Merge pull request #1357 from slowy07/slowy07-fixing

fixing baseException and reformatted code

Author: geekcomputers

Eight_Puzzle_Solver/eight_puzzle.py

@@ -1,9 +1,9 @@
-import sys
+# import sys
 from collections import deque
 from copy import deepcopy
 from queue import PriorityQueue
-import time
-from collections import Counter
+# import time
+# from collections import Counter
 
 class Node:
     def __init__(self,state,depth = 0,moves = None,optimizer=0):

Face and eye Recognition/face_recofnation_first.py

@@ -1,34 +1,37 @@
-## Name - Soumyajit Chakraborty 
+## Name - Soumyajit Chakraborty
 ## place - kolkata
 ## date - 10 / 08 / 2020
 
 import cv2 as cv
-face_cascade = cv.CascadeClassifier('..\libs\haarcascade_frontalface_default.xml')
-face_cascade_eye = cv.CascadeClassifier('..\libs\haarcascade_eye.xml')
-#face_glass = cv.CascadeClassifier('..\libs\haarcascade_eye_tree_eyeglasses.xml')
+
+face_cascade = cv.CascadeClassifier("..\libs\haarcascade_frontalface_default.xml")
+face_cascade_eye = cv.CascadeClassifier("..\libs\haarcascade_eye.xml")
+# face_glass = cv.CascadeClassifier('..\libs\haarcascade_eye_tree_eyeglasses.xml')
 
 cap = cv.VideoCapture(0)
-while(cap.isOpened()):
+while cap.isOpened():
 
-    falg ,img = cap.read() #start reading the camera output i mean frames
+    falg, img = cap.read()  # start reading the camera output i mean frames
     # cap.read() returning a bool value and a frame onject type value
 
-    gray = cv.cvtColor(img , cv.COLOR_BGR2GRAY) # converting to grayscale image to perform smoother
-    faces = face_cascade.detectMultiScale(img , 1.1, 7) #we use detectMultiscale library function to detect the predefined structures of a face
-    eyes = face_cascade_eye.detectMultiScale(img , 1.1 , 7)
+    gray = cv.cvtColor(
+        img, cv.COLOR_BGR2GRAY
+    )  # converting to grayscale image to perform smoother
+    faces = face_cascade.detectMultiScale(
+        img, 1.1, 7
+    )  # we use detectMultiscale library function to detect the predefined structures of a face
+    eyes = face_cascade_eye.detectMultiScale(img, 1.1, 7)
     # using for loops we are trying to read each and every frame and map
-    for(x , y ,w ,h ) in faces:
-         cv.rectangle(img , (x , y) , (x+w , y+h) , (0 , 255 , 0) , 1)
+    for (x, y, w, h) in faces:
+        cv.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 1)
 
-    for(a , b , c , d) in eyes:
-         cv.rectangle(img, (a , b), (a+c, b+d), (255, 0, 0), 1)
+    for (a, b, c, d) in eyes:
+        cv.rectangle(img, (a, b), (a + c, b + d), (255, 0, 0), 1)
 
-    cv.imshow('img' , img )
+    cv.imshow("img", img)
     c = cv.waitKey(1)
-    if c == ord('q'):
+    if c == ord("q"):
         break
 
 cv.release()
 cv.destroyAllWindows()
-
-

Face and eye Recognition/gesture_control.py

@@ -1,17 +1,18 @@
 import cv2 as cv
+
 # import numpy as np
 
-img = cv.imread('..\img\hand1.jpg' , 0)
-flag,frame = cv.threshold(img , 70 , 255 , cv.THRESH_BINARY)
+img = cv.imread("..\img\hand1.jpg", 0)
+flag, frame = cv.threshold(img, 70, 255, cv.THRESH_BINARY)
 
-contor,_ = cv.findContours(frame.copy(),cv.RETR_TREE,cv.CHAIN_APPROX_SIMPLE)
+contor, _ = cv.findContours(frame.copy(), cv.RETR_TREE, cv.CHAIN_APPROX_SIMPLE)
 
 hull = [cv.convexHull(c) for c in contor]
 
-final = cv.drawContours(img , hull , -1 , (0 , 0 , 0) )
-cv.imshow('original_image' , img)
-cv.imshow('thres' , frame)
-cv.imshow('final_hsv' , final)
+final = cv.drawContours(img, hull, -1, (0, 0, 0))
+cv.imshow("original_image", img)
+cv.imshow("thres", frame)
+cv.imshow("final_hsv", final)
 
 cv.waitKey(0)
-cv.destroyAllWindows()
+cv.destroyAllWindows()