Fernando Marcos Wittmann WittmannF

Face Recognition in Python with the OpenCV Library

In this post we will use the OpenCV library for facial recognition. Here is an example using my webcam as an input:

The best part is that it can be done using less than 20 lines of code:

	from sklearn.datasets import make_regression
	from sklearn.metrics import r2_score
	import matplotlib.pyplot as plt
	#%matplotlib inline

	# Generate toy data
	X, y, w_true = make_regression(n_samples=20, n_features=1, random_state=0, noise=1.0, coef=True)
	w_bad = 0.5*w_true
	w_verybad = -0.3*w_true

	import matplotlib.pyplot as plt
	import keras.backend as K
	from keras.callbacks import Callback


	class LRFinder(Callback):

	'''
	A simple callback for finding the optimal learning rate range for your model + dataset.

	from keras.callbacks import Callback
	import keras.backend as K
	import numpy as np
	import matplotlib.pyplot as plt

	class LRFinder(Callback):
	"""
	Up-to date version: https://github.com/WittmannF/LRFinder
	Example of usage:
	from keras.models import Sequential

	from selenium import webdriver
	from PIL import Image
	from io import BytesIO

	def take_screenshot(element, driver, filename='screenshot.png'):
	"""
	Source: https://stackoverflow.com/questions/15018372/how-to-take-partial-screenshot-with-selenium-webdriver-in-python
	"""
	location = element.location_once_scrolled_into_view
	size = element.size

	## Imports
	from ashrae_utils import reduce_mem_usage, CyclicLR, LRFinder
	import numpy as np # linear algebra
	import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)
	import math
	import tqdm
	import gc
	from sklearn.linear_model import RidgeCV
	import seaborn as sns