Delete image.py

Deleted first long code

OpenCV/image.py

@@ -1,171 +0,0 @@
-from turtle import ycor
-import numpy as np
-import png
-import cv2
-
-class Image:
-    def __init__(self, x_pixels=0, y_pixels=0, filename=''):
-        # you need to input either filename OR x_pixels, y_pixels, and num_channels
-        self.input_path = 'pyphotoshop-main\input/'
-        self.output_path = 'pyphotoshop-main\output/'
-       
-        self.x_pixels = x_pixels
-        self.y_pixels = y_pixels
-            
-        self.array = np.zeros((x_pixels, y_pixels))
-
-
-#Read original image          
-im=cv2.imread(r"Animate\images\flag (1).png")
-
-
-#Change to 2D array and canny_edges
-canny_edges=cv2.Canny(image=im, threshold1=100, threshold2=200)
-
-
-manys=np.random.randint(255, size=(5,5))
-ones=np.array([[0, 255, 0, 255,0],[ 255, 0,  0, 255,  255],[0,  255,  0,  255, 0],[255, 255,  0,  255, 0],[ 255, 0, 255, 0, 255]])
-
-cv2.imwrite("ones.png",ones)
-
-#Try loop through elements in the image matrice:
-
-#-----------------------------------------------------------------------------------------------------------
-
-
-
-
-#Getting the last key in a dictionary
-def get_last_key(dictionary):
-  for key in dictionary.keys():
-    last_key=key
-  return last_key  
-
-#Get the coord of the key with the white value/255
-def get_white_key(dictionary):
-    for key,value in dictionary.items():
-        if value==255:
-           white_coord=key
-    return white_coord
-
-
-# find neighbouring pixel:
-def get_neighbours(image, x, y, x_pixels, y_pixels, kernel=0):
-    
-    neighbour_coords=[
-    [max(0, (x-1)),max(0,(y-1))],
-    [max(0, (x-1)),y],
-    [max(0, (x-1)), min((y_pixels-1),(y+1))],
-    [x,max(0,y-1)],
-    [x,min((y_pixels-1),(y+1))],
-    [min((x_pixels-1),(x+1)),max(0,(y-1))],
-    [min((x_pixels-1),(x+1)),y],
-    [min((x_pixels-1),(x+1)),y+1]
-    ] # to finish array kernel....
-    neighbour_coords=np.array(neighbour_coords)
-    print(f"Image pixel is : at {x,y} ")
-    return neighbour_coords
-
-#find value at neighbour
-def value_at_neighbour(new_frame,image,coord=[0,0],pixel_count=0):
-    pixel_count+=1
-    print(f"Pixel count is at {pixel_count}")
-    x_pixels, y_pixels=np.shape(image)
-    neighbour_coords=get_neighbours(image, coord[0], coord[1],x_pixels, y_pixels,kernel=0)
-    neighbour_values=[]#empty array with shape of nighbour-co-ords array
-    dict={}
-
-    #Run through coords in neighbours coord list and find their values      
-    for coord in neighbour_coords:
-        neighbour_value = image[min(x_pixels-1,coord[0]),min(y_pixels-1,coord[1])]
-        neighbour_values.append(neighbour_value)
-
-        #Changing values back to normal arrays to work with in dict
-        pyneighbour_value=int(neighbour_value)
-        pyz=tuple(coord)
-        dict[pyz]=pyneighbour_value# append to dictionary of neighbour-co-ords
-    print(f"My dict of neighbour coords:values is {dict} and value is {pyneighbour_value} ")#At the end of this for loop, we finally get
-        
-    
-
-       
-    if pixel_count <25:
-        if 255 in neighbour_values:
-            coord=get_white_key(dict)
-            print(f"\n \n New coordinate in recursive function is {coord} and pixl count{pixel_count}")
-            
-            #Append dict of neighbours values to new_frame array
-            for key, value in dict.items():
-                x_index=int(key[0])
-                y_index=int(key[1])
-                new_frame[x_index][y_index]=value
-
-
-            #Convert array with new dict values to np array, then save it a 
-            #list of variables that we can cv.write later
-            frames[pixel_count]=new_frame
-            
-
-            value_at_neighbour(new_frame, image,coord,pixel_count=pixel_count)
-
-        #if all the values are black and it breaks out of loop
-        #We need to check the next square
-        elif 255 not in neighbour_values:
-            coord=get_last_key(dict)
-            print(f"\n \n Value is 0 so new coord is {coord}")
-            value_at_neighbour(new_frame, image,coord,pixel_count)
-                
-                           
-                           
-                
-            
-
-   
-
-
-            
-
-
-
-
-
-#Create and write image with path
-#Create an empty imaage of arrays with 0 and switch the 0 with the white values one by one
-
-"""
-That is, if neighbour coord is True
-If neighbour coord is True, then move to square
-Divide square by number of frames
-We need it to pick a square
-"""
-
-
-#Initialize frame count
-frame_count=0
-
-#So now we have to create a path through the image and create frames  
-def create_path_frames(frames=10) :
-    new_frame=np.zeros(5,5)
-    for i in range(frames): #number of frames
-        frame_count += 1
-        cv2.imwrite(f'new{frame_count}.png',new_frame)
-
-            
-
-
-new_frame=[[0]*5]*5
-
-
-frames={}
-
-value_at_neighbour(new_frame, ones)
-
-print(len(frames))
-"""
-for key, value in frames.items():
-    frame=np.array(value)
-    cv2.imwrite(f'frame{key}.png',frame)
-"""
-
-
-