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Face recognition is used for to unlocking cell phones. And with recent advancements in deep learning,In this repository how to develop a face recognition system that can detect faces in images, identify the faces, and even modify faces with "digital makeup" like you've experienced in popular mobile apps

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Face-Recognition-Deep-Learning

Face recognition is used for to unlocking cell phones. And with recent advancements in deep learning,In this repository how to develop a face recognition system that can detect faces in images, identify the faces, and even modify faces with "digital makeup" like you've experienced in popular mobile apps

Part 01 - Face Recognition Pipeline Steps

Step 1: Locate and extract faces from each image Step 2: Identify facial features in each image Step 3: Align faces to match pose template Step 4: Encode faces using a trained neural network Step 5: Check Euclidean distance between face encodings

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Use of face recognition

  1. Identify verification’
  2. Automatically organizing new photo libraries by person.
  3. Tracking a specific person
  4. Counting unique people
  5. Finding people with similar appearances.

Install libaries

pip install pillow 
pip install face-recognition

if you are using google Co-lab set to Run time to GUP

Part 02 - Face Recognition

Sliding window classifier

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Histogram of Oriented Gradients (HOG)

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Analyzing an Image as a Histogram of Oriented Gradients

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face land mark estimation

Identify key pint on the face – tip of the nose , center of the eye

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Identifying Face Landmarks with a Machine learning model

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Calculate affine Transform

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Finally -

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Part 03 - Representing a face as a set of Measurements

measure each eye, size of the cheekbones and the width of mouth and so on

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Here are two face , lets take three measurements for each face i. Length of nose – 2.5 (left) | 2 (right) ii. Width of mouth – 2.5 and 3 iii. Distance of one eye to other 4 and 3.5

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That distance is relay small or close each other(two point) that may be a same person.

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using face_encodings library - output 128 values

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Part 05 Euclidean distance

Face distance threshold – Set a face maximum distance that is still considered the same face . Lets assume the threshold value is 0.6.

  • If the distance (a,b) > 0.6, not , match
  • If the distance (a,b) =< 0.6, they match
  • he lower the distance , the better the match

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Part 6 - Fun Uses of face recognition

  • How to drawaing a image (makeup)
  • Choose best image from collection of images

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Face recognition is used for to unlocking cell phones. And with recent advancements in deep learning,In this repository how to develop a face recognition system that can detect faces in images, identify the faces, and even modify faces with "digital makeup" like you've experienced in popular mobile apps

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