /R8 14.3462 Tf faces_detected = face_haar_cascade.detectMultiScale(gray_img, #cropping region of interest i.e. 11.9559 TL This is used to reduce the dimension of the input image. How to do Real-time Mask detection . And later on we will think about the solution to track the movement.
[ (fast) -234.994 (and) -233.985 (accur) 14.9852 (ate) -235.012 (ima) 10.013 (g) 10.0032 (e) -234.985 (pr) 44.9839 (ocessing) -234.014 (algorithm) -235.007 (that) -234.995 (oper) 14.9901 (ates) ] TJ You can get VisDrone-DET2021: The Vision Meets Drone Object Detection Challenge Results for more information. [ (box) 14.9926 (es) -253.014 (of) -253.994 (humans) -252.987 (in) -253.985 (an) -253.017 (image) -253.982 (as) -253.017 (head) -253.997 (detection) -252.992 (is) -253.982 (suf) 24.986 <026369656e74> ] TJ For the extremely popular tasks, these already exist. T* endobj /Resources 15 0 R /ProcSet [ /PDF /Text ] 201.454 -17.9332 Td /Resources << endobj The objective of this post is to demonstrate how to detect and count faces in an image, using OpenCV and Python. << /XObject 55 0 R
/Resources << T* Eye. 71.164 13.051 73.895 10.082 77.262 10.082 c T* Note: I do not want to do face detection; just head detection to figure out number of people in the photo. /Parent 1 0 R We'll do face and eye detection to start. Head (Dense Prediction) — used in one-stage-detection algorithms such as YOLO, SSD, etc. [ (can) -250 (be) -249.997 (summarized) -250.005 (as) -249.995 (follo) 24.9958 (ws\072) ] TJ /Resources << /R10 9.9626 Tf Found inside – Page 492... in Python interfaced with Visual Studio Code (1.55.2) 64-bit (win 64) using the python library for face-detection using ... Video-frames were analyzed to derive different head-motions: head-shake-left and head-shake-right (rotation ... Found inside – Page 101Cat Head Detection - How to Effectively Exploit Shape and Texture Features, Proc. of European Conf. ... Fish License sketch, Monty Python's Flying Circus, Episode 23 (1970) This segment of the project uses tens of thousands of files, ... In this simple example, we will use a Haar feature-based cascade classifier for the face detection. T* As in most modern face detectors, we also apply a cascaded classifier for detecting faces. Q 79.777 22.742 l stream All you need to write your own people head detector from the youtube video. -83.9281 -24.9223 Td Found inside – Page 85CNN Implementation for Semantic Heads Segmentation Using Top-View Depth Data in Crowded Environment Rocco Pietrini(B), ... The aforementioned networks have their stand-alone Python script implementation for training and testing. /I true Ever wondered how to programmatically define technical patterns in price data? It is a two-level web-service with client and server modules. Our params (smoothing and window range) are too sensitive for this timeframe (60 minutes). /ProcSet [ /PDF /Text ] /Annots [ ] Found inside – Page 475Our current implementation (in Python) of the entire processing pipeline, including preprocessing (see Subsection 3.1), takes on average 1.1s per image. Table 2. Comparison to state of the art: Optic nerve head detection results (number ... T* head detection and precision of shoulders detection, with the biggest advantage of our models being in terms of com- . Face Detection using Python and Bob¶. Detection of these intrusions is a form of anomaly detection. Q The slow pointer moves one node ahead at a time, while the fast pointer moves two nodes ahead at a time. endobj /S /Transparency Issues. endobj In this article you saw in the field of edge detection, the Harris Corner Detection algorithm that is able to detect the corner within a picture. 67.215 22.738 71.715 27.625 77.262 27.625 c [ (par) -314.01 (with) -313.994 (the) -314.018 (state) -314.005 (of) -314.014 (the) -314.019 (art) -314.008 (in) -314.014 (terms) -314.008 (of) -314.014 (pr) 36.9865 (ecision\055r) 36.9987 (ecall) -314.016 (of) ] TJ >> 16 to 235 for Y, 16 to 240 for Cb and Cr. /MediaBox [ 0 0 612 792 ] The following tutorial will introduce you with the concept of object detection in python using OpenCV and how you can use if for the applications like face and eye recognition. Found inside – Page 164For implementation FilterPy, a Kalman filtering and optimal estimation library in Python is used. ... A live counter for the tracked head is updated based on whether a detection could be assigned to the tracker or not. [ (putation) -205.997 (time) 14.9901 (\056) -295.007 (W) 91.9859 (e) -204.99 (also) -205.982 (analyze) -205.985 (the) -205.017 (ef) 18 (fect) -206 (of) -205.012 (adding) -206.012 (the) -205.997 (depth) ] TJ [ (W) 79.9866 (e) -454.988 (propose) -455.003 (a) -454.988 (system) -454.988 (that) -455.007 (combines) -454.993 (traditional) -454.983 (im\055) ] TJ The code. [ (welahmar\100uottawa\056ca\054) -599.991 (fnowr010\100uottawa\056ca\054) -599.991 (laganier\100eecs\056uottawa\056ca) ] TJ 10 0 obj Changing the market one algorithm at a time. Leverage the power of Python to collect, process, and mine deep insights from social media dataAbout This Book* Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more* Analyze and extract ... Found inside – Page 1843.2 Pain Detector Based on Temperature This sensor emulates in a different way the way we feel articular pain. ... The Python implementation consists of a headCaresseDetector class that scans the head tactile sensors. [ (1\0562\056) -250.004 (Contrib) 19.9854 (ution) ] TJ T* Technology and services are offered by AlpacaDB, Inc. T* Face Detection using Haar Cascades. 109.984 9.465 l 9.96211 0 Td Intrusion detection systems - In the field of computer science, unusual network traffic, abnormal user actions are common forms of intrusions. Feature Extractors Now that our model is trained, we can modify the code in the first section so that it can detect faces and also tell us if the person is wearing a mask or not. In this OpenCV with Python tutorial, we're going to discuss object detection with Haar Cascades. Q /R16 9.9626 Tf python file.py -v C:\run.mp4. But in Linked List containing a loop, the last node of the Linked List points to some . . f
Open source computer vision library is an open source computer vision and machine learning library. We will use Python to implement Object Detection in a simple demo using the Tensorflow code. Python being a very powerful programming languages and one of the programming languages that are being used all over the world has proven to give best results in the face recognition and detection systems. T* Matplotlib. This chapter focuses on using unsupervised learning techniques to detect fraud. These intrusions are capable enough to breach many confidential aspects of an organization. h you need to detect the faces, to know more about detecting faces using python, you can refer to my article by clicking. It was built with a vision to provide basic infrastructure to . /Pages 1 0 R def screener(stock_data, ema_list, window_list): stocklist = ['AA', 'AAL', 'AAPL', 'AMZN'] # Long list of stocks here, stock_data = get_stock_data(stocklist, 2), resampled_stock_data = resample(stock_data, '360T'), results = screener(resampled_stock_data, ema_list, window_list), PySpark Learning Journal 01: 01.03.2021 SUN — Loading CSV From URL, How to survive as a Roman Emperor in 6 Visualizations, «Monthly Report» The Change of AIDUS QTS Profit Rate (February 28, 2021), Data Storytelling — Basic Data Visualization in Excel. We will be using a Holistic model from mediapipe solutions to detect all the face and hand landmarks. In this package, we provide a pre-trained classifier for upright frontal faces, but the cascade can be re-trained using own data. /ExtGState 82 0 R All contents are copyright of their authors. Found inside – Page 32Comparison of Spent - Fuel Assembly Control Devices : The Cadarache Python and LANL's Fork , G. Bignan ( CEA / CEN ... The two detection heads of the Python detector are shown from the side , with the inner components indicated on the ... Code example and cascade description. /CA 0.5 >> 12 0 obj T* You should have basic OpenCV and C/C++ programming experience before reading this book, as it is aimed at Computer Science graduates, researchers, and computer vision experts widening their expertise. /ProcSet [ /PDF /Text ] T* /Group 52 0 R Before moving to the next part, make sure to download the above model from this link and place it in the same folder as the python script you are going to write the below code in. >> << 9.96211 0 Td 0 g [ (body) -300.989 (such) -300.996 (as) -301.006 (the) -299.982 (shoulders\054) -313.992 (elbo) 24.9909 (ws\054) -314.016 (hips\054) -312.982 (and) -301.004 (knees\056) -463.011 (Pose) ] TJ You can use the trained dataset to detect the emotion of the human being. [ (point) -401.982 (locations) -400.997 (that) -401.997 <6465026e65> -401.997 (important) -402.011 (joints) -400.992 (of) -402.011 (the) -402.002 (human) ] TJ /XObject 83 0 R Make the following changes if you're using any other Python version: In model.py, change xrange in line 18 to range. 5 0 obj >> �WL�>���Y���w,Q�[��j��7&��i8�@�. T* [ (fer) 36.9834 (ent) -382.987 (ar) 36.9852 (c) 15.0128 (hitectur) 37.0036 (es) -382.013 (of) -382.983 (our) -383.018 (model) -383.018 (ar) 36.9852 (e) -383 (discussed\056) -708.004 (W) 91.9871 (e) -383 (also) ] TJ /Kids [ 3 0 R 4 0 R 5 0 R 6 0 R 7 0 R 8 0 R 9 0 R 10 0 R 11 0 R ] You initialize your code with the cascade you want, and then it does the work for you. /Resources << nally, we use Cython [2] to create a bridge between Python and C to remove the overhead caused by the dynamic bind-ing in Python. Fortunately, Python offers a number of easy-to-use packages for carrying this analysis out. The First 7 Rows Of Data. Get access . Let's move on to the Python implementation of the live facial detection. /R12 8.9664 Tf Real time face detection. 91.531 15.016 l /ca 0.5
/a1 << This is just a beginning step in face detection. /ExtGState 88 0 R In order to do object recognition/detection with cascade files, you first need cascade files. [ (pr) 44.9839 (opose) -255 (thr) 36.9926 (ee) -254.005 (dif) 18.0166 (fer) 36.9828 (ent) -255.009 (models) -254.014 (based) -255 (on) -253.987 (con) 39.9982 (volutional) -255.006 (neu\055) ] TJ Output: False. >> endobj One of the most popular technique for edge detection has been Canny Edge detection which has been the go-to method for most of the computer vision researchers and . Found inside – Page 358Intelligent algorithms for building image processing apps using OpenCV 4, Python, and scikit-learn, ... takes in video as input and performs face detection coupled with age, gender, head-pose, emotion, and facial landmark detection. T* /ProcSet [ /PDF /ImageC /Text ] To do this, open the .json file and replace the current location with the location where your images are located. 11 0 obj head nod detection. >> [ (nation) -291.015 (of) -290.018 (ima) 10.013 (g) 10.0032 (e) -291.015 (pr) 44.9839 (ocessing) -290.985 (and) -290.015 (deep) -291.009 (learning) -291.013 (appr) 44.9949 (oac) 14.9828 (hes\056) ] TJ
You can download the data set by clicking here. Detection of these intrusions is a form of anomaly detection. Detect faces. Hello and welcome to this Kaggle tutorial on how to build a model for face mask detection using Python and Machine Learning. . /Font << /Type /Page
LBP cascade free to download to use in opencv to detect people and heads. T* We can develop a machine learning model in python which can detect whether the news is fake or not. /Parent 1 0 R . >> /ExtGState 63 0 R Let's now write the code of the first part, where we import the video where the eye is moving. This book and its sister volumes, i.e. Found inside – Page 100During the training stage, we assign a position q on a detection layer fi (i = 0,1,2,3,4) to an object, if 1) q falls in ... All the head depth of the detection heads is two. ... We implement our framework using Python and PyTorch [32]. it easy for you to start programming your own Machine Learning model even if you don't have the programming language Python installed on your computer. [ (Department) -250 (of) -250.015 (Electrical) -250.004 (Engineering) -249.997 (and) -249.987 (Computer) -250.014 (Science\054) -249.993 (Uni) 24.9957 (v) 14.9851 (ersity) -249.989 (of) -250.014 (Otta) 15.0096 (w) 9.99826 (a) ] TJ We import the libraries Opencv and numpy, we load the video "eye_recording.flv" and then we put it in a loop so tha we can loop through the frames of the video and process . [ (the) -247.99 (big) 10.0155 (g) 10.0032 (est) -247.989 (advanta) 9.9873 (g) 10.0032 (e) -246.983 (of) -247.986 (our) -247.982 (models) -248.015 (being) -247 (in) -247.986 (terms) -248.02 (of) -247.986 (com\055) ] TJ import cv2. Detecting things like faces, cars, smiles, eyes, and license plates for example… Robinhood Menlo Park, CA 2 weeks ago Be among the first 25 applicants See who Robinhood has hired for this role . Disclaimer: this code is intended as a starting point for finding technical patterns, it is for educational purposes only. For detecting the emotion, first, you need to run the train.py program to train the data. A Python implementation of Yolov5 to detect head or helmet in the wild in Jetson Xavier nx and Jetson nano. T* [ (humans) -319.996 (in) -320.993 (videos) -320 (is) -320.012 (a) -321.01 (prominent) -319.986 (challenge) -320.013 (in) -320.013 (machine) -320.988 (vi\055) ] TJ 3 0 obj 8. Python, trading, data viz. Since face detection is such a common case, OpenCV comes with a number of built-in cascades for detecting everything from faces to eyes to hands to legs. In this tutorial, we will implement facial expression detection using machine learning in Python. Also Spyder terminal, Jupyter Notebook or Pycharm Editor recommended. /CA 1 Heart Disease Detection Using Machine Learning & Python. 139.211 -13.948 Td /ProcSet [ /PDF /ImageC /Text ] Thanks to the OpenCV library, all this analysis can be invoked through the use of a single cv2.cornerHarris() function, making the work much easier to carry out analysis of images at a higher level with Python. [ (Deep) -238 (learning) -237.982 (has) -239.012 (dominated) -238 (the) -237.992 <02656c64> -238.017 (of) -239.016 (machi) 0.99493 (ne) -239.019 (vision) ] TJ [ (tection) -234.017 (in) -235.007 (autonomous) -233.988 (dri) 24.9848 (ving) -234.998 (systems\054) -237.017 (to) -235.007 (security) -233.981 (and) -235.015 (con\055) ] TJ /Filter /FlateDecode /BBox [ 0 0 612 792 ] << 11.9551 TL "This book provides a working guide to the C++ Open Source Computer Vision Library (OpenCV) version 3.x and gives a general background on the field of computer vision sufficient to help readers use OpenCV effectively."--Preface. . >> Later we’ll resample to our timeframe of choice. Learn more about bidirectional Unicode characters. /Parent 1 0 R >> T* /R8 11.9552 Tf Your camera automatically turns on and detects the emotion of your face. h df.head(7) #Print the first 7 rows. /R16 28 0 R #Get the shape of the data . Code. /MediaBox [ 0 0 612 792 ] The detection of emotion is made by using the machine learning concept. Found inside – Page 1082, has been created using the Qt libraries 4 and Python programming language. It has been divided into four vertical sections: 1. Input Visualization, 2. Head Detection, 3. Head Pose Estimation and Facial ... In order to find the best params, I reorganized my code into functions and iterated through multiple stocks, smoothing, and window parameters. /Rotate 0 Luckily, this problem can be addressed using machine learning. [ (such) -249.985 (systems\056) ] TJ h Comments (6) Run. /ExtGState 54 0 R [ (F) 24.9889 (ast) -249.998 (Human) -249.99 (Head) -250 (and) -249.991 (Shoulder) -250.007 (Detection) -250.003 (Using) -249.991 (Con) 40.0071 (v) 9.99625 (olutional) -249.995 (Netw) 9.99285 (orks) -250.015 (and) ] TJ
A quick read-through of that article will be great to understand the intrinsic working and hence I will write about it only in brief here. Input: 1→ 2→ 3→ NULL. ; Sparse Prediction — used in two-stage-detection algorithms such as Faster-R-CNN, etc. 87.273 33.801 l -11.9547 -11.9547 Td Python, trading, data viz. This Notebook has been released under the Apache 2.0 open source license. /R12 21 0 R endobj T* Pull requests. 11.9547 -11.9559 Td 100.875 18.547 l BT [ (c) 15.0128 (hannel) -250.014 (on) -249.988 (the) -249.99 (performance) -250.007 (of) -249.985 (the) -249.99 (network\056) ] TJ cv2.putText(test_img, predicted_emotion, (int(x), int(y)), cv2.FONT_HERSHEY_SIMPLEX, The Best VS Code Extensions For Remote Working, How To Post Data In ASP.NET Core Using Ajax, Top 15 Git Commands With Examples For Every Developers. Found inside – Page 181... of the current frame (stored in self.head by _process_frame), and align it with all the other collected frames. ... set" self.samples.append(head.flatten()) self.labels.append(label) else: print "Could not align head (eye detection ... Edge detection is a very old problem in computer vision which involves detecting the edges in an image to determine object boundary and thus separate the object of interest. T* 105.816 14.996 l In this tutorial, you're going to build an SMS spam detection web application. '�K����]G�«��Z��xO#q*���k. [ (1\056) -249.99 (Intr) 18.0146 (oduction) ] TJ Opencv Python Hand Detection and Tracking: Aim of the project is to move a robotic hand, mimicking humand hand based on a camera feed.The project is divided intoSoftware (i'm using opencv to detect human hand and find the distance between palm center and finger tips. 6 min read. Let’s plot it with the resampled price data to visually confirm we’re on the right track. 78.598 10.082 79.828 10.555 80.832 11.348 c We will use Python to implement Object Detection in a simple demo using the Tensorflow code. 9 0 obj You can install the dependencies by using the commands given below: For training purposes, I use the predefined un trained dataset CSV file as my main input for my input for training the machine. [ (e) 25.0105 (v) 14.9828 (er) 39.986 (\054) -370.994 (generating) -346.984 (training) -345.991 (data) -346.996 (requires) -346.991 (manual) -347.021 (labour) ] TJ This is a great article on Learn OpenCV which explains head pose detection on images with a lot of Maths about converting the points to 3D space and using cv2.solvePnP to find rotational and translational vectors.
/R8 10.9589 Tf The machine learning algorithm used by me was a tensor flow algorithm, which was designed by Google for machine learning functions. 11.9551 TL [ (r) 14.984 (al) -267.002 (networks) -266 (for) -266.996 (this) -266.989 (pr) 44.9839 (oblem\056) -360 (Experimental) -265.997 (r) 37.0183 (esults) -266.987 (for) -266.997 (dif\055) ] TJ >> /ExtGState 79 0 R These are the OpenCV and the Numpy modules. [ (approaches) -388.008 (to) -388.982 (human) -387.99 (detection) -387.99 (depending) -389.004 (on) -388.004 (the) -388.006 (type) -388.982 (of) ] TJ -9.96211 -19.1609 Td /Type /Page Got it. [ (it) -374.001 (is) -374.004 (e) 15.0122 (xpected) -374.006 (to) -374.004 (be) -372.997 (in) -374.006 (predicting) -373.987 (test) -374.001 (images\056) -682.019 (Ho) 24.986 (w\055) ] TJ << T* This book focuses on leveraging mobile platforms to build interactive and useful applications. The book starts off with an introduction to OpenCV and Android and how they interact with each other using OpenCV's Java API. >> /Type /Page [ (liably) -385.987 (detect) -386.007 (humans) -385.985 (in) -386.002 (indoor) -385.99 (en) 39.9933 (vironments) -386.989 (in) -386.004 (real) -386.019 (time) ] TJ So make sure the image is in grayscale. The Object Detection opencv method we will use is a sweet balance betwe. Found inside – Page 674[7] shared various techniques that can be used for detecting drowsiness in their research. ... the yawn frequency, eye blinking frequency, eye gaze movement, head movement and facial expressions for detecting drowsiness of the drivers. For detecting the different emotions, first, you need to train those different emotions, or you can use a dataset already available on the internet. We'll do mouth detection to start. Get the number of rows and columns. /Title (Fast Human Head and Shoulder Detection Using Convolutional Networks and RGBD Data) This tutorial is a follow-up to Face Recognition in Python, so make sure you've gone through that first post.. As mentioned in the first post, it's quite easy to move from detecting faces in images to detecting them in video via a webcam - which is exactly what we will detail in this post. [ (data\056) -364.013 (The) -267.009 (more) -267.985 (e) 15.0122 (xamples) -268.009 (a) -268 (model) -268.009 (trains) -268.014 (on\054) -271.979 (the) -267.985 (better) ] TJ
/Font 89 0 R (application\056) ' 83.789 8.402 l /Font 86 0 R 2 0 obj >> /Contents 78 0 R
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