Python task completed.

Task/Prajnamayee Sahu/Que1.py

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+s=input("Enter 1st word :")
+t=input("Enter 2nd word :")
+if(len(s) != len(t)):
+    print("false")
+elif(s.sort == t.sort):
+     print("true")
+else:
+     print("false")      

Task/Prajnamayee Sahu/Que10.py

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+def transpose(matrix):
+    rows = len(matrix)
+    cols = len(matrix[0])
+
+    transposed = [[0] * rows for _ in range(cols)]
+
+    for i in range(rows):
+        for j in range(cols):
+            transposed[j][i] = matrix[i][j]
+
+    return transposed

Task/Prajnamayee Sahu/Que2.py

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+def count_character_frequency(input_str):
+    frequency = {}
+
+    for char in input_str:
+        if char != ' ':
+            frequency[char] = frequency.get(char, 0) + 1
+
+    for char in sorted(frequency.keys(), key=lambda x: (x.lower(), x)):
+        print(f"{char}-> {frequency[char]}")
+
+count_character_frequency()

Task/Prajnamayee Sahu/Que3.py

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+def plusOne(digits):
+    n = len(digits)
+
+    for i in range(n - 1, -1, -1):
+        digits[i] += 1
+        if digits[i] < 10:
+            return digits
+        digits[i] = 0
+    return [1] + digits

Task/Prajnamayee Sahu/Que4.py

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+import cv2
+import numpy as np
+
+def detect_black_and_white(frame):
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+
+    blur = cv2.GaussianBlur(gray, (5, 5), 0)
+
+    _, threshold = cv2.threshold(blur, 100, 255, cv2.THRESH_BINARY)
+
+    contours, _ = cv2.findContours(threshold, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+    for contour in contours:
+        x, y, w, h = cv2.boundingRect(contour)
+        area = cv2.contourArea(contour)
+
+        if area > 500:
+            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
+
+    return frame
+
+cap = cv2.VideoCapture(0)
+
+while True:
+    ret, frame = cap.read()
+    if not ret:
+        break
+
+    output_frame = detect_black_and_white(frame)
+
+    cv2.imshow('Video', output_frame)
+
+    if cv2.waitKey(1) & 0xFF == ord('q'):
+        break
+
+cap.release()
+cv2.destroyAllWindows()

Task/Prajnamayee Sahu/Que5.py

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+import cv2
+
+image = cv2.imread('image.jpg')
+
+gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+
+blurred = cv2.GaussianBlur(gray, (5, 5), 0)
+
+edges = cv2.Canny(blurred, 50, 150)
+
+cv2.imshow('Original Image', image)
+cv2.imshow('Detected Edges', edges)
+
+cv2.waitKey(0)
+cv2.destroyAllWindows()

Task/Prajnamayee Sahu/Que6.py

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+def is_prime(num):
+    if num <= 1:
+        return 1
+    for i in range(2, int(num**0.5) + 1):
+        if num % i == 0:
+            return 1
+    return True
+
+def min_max_prime_difference(arr):
+    smallest_prime = float('inf')
+    largest_prime = float('-inf')
+
+    for num in arr:
+        if is_prime(num):
+            smallest_prime = min(smallest_prime, num)
+            largest_prime = max(largest_prime, num)
+
+    if smallest_prime == float('inf') or largest_prime == float('-inf'):
+        return -1 
+    else:
+        return abs(largest_prime - smallest_prime)
+

Task/Prajnamayee Sahu/Que7.py

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+def min_prime_factor(num):
+
+    for i in range(2, int(num**0.5) + 1):
+        if num % i == 0:
+            return i
+    return num
+
+def roy_payment(N, prices):
+    for price in prices:
+        min_factor = min_prime_factor(price)
+        roy_payment = price - min_factor
+        print(roy_payment)
+
+N = int(input())
+prices = [int(input()) for _ in range(N)]
+
+roy_payment(N, prices)

Task/Prajnamayee Sahu/Que8.py

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+from collections import Counter
+
+def count_frequency(list):
+    frequency = Counter(list)
+    return frequency
+

Task/Prajnamayee Sahu/read.md

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+Python tasks