[pull] master from avinashkranjan:master #26

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		# These are supported funding model platforms

	github: # Replace with up to 4 GitHub Sponsors-enabled usernames e.g., [user1, user2]
	github: avinashkranjan
		patreon: avinashkranjan
		open_collective: # Replace with a single Open Collective username
		ko_fi: avinashkranjan
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2 changes: 1 addition & 1 deletion Amazon-Price-Alert/requirements.txt

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Expand Up		@@ -6,7 +6,7 @@ chardet==3.0.4
		cssselect==1.1.0
		fake-useragent==0.1.11
		idna==2.10
	lxml==4.6.5
	lxml==4.9.1
		parse==1.18.0
		pyee==7.0.4
		pyppeteer==0.2.2
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2 changes: 1 addition & 1 deletion Calculate-distance/requirements.txt

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		geopy==2.1.0
		folium==0.12.1
		django-crispy-forms==1.11.0
	Django==2.2.28
	Django==3.2.15

10 changes: 10 additions & 0 deletions Connect 4 with Minimax Algorithm/READme.md

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	This is a single player connect 4 game which used [Minimax algorithm](https://en.wikipedia.org/wiki/Minimax).

	Dependancies:
	1. Pygame 2.1.2
	2. Numpy 1.23.1

	Game Rules:

	Four consecutive balls should match of the same colour horizontally, vertically or diagonally (either of both) just like tic-tac-toe.
	That's it now u r ready to play the game :)

287 changes: 287 additions & 0 deletions Connect 4 with Minimax Algorithm/connect4withMiniMax.py

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	import numpy as np
	import random
	import pygame
	import sys
	import math

	BLUE = (0,0,255)
	BLACK = (0,0,0)
	RED = (255,0,0)
	YELLOW = (255,255,0)

	ROW_COUNT = 6
	COLUMN_COUNT = 7

	PLAYER = 0
	AI = 1

	PLAYER_PIECE = 1
	AI_PIECE = 2

	def createBoard():
	board = np.zeros((ROW_COUNT,COLUMN_COUNT))
	return board

	def dropPiece(board, row, col, piece):
	board[row][col] = piece

	def isPlaceValid(board, col):
	return board[ROW_COUNT-1][col] == 0

	def GetNextRow(board, col):
	for r in range(ROW_COUNT):
	if board[r][col] == 0:
	return r

	def printBoard(board):
	print(np.flip(board, 0))

	def winningMove(board, piece):
	# Check horizontal locations for win
	for c in range(COLUMN_COUNT-3):
	for r in range(ROW_COUNT):
	if board[r][c] == piece and board[r][c+1] == piece and board[r][c+2] == piece and board[r][c+3] == piece:
	return True

	# Check vertical locations for win
	for c in range(COLUMN_COUNT):
	for r in range(ROW_COUNT-3):
	if board[r][c] == piece and board[r+1][c] == piece and board[r+2][c] == piece and board[r+3][c] == piece:
	return True

	# Check positively sloped diaganols
	for c in range(COLUMN_COUNT-3):
	for r in range(ROW_COUNT-3):
	if board[r][c] == piece and board[r+1][c+1] == piece and board[r+2][c+2] == piece and board[r+3][c+3] == piece:
	return True

	# Check negatively sloped diaganols
	for c in range(COLUMN_COUNT-3):
	for r in range(3, ROW_COUNT):
	if board[r][c] == piece and board[r-1][c+1] == piece and board[r-2][c+2] == piece and board[r-3][c+3] == piece:
	return True

	def scoringScorePosition(selectedGroup, piece):
	score = 0
	opp_piece = PLAYER_PIECE
	if piece == PLAYER_PIECE:
	opp_piece = AI_PIECE

	if selectedGroup.count(piece) == 4:
	score += 100
	elif selectedGroup.count(piece) == 3 and selectedGroup.count(0) == 1:
	score += 5
	elif selectedGroup.count(piece) == 2 and selectedGroup.count(0) == 2:
	score += 2

	if selectedGroup.count(opp_piece) == 3 and selectedGroup.count(0) == 1:
	score -= 4

	return score

	def scorePosition(board, piece):
	score = 0

	## Score center column
	center_array = [int(i) for i in list(board[:, COLUMN_COUNT//2])]
	center_count = center_array.count(piece)
	score += center_count * 3

	## Score Horizontal
	for r in range(ROW_COUNT):
	row_array = [int(i) for i in list(board[r,:])]
	for c in range(COLUMN_COUNT-3):
	selectedGroup = row_array[c:c+4]
	score += scoringScorePosition(selectedGroup, piece)

	## Score Vertical
	for c in range(COLUMN_COUNT):
	col_array = [int(i) for i in list(board[:,c])]
	for r in range(ROW_COUNT-3):
	selectedGroup = col_array[r:r+4]
	score += scoringScorePosition(selectedGroup, piece)

	## Score posiive sloped diagonal
	for r in range(ROW_COUNT-3):
	for c in range(COLUMN_COUNT-3):
	selectedGroup = [board[r+i][c+i] for i in range(4)]
	score += scoringScorePosition(selectedGroup, piece)

	for r in range(ROW_COUNT-3):
	for c in range(COLUMN_COUNT-3):
	selectedGroup = [board[r+3-i][c+i] for i in range(4)]
	score += scoringScorePosition(selectedGroup, piece)

	return score

	def isTerminalNode(board):
	return winningMove(board, PLAYER_PIECE) or winningMove(board, AI_PIECE) or len(getValidLocations(board)) == 0

	def minimax(board, depth, alpha, beta, maximizingPlayer):
	validLocations = getValidLocations(board)
	isTerminal = isTerminalNode(board)
	if depth == 0 or isTerminal:
	if isTerminal:
	if winningMove(board, AI_PIECE):
	return (None, 100000000000000)
	elif winningMove(board, PLAYER_PIECE):
	return (None, -10000000000000)
	else: # Game is over, no more valid moves
	return (None, 0)
	else: # Depth is zero
	return (None, scorePosition(board, AI_PIECE))
	if maximizingPlayer:
	value = -math.inf
	column = random.choice(validLocations)
	for col in validLocations:
	row = GetNextRow(board, col)
	b_copy = board.copy()
	dropPiece(b_copy, row, col, AI_PIECE)
	new_score = minimax(b_copy, depth-1, alpha, beta, False)[1]
	if new_score > value:
	value = new_score
	column = col
	alpha = max(alpha, value)
	if alpha >= beta:
	break
	return column, value

	else: # Minimizing player
	value = math.inf
	column = random.choice(validLocations)
	for col in validLocations:
	row = GetNextRow(board, col)
	b_copy = board.copy()
	dropPiece(b_copy, row, col, PLAYER_PIECE)
	new_score = minimax(b_copy, depth-1, alpha, beta, True)[1]
	if new_score < value:
	value = new_score
	column = col
	beta = min(beta, value)
	if alpha >= beta:
	break
	return column, value

	def getValidLocations(board):
	validLocations = []
	for col in range(COLUMN_COUNT):
	if isPlaceValid(board, col):
	validLocations.append(col)
	return validLocations

	def bestMoveForAI(board, piece):

	validLocations = getValidLocations(board)
	bestScore = -10000
	bestMove = random.choice(validLocations)
	for col in validLocations:
	row = GetNextRow(board, col)
	temp_board = board.copy()
	dropPiece(temp_board, row, col, piece)
	score = scorePosition(temp_board, piece)
	if score > bestScore:
	bestScore = score
	bestMove = col

	return bestMove

	def drawBoard(board):
	for c in range(COLUMN_COUNT):
	for r in range(ROW_COUNT):
	pygame.draw.rect(screen, BLUE, (cSQUARESIZE, rSQUARESIZE+SQUARESIZE, SQUARESIZE, SQUARESIZE))
	pygame.draw.circle(screen, BLACK, (int(cSQUARESIZE+SQUARESIZE/2), int(rSQUARESIZE+SQUARESIZE+SQUARESIZE/2)), RADIUS)

	for c in range(COLUMN_COUNT):
	for r in range(ROW_COUNT):
	if board[r][c] == PLAYER_PIECE:
	pygame.draw.circle(screen, RED, (int(cSQUARESIZE+SQUARESIZE/2), height-int(rSQUARESIZE+SQUARESIZE/2)), RADIUS)
	elif board[r][c] == AI_PIECE:
	pygame.draw.circle(screen, YELLOW, (int(cSQUARESIZE+SQUARESIZE/2), height-int(rSQUARESIZE+SQUARESIZE/2)), RADIUS)
	pygame.display.update()

	board = createBoard()
	printBoard(board)
	isGameOver = False

	pygame.init()

	SQUARESIZE = 100

	width = COLUMN_COUNT * SQUARESIZE
	height = (ROW_COUNT+1) * SQUARESIZE

	size = (width, height)

	RADIUS = int(SQUARESIZE/2 - 5)

	screen = pygame.display.set_mode(size)
	drawBoard(board)
	pygame.display.update()
	pygame.display.set_caption('Connect 4')
	myfont = pygame.font.SysFont("monospace", 75)

	turn = random.randint(PLAYER, AI)

	while not isGameOver:

	for event in pygame.event.get():
	if event.type == pygame.QUIT:
	sys.exit()

	if event.type == pygame.MOUSEMOTION:
	pygame.draw.rect(screen, BLACK, (0,0, width, SQUARESIZE))
	posx = event.pos[0]
	if turn == PLAYER:
	pygame.draw.circle(screen, RED, (posx, int(SQUARESIZE/2)), RADIUS)

	pygame.display.update()

	if event.type == pygame.MOUSEBUTTONDOWN:
	pygame.draw.rect(screen, BLACK, (0,0, width, SQUARESIZE))
	#print(event.pos)
	# Ask for Player 1 Input
	if turn == PLAYER:
	posx = event.pos[0]
	col = int(math.floor(posx/SQUARESIZE))

	if isPlaceValid(board, col):
	row = GetNextRow(board, col)
	dropPiece(board, row, col, PLAYER_PIECE)

	if winningMove(board, PLAYER_PIECE):
	label = myfont.render("Player 1 win!!", 1, RED)
	screen.blit(label, (40,10))
	isGameOver = True

	turn += 1
	turn = turn % 2

	printBoard(board)
	drawBoard(board)


	# # Ask for Player 2 Input
	if turn == AI and not isGameOver:

	#col = random.randint(0, COLUMN_COUNT-1)
	#col = bestMoveForAI(board, AI_PIECE)
	col, minimax_score = minimax(board, 5, -math.inf, math.inf, True)

	if isPlaceValid(board, col):
	#pygame.time.wait(500)
	row = GetNextRow(board, col)
	dropPiece(board, row, col, AI_PIECE)

	if winningMove(board, AI_PIECE):
	label = myfont.render("Player 2 wins!!", 1, YELLOW)
	screen.blit(label, (40,10))
	isGameOver = True

	printBoard(board)
	drawBoard(board)

	turn += 1
	turn = turn % 2

	if isGameOver:
	pygame.time.wait(5000)

2 changes: 2 additions & 0 deletions Connect 4 with Minimax Algorithm/requirements.txt

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	pygame == 2.1.2
	numpy = 1.23.1

1 change: 1 addition & 0 deletions Github_Bomb_Issues/requirements.txt

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Expand Up		@@ -2,3 +2,4 @@ PyGithub
		requests
		os
		getpass
	pyjwt>=2.4.0 # not directly required, pinned by Snyk to avoid a vulnerability

2 changes: 1 addition & 1 deletion Heart Disease Prediction/requirements.txt

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	numpy==1.18.5
	numpy==1.22.0
		pandas @ file:///C:/ci/pandas_1592833613419/work
		scikit-learn @ file:///C:/ci/scikit-learn_1592853510272/work

2 changes: 1 addition & 1 deletion Image Contrast Adjusting Filter/requirements.txt

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	numpy==1.22.0rc1
	numpy==1.22.0
		matplotlib==3.2.2
		Pillow==9.0.1

2 changes: 1 addition & 1 deletion Image_Background_Subtractor/requirements.txt

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	numpy==1.22.0rc1
	numpy==1.22.0
		opencv-python==4.5.1.48

2 changes: 1 addition & 1 deletion Internshala-Scraper/requirements.txt

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Expand Up		@@ -3,7 +3,7 @@ bs4==0.0.1
		certifi==2020年6月20日
		chardet==3.0.4
		idna==2.10
	lxml==4.6.5
	lxml==4.9.1
		requests==2.24.0
		soupsieve==2.0.1
		urllib3==1.25.10

2 changes: 1 addition & 1 deletion Neon Effect Filter/requirements.txt

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		@@ -1,3 +1,3 @@
	numpy==1.22.0rc1
	numpy==1.22.0
		opencv_python==4.5.1.48
		matplotlib==3.2.2

2 changes: 1 addition & 1 deletion Noise Reduction Script/requirements.txt

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		matplotlib==3.2.2
	numpy==1.22.0rc1
	numpy==1.22.0
		scipy==1.5.0

2 changes: 1 addition & 1 deletion PDF Watermark Remover/requirements.txt

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		scikit_image==0.18.1
		pdf2image==1.15.1
		fpdf==1.7.2
	numpy==1.22.0rc1
	numpy==1.22.0
		Pillow==9.0.1
		PyPDF2==1.27.5
		skimage==0.0

2 changes: 1 addition & 1 deletion PDFToWord/requirements.txt

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		fire==0.4.0
	lxml==4.6.5
	lxml==4.9.1
		pdf2docx==0.5.1
		PyMuPDF==1.18.12
		python-docx==0.8.10
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2 changes: 1 addition & 1 deletion Text_Summary/requirements.txt

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		nltk==3.6.6
	numpy==1.22.0rc1
	numpy==1.22.0
		networkx==2.5

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