KevinPatel04

MATLAB Cheatsheets for Image Processing

• Read Image File

  
  %%
  % replace `PATH_TO_IMAGE` with actual image file path
  %
 impath = 'PATH_TO_IMAGE';

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KevinPatel04

Creating Branch and Commit on GitHub using Vs Code

• Download Git on your PC from Here.
• Open the Terminal and follow the following steps:

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import argparse
import datetime
import imutils
import math
import cv2
import numpy as np

width = 800
textIn = 0
textOut = 0

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# import libraries here
import dlib
import face_recognition

# print the version of library
print(dlib.__version__)
print(face_recognition.__version__)

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# import required packages
import dlib
import cv2

# only for google colab
# from google.colab.patches import cv2_imshow

# load the image to be detected
image = cv2.imread('images/modi-obama-1.jpg')

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# import required packages
import dlib
import cv2

# only for google colab
# from google.colab.patches import cv2_imshow

# for using your inbuilt webcam
# Get the webcam #0 ( the default one, 1, 2 and so on)
# video_stream = cv2.VideoCapture(0)

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# load the image to be detected
image = cv2.imread('test/family.jpg')

# find all face locations using face_locations() function
# model can be "cnn" or "hog"
# number_of_times_to_upsample = 1 higher and detect more smaller faces from the image
all_face_locations = face_recognition.face_locations(image, model="hog")

#printing the number of faces in the array
print("There are {} face(s) in this image".format(len(all_face_locations)))

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•
├── test
│   ├── modi-obama-1.jpg
│   ├── modi-obama-2.jpg
│   └── face-demographics-walking.mp4
├── models
│   ├── facial_expression_model_weights.h5
│   └── facial_expression_model_structure.json
├── facial-expression-recognition-from-image.py

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# capture the video from default camera
# video_stream = cv2.VideoCapture(0)

# read video from video file
video_file_path = 'test/face-demographics-walking.mp4'
video_stream = cv2.VideoCapture(video_file_path)

# initialize the number of frame needed to be skipped
skip = 0