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Nov 27, 2021
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add class #7

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3 changes: 1 addition & 2 deletions .idea/Filteristic.iml
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2 changes: 1 addition & 1 deletion .idea/misc.xml
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Binary file added filters/__pycache__/beardfilter.cpython-39.pyc
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Binary file added filters/__pycache__/change_filter.cpython-39.pyc
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118 changes: 72 additions & 46 deletions filters/beardfilter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,66 +2,92 @@
import numpy as np
import dlib
from math import hypot
from change_filter import change_filter
# change_filter =[{'filter':['../assest/hair9.png','../assest/ghoul2.png'],'center':[27,66],'width':[1.5,1],'height':[1,1],'up':[100,20],'left':[0,0]}]
cap = cv2.VideoCapture(0)
_, frame = cap.read()
rows, cols, _ = frame.shape
filter1 = np.zeros((rows, cols), np.uint8)
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
counte=0
def video_filtering_face(path,center,width,height,up,left,counte=0):

filter_image = []
for i in path:
filter_image.append(cv2.imread(i))


def video_filtering_face(path,center,width,height,up=0,left=0,yahia = False):
filter_path = path
filter_image = cv2.imread(filter_path)
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")
cap = cv2.VideoCapture(0)
_, frame = cap.read()
rows, cols, _ = frame.shape
filter1 = np.zeros((rows, cols), np.uint8)
while cap.isOpened():
filter1 = np.zeros((rows, cols), np.uint8)

_, frame = cap.read()
filter1.fill(0)
gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = detector(frame)
if faces:
try:
for i in range(len(path)):
filter(frame,gray_frame,faces,filter_image[i],center[i],width[i],height[i],up[i],left[i])
except:
_, frame_f = cap.read()
cv2.imshow("Frame", frame_f)
else:
_, frame_f = cap.read()
cv2.imshow("Frame", frame_f)
key = cv2.waitKey(1)
if key == ord('n'):
# print('first : ' ,i)
change_image(counte)
# print('second : ', i)

for face in faces:
landmarks = predictor(gray_frame, face)

# filter coordinates
if yahia:
up = (landmarks.part(8).y - landmarks.part(62).y)*3
center_filter = (landmarks.part(center).x-left, landmarks.part(center).y-up)
left_filter = (landmarks.part(3).x, landmarks.part(3).y)
right_filter = (landmarks.part(13).x, landmarks.part(13).y)

filter_width = int(hypot(left_filter[0] - right_filter[0],
left_filter[1] - right_filter[1]) * width)
filter_height = int(filter_width *height)
def filter(frame,gray_frame,faces,filter_image1,center,width,height,up=0,left=0):
for face in faces:
landmarks = predictor(gray_frame, face)

# New filter position
top_left = (int(center_filter[0] - filter_width / 2),
int(center_filter[1] - filter_height / 2))
bottom_right = (int(center_filter[0] + filter_width / 2),
int(center_filter[1] + filter_height / 2))
# filter coordinates
# top_filter = (landmarks.part(27).x+10, landmarks.part(24).y+10)
# if yahia:
# up = (landmarks.part(8).y - landmarks.part(62).y) * 3
center_filter = (landmarks.part(center).x-left, landmarks.part(center).y-up)
left_filter = (landmarks.part(4).x, landmarks.part(4).y)
right_filter = (landmarks.part(14).x, landmarks.part(14).y)

# Adding the new filter
# coloring
filtery = cv2.resize(filter_image, (filter_width, filter_height))
filtery_gray = cv2.cvtColor(filtery, cv2.COLOR_BGR2GRAY)
filter_width = int(hypot(left_filter[0] - right_filter[0],
left_filter[1] - right_filter[1]) * width)
filter_height = int(filter_width * height)

_, filter1 = cv2.threshold(filtery_gray, 25, 255, cv2.THRESH_BINARY_INV)
# New filter position
top_left = (int(center_filter[0] - filter_width / 2),
int(center_filter[1] - filter_height / 2))
bottom_right = (int(center_filter[0] + filter_width / 2),
int(center_filter[1] + filter_height / 2))

filter_area = frame[top_left[1]: top_left[1] + filter_height,
top_left[0]: top_left[0] + filter_width]
filter_area_no_filter = cv2.bitwise_and(filter_area, filter_area, mask=filter1)
final_filter = cv2.add(filter_area_no_filter, filtery)
# Adding the new filter
# coloring
filtery = cv2.resize(filter_image1, (filter_width, filter_height))
filtery_gray = cv2.cvtColor(filtery, cv2.COLOR_BGR2GRAY)
_, filter1 = cv2.threshold(filtery_gray, 25, 255, cv2.THRESH_BINARY_INV)

frame[top_left[1]: top_left[1] + filter_height,
top_left[0]: top_left[0] + filter_width] = final_filter
filter_area = frame[top_left[1]: top_left[1] + filter_height,
top_left[0]: top_left[0] + filter_width]
filter_area_no_filter = cv2.bitwise_and(filter_area, filter_area, mask=filter1)
final_filter = cv2.add(filter_area_no_filter, filtery)

cv2.imshow("Frame", frame)
except:
_, frame_f = cap.read()
cv2.imshow("Frame", frame_f)
else:
_, frame_f = cap.read()
cv2.imshow("Frame", frame_f)
key = cv2.waitKey(1)
if key == 27:
break
frame[top_left[1]: top_left[1] + filter_height,
top_left[0]: top_left[0] + filter_width,:] = final_filter

cv2.imshow("Frame", frame)

def change_image(i):
video_filtering_face(
change_filter[i]['filter'],
change_filter[i]['center'],
change_filter[i]['width'],
change_filter[i]['height'],
change_filter[i]['up'],
change_filter[i]['left'],
change_filter[i]['counte']
)
62 changes: 62 additions & 0 deletions filters/change_filter.py
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Original file line number Diff line number Diff line change
@@ -0,0 +1,62 @@


change_filter =[{'filter':['../assest/hair9.png','../assest/ghoul2.png','../assest/eye1.png','../assest/eye2.png'],
'center':[27,66,40,46],
'width':[1.5,1,0.2,0.2],
'height':[1,1,0.4,0.4],
'up':[100,20,5,5],
'left':[0,0,0,0],
'counte':1},
{'filter': ["../assest/birthday-hat.png"],
'center': [27],
'width': [1.3],
'height': [1],
'up': [120],
'left': [0],
'counte':2},
{'filter': ["../assest/gold-crown.png"],
'center': [27],
'width': [1.3],
'height': [1],
'up': [120],
'left': [0],
'counte':3},
{'filter': ["../assest/queens-crown.png"],
'center': [27],
'width': [1.3],
'height': [1],
'up': [120],
'left': [0],
'counte':4},
{'filter': ["../assest/flower-crown.png"],
'center': [27],
'width': [1.3],
'height': [1],
'up': [80],
'left': [0],
'counte': 5},
{'filter': ["../assest/funny-sunglass.png"],
'center': [27],
'width': [1.05],
'height': [0.33],
'up': [0],
'left': [0],
'counte': 6},
{'filter': ['../assest/moustache2.png'],
'center': [51],
'width': [1],
'height': [0.5],
'up': [1],
'left': [-3],
'counte': 7},
{'filter': ["../assest/tongue.png"],
'center': [57],
'width': [0.6],
'height': [1.2],
'up': [-25],
'left': [0],
'counte': 0},


]

6 changes: 6 additions & 0 deletions filters/fliter_face.json
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change_filter =[{'filter':['../assest/hair9.png','../assest/ghoul2.png'],
'center':[27,66],
'width':[1.5,1],
'height':[1,1],
'up':[100,20],
'left':[0,0]}]
12 changes: 6 additions & 6 deletions filters/video_filtering_face.py
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Expand Up @@ -2,11 +2,11 @@

# video_filtering_face("beard.png",8,1.1,1.5)

# video_filtering_face("../assest/birthday-hat.png",27,1.3,1.2,yahia=True)
# video_filtering_face("../assest/gold-crown.png",29,1.5,0.5, yahia = True)
# video_filtering_face("../assest/queens-crown.png",29,1.5,0.5, yahia = True)
# video_filtering_face("../assest/flower-crown.png",27,1.5,0.5,90)

# video_filtering_face("../assest/sunglasses2.png",27,1,0.35) ## not working
# video_filtering_face("../assest/funny-sunglass.png",27,1.05,0.33)
# video_filtering_face("../assest/moustache2.png",51,1,0.5,1,-3)
video_filtering_face("../assest/tongue.png",57,0.6,1.2,-25)
# video_filtering_face(['../assest/moustache2.png'],[51],[1],[0.5],[1],[-3])
video_filtering_face(["../assest/tongue.png"],[57],[0.6],[1.2],[-25],[0])
# video_filtering_face(['../assest/hair9.png','../assest/ghoul2.png','../assest/eye1.png','../assest/eye2.png'],
# [27,66,40,46],[1.5,1,0.2,0.2],[1,1,0.4,0.4],[100,20,5,5],[0,0,0,0])