Sun Weiran ianforme

ianforme / main-function-cv2.py

Created December 31, 2020 09:13

	# Get a reference to webcam
	video_capture = cv2.VideoCapture(0)

	emotion_dict = {
	0: 'Surprise',
	1: 'Happy',
	2: 'Disgust',
	3: 'Anger',
	4: 'Sadness',
	5: 'Fear',

ianforme / emotion-model.py

Created December 31, 2020 08:36

	input = Input(shape=(48, 48, 1))
	cnn1 = Conv2D(36, kernel_size=3, activation='relu')(input)
	cnn1 = MaxPool2D(pool_size=3, strides=2)(cnn1)
	cnn2 = Conv2D(64, kernel_size=3, activation='relu')(cnn1)
	cnn2 = MaxPool2D(pool_size=3, strides=2)(cnn2)
	cnn3 = Conv2D(128, kernel_size=3, activation='relu')(cnn2)
	cnn3 = MaxPool2D(pool_size=3, strides=2)(cnn3)
	dense = Flatten()(cnn3)
	dense = Dropout(0.3)(dense)
	dense = Dense(256, activation='relu')(dense)

ianforme / gender-model.py

Created December 31, 2020 08:35

	input = Input(shape=(224, 224, 3))
	cnn1 = Conv2D(36, kernel_size=3, activation='relu')(input)
	cnn1 = MaxPool2D(pool_size=3, strides=2)(cnn1)
	cnn2 = Conv2D(64, kernel_size=3, activation='relu')(cnn1)
	cnn2 = MaxPool2D(pool_size=3, strides=2)(cnn2)
	cnn3 = Conv2D(128, kernel_size=3, activation='relu')(cnn2)
	cnn3 = MaxPool2D(pool_size=3, strides=2)(cnn3)
	cnn4 = Conv2D(256, kernel_size=3, activation='relu')(cnn3)
	cnn4 = MaxPool2D(pool_size=3, strides=2)(cnn4)
	cnn5 = Conv2D(512, kernel_size=3, activation='relu')(cnn4)

ianforme / age-model.py

Created December 31, 2020 08:31

	input = Input(shape=(224, 224, 3))

	cnn1 = Conv2D(128, kernel_size=3, activation='relu')(input)
	cnn1 = Conv2D(128, kernel_size=3, activation='relu')(cnn1)
	cnn1 = Conv2D(128, kernel_size=3, activation='relu')(cnn1)
	cnn1 = MaxPool2D(pool_size=3, strides=2)(cnn1)

	cnn2 = Conv2D(128, kernel_size=3, activation='relu')(cnn1)
	cnn2 = Conv2D(128, kernel_size=3, activation='relu')(cnn2)
	cnn2 = Conv2D(128, kernel_size=3, activation='relu')(cnn2)

ianforme / kmeans-image.py

Created November 29, 2020 13:52

Use clustering algorithms to generate photo filter

	from sklearn.cluster import KMeans, AgglomerativeClustering, DBSCAN, Birch
	from sklearn.mixture import GaussianMixture
	from PIL import Image
	import numpy as np
	import pandas as pd
	import matplotlib.pyplot as plt

	# load picture
	img = Image.open('./thor4.jpg')
	arr = np.array(img)

ianforme / dbdt-lr-example.ipynb

Created November 6, 2019 05:21

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ianforme / xpath_tutorial.html

Last active June 5, 2019 09:16

	<div class='team-stats'>
	<div class='points-per-game'>
	<table class='category-table'>
	<tr>
	<a class='team-name'>Golden State Warriors</a>
	<a class='team-value'>116.3</a>
	</tr>
	<tr>
	<a class='team-name'>LA Clippers</a>
	<a class='team-value'>114.7</a>