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import cv2
import sys
from cv2 import CONTOURS_MATCH_I2
import numpy as np
#Takes two inputs as images
#Original 1 and 2 are dummy data
original =cv2.imread(r"Animate\images\flag (1).png")
original2 =cv2.imread(r"Animate\images\brain2.png")
# get key positions at which frame needs to be generated
def list_of_positions(num_contours,num_frames=100):
positions=[]
for i in range(0, num_frames):
positions.append(int(num_contours/num_frames*i))
return positions
def contourfinder(image1, image2, text=None, num_frames=100):
#Create two blank pages to write into
blank = np.zeros(image1.shape, dtype='uint8')
blank2 = np.zeros(image1.shape, dtype='uint8')
#Threshold and contours for image 1 and 2
threshold=cv2.Canny(image=image1, threshold1=100, threshold2=200)
contours, hierarchies = cv2.findContours(threshold, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
threshold2=cv2.Canny(image=original2, threshold1=100, threshold2=200)
contours2, hierarchies2 = cv2.findContours(threshold2, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
#Initialize three empty videos
vid1 = cv2.VideoWriter('vid1.mp4',cv2.VideoWriter_fourcc(*'mp4v'), 24, threshold.shape)
vid2 = cv2.VideoWriter('vid2.mp4',cv2.VideoWriter_fourcc(*'mp4v'), 24, threshold.shape)
text_vid = cv2.VideoWriter('text_vid.mp4',cv2.VideoWriter_fourcc(*'mp4v'), 10, threshold.shape)
#Get positions
positions=list_of_positions((len(contours)))
frames=[]
#Loop over contours adding them to blank image then writing to video
for i in range(0, len(contours)):
cv2.drawContours(blank, contours=contours, contourIdx=i, color=(125, 200, 255), thickness=1)
if i in positions:
frames.append(blank)
#Complile to video
vid1.write(blank)
last_image1=blank
vid1.release()
positions=list_of_positions((len(contours2)))
for i in range(0, len(contours2)):
cv2.drawContours(blank2, contours=contours2, contourIdx=i, color=(125, 200, 255), thickness=1)
if i in positions:
frames.append(blank2)
vid2.write(blank2)
last_image2=blank2
vid2.release()
#Next is the text vid
if text !=None:
# Reading an image in default mode
image = np.zeros(original.shape, dtype='uint8')
# font
font = cv2.FONT_HERSHEY_COMPLEX
# org
org = (10, 400)
# fontScale
fontScale = 3
# Blue color in BGR
color = (186, 184, 108)
# Line thickness of 2 px
thickness = 4
def text_frames(text,image,org):
spacing=55 #spacing between letters
blink=image
cv2.imwrite(f"blink.png", blink)
for i in range(0, len(text)-1):
text_vid.write(blink)
# Using cv2.putText() method
image = cv2.putText(image, text[i], org, font,
fontScale, color, thickness, cv2.LINE_AA)
#Take care of org spacing
org=(org[0]+spacing,org[1])
if text[i].isupper():
org=(org[0] +spacing +1, org[1])
print(f"Upper {text[i]}")
print(org)
# Displaying the image
cv2.imwrite(f"text_im{i}.png", image)
#Complile to video
text_vid.write(image)
text_vid.release()
text_frames(text,image,org)
return last_image1,last_image2
#contourfinder(original, original2, "spies gui Fly")
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