shashwatwork

# Build the recommendation model using ALS on the training data
als = ALS(maxIter=5, regParam=0.01, userCol="userId", itemCol="movieId", ratingCol="rating")
model = als.fit(training)

shashwatwork

import pandas as pd
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName('recnn').getOrCreate()
#Display the first Row of Dataframe
data.head()
data.describe().show()

shashwatwork

import pandas as pd
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName('recnn').getOrCreate()

shashwatwork

import numpy as np
import cv2 
import matplotlib.pyplot as plt
denis = cv2.imread('../DATA/Denis_Mukwege.jpg',0)
##OpenCV comes with these pre-trained cascade files
face_cascade = cv2.CascadeClassifier('../DATA/haarcascades/haarcascade_frontalface_default.xml')
def detect_face(img):
    
  
    face_img = img.copy()

shashwatwork

import cv2
import numpy as np
import matplotlib.pyplot as plt
img = cv2.imread('../DATA/internal_external.png',0)
image, contours, hierarchy = cv2.findContours(img, cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
# Draw External Contours

# Set up empty array
external_contours = np.zeros(image.shape)

shashwatwork

#import the required libraries
import numpy as np 
import cv2 
import matplotlib.pyplot as plt 
%matplotlib inline
def display_img(img):
    fig = plt.figure(figsize=(12,10))
    ax = fig.add_subplot(111)
    ax.imshow(img,cmap='gray')
#read the image

shashwatwork

import cv2
import numpy as np
import matplotlib.pyplot as plt
def load_img():
    img = cv2.imread('../DATA/bricks.jpg').astype(np.float32) / 255
    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    return img
  
  def display_img(img):
    fig = plt.figure(figsize=(12,10))

shashwatwork

import cv2
import numpy as np
import matplotlib.pyplot as plt
def load_img():
    img = cv2.imread('../DATA/bricks.jpg').astype(np.float32) / 255
    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    return img

def display_img(img):
    fig = plt.figure(figsize=(12,10))

shashwatwork

import cv2
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

#here 0 means that the image is loaded in gray scale format
gray_image = cv2.imread('../DATA/Nadia_Murad.jpg',0)

ret,thresh_binary = cv2.threshold(gray_image,127,255,cv2.THRESH_BINARY)
ret,thresh_binary_inv = cv2.threshold(gray_image,127,255,cv2.THRESH_BINARY_INV)

shashwatwork

import numpy as np
import cv2
import matplotlib.pyplot as plt

img1 = cv2.imread('../DATA/dog_backpack.png')
img1 = cv2.cvtColor(img1, cv2.COLOR_BGR2RGB)
plt.imshow(img1)
img1.shape
x_offset=934-600
y_offset=1401-600