diff --git a/.idea/Filteristic.iml b/.idea/Filteristic.iml index d28d420..8aeb520 100644 --- a/.idea/Filteristic.iml +++ b/.idea/Filteristic.iml @@ -2,11 +2,10 @@ - - + \ No newline at end of file diff --git a/.idea/misc.xml b/.idea/misc.xml index b534b89..8d93904 100644 --- a/.idea/misc.xml +++ b/.idea/misc.xml @@ -1,4 +1,4 @@ - + \ No newline at end of file diff --git a/__pycache__/main.cpython-38.pyc b/__pycache__/main.cpython-38.pyc deleted file mode 100644 index cae4fd6..0000000 Binary files a/__pycache__/main.cpython-38.pyc and /dev/null differ diff --git a/assest/background/back1.png b/assest/background/back1.png new file mode 100644 index 0000000..d9f9437 Binary files /dev/null and b/assest/background/back1.png differ diff --git a/assest/background/back2.png b/assest/background/back2.png new file mode 100644 index 0000000..5c05343 Binary files /dev/null and b/assest/background/back2.png differ diff --git a/assest/background/back3.png b/assest/background/back3.png new file mode 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--git a/assest/moustache2.png b/assest/moustache2.png new file mode 100644 index 0000000..c26900e Binary files /dev/null and b/assest/moustache2.png differ diff --git a/assest/queens-crown.png b/assest/queens-crown.png new file mode 100644 index 0000000..dfcf506 Binary files /dev/null and b/assest/queens-crown.png differ diff --git a/sunglasses.png b/assest/sunglasses.png similarity index 100% rename from sunglasses.png rename to assest/sunglasses.png diff --git a/assest/tongue.png b/assest/tongue.png new file mode 100644 index 0000000..93636b8 Binary files /dev/null and b/assest/tongue.png differ diff --git a/background_image/backgorund_image.py b/background_image/backgorund_image.py new file mode 100644 index 0000000..b6b2705 --- /dev/null +++ b/background_image/backgorund_image.py @@ -0,0 +1,23 @@ +import pixellib +from check_directory import saveimage,check_image +from pixellib.tune_bg import alter_bg +def backgroundImage(type,input_image,color,back_ground=''): + path_name =check_image() + if path_name: + change_bg = alter_bg(model_type = "pb") + change_bg.load_pascalvoc_model("xception_pascalvoc.pb") + + if type == 'image': + change_bg.change_bg_img(f_image_path = input_image,b_image_path = back_ground, output_image_name=path_name) + if type == 'gray': + change_bg.gray_bg(input_image, output_image_name=path_name) + if type =='color': + change_bg.color_bg(input_image, colors=color, output_image_name=path_name) + if type == 'blur': + change_bg.blur_bg(input_image, low=True, output_image_name=path_name) + saveimage(path_name) + + + + +# backgroundImage('gray','Output_image/test2.png','Input_image/lena.jpg') diff --git a/background_image/check_directory.py b/background_image/check_directory.py new file mode 100644 index 0000000..3691be4 --- /dev/null +++ b/background_image/check_directory.py @@ -0,0 +1,46 @@ +from os.path import exists +import os +import cv2 +import requests +def check_image(): + path = input('enter the name of path output : ') + path_image = f'Output_image/{path}.png' + file_exists = exists(path_image) + while file_exists: + path_name2 = input('this name is exist try another one or enter q : ') + if path_name2 == 'q': + path_image = False + break + + path_image = f'Output_image/{path_name2}.png' + file_exists = exists(path_image) + return path_image + +def saveimage(path): + print("close the window for image") + image = cv2.imread(path) + cv2.imshow('image window', image) + cv2.waitKey(0) + cv2.destroyAllWindows() + save = input('do you want to save image ?') + if not save == 'yes': + os.remove(path) + return +def add_path(image_path,origin): + path_name = input('add path name : ') + r= requests.get(image_path) + path_image = f'{origin}{path_name}.png' + file_exists = exists(path_image) + while file_exists : + path_name2 = input('this name is exist try another one or enter q : ') + if path_name2 =='q': + path_image='' + break + + path_image = f'{origin}{path_name2}.png' + file_exists = exists(path_image) + + with open(path_image,'wb') as f : + f.write(r.content) + + return path_image \ No newline at end of file diff --git a/background_image/filter_background_image.py b/background_image/filter_background_image.py new file mode 100644 index 0000000..71c5b57 --- /dev/null +++ b/background_image/filter_background_image.py @@ -0,0 +1,20 @@ +from backgorund_image import backgroundImage +from check_directory import add_path +def filter_background_image(): + type_filter = int(input('type_filter : ')) + background_filter ='' + color = '' + type_of_background = input('enter type of background : [gray,image,blur,color] : ') + path_input_image = add_path(input('path image : '),'Input_image/') + if type_filter ==0 and type_of_background == 'image' : + background_filter = add_path(input('path image : '), 'input_background/') + backgroundImage(type_of_background, path_input_image,color, background_filter) + if type_of_background=='color': + add_color = input('input color rgb : 0,0,255 : ') + color = tuple(map(int, add_color.split(','))) + + if type_filter == 1 : + backgroundImage(type_of_background,path_input_image,color,'../assest/background/back1.jpg') + if type_filter == 2 : + backgroundImage(type_of_background,path_input_image,background_filter,color,'../assest/background/back2.jpg') +filter_background_image() \ No newline at end of file diff --git a/background_live/__pycache__/background_live.cpython-39.pyc b/background_live/__pycache__/background_live.cpython-39.pyc new file mode 100644 index 0000000..4c5d07d Binary files /dev/null and b/background_live/__pycache__/background_live.cpython-39.pyc differ diff --git a/background_live/__pycache__/request_image.cpython-39.pyc b/background_live/__pycache__/request_image.cpython-39.pyc new file mode 100644 index 0000000..4d607f7 Binary files /dev/null and b/background_live/__pycache__/request_image.cpython-39.pyc differ diff --git a/background_live/background_live.py b/background_live/background_live.py new file mode 100644 index 0000000..3dbee72 --- /dev/null +++ b/background_live/background_live.py @@ -0,0 +1,82 @@ +import cv2 +import mediapipe as mp +import numpy as np +from request_image import add_path +import os +def background(path,blur =1,img=2): + mp_selfie_segmentation = mp.solutions.selfie_segmentation + back1=1 + cam = cv2.VideoCapture(0) + cam.set(3, 1280) + cam.set(4, 720) + fsize = (520, 720) + + + + # begin with selfie segmentation model + + img_name = "" + while cam.isOpened(): + scene = cv2.imread(path) # read the scene image + scene = cv2.blur(scene, (blur, blur)) + scene = cv2.resize(scene, (fsize[1], fsize[0])) # resize scene to the size of frame + with mp_selfie_segmentation.SelfieSegmentation(model_selection=1) as selfie_seg: + bg_image = scene + ret, frame = cam.read() + if not ret: + print("Error reading frame...") + continue + frame = cv2.resize(frame, (fsize[1], fsize[0])) + + # flip it to look like selfie camera + frame = cv2.flip(frame, 1) + + # get rgb image to pass that on selfie segmentation + rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) + + # process it! + results = selfie_seg.process(rgb) + + # get the condition from result's segmentation mask + condition = np.stack((results.segmentation_mask,) * 3, axis=-1) > 0.1 + + # apply background change if condition matches + output_image = np.where(condition, frame, bg_image) + + # show the output + cv2.imshow('Background Change with MP', output_image) + key = cv2.waitKey(5) & 0xFF + + if key == ord('n'): + back1+=1 + if back1 ==img+1: + back1=1 + path = f'../assest/background/back{back1}.png' + if key == ord('a'): + path = add_path(input('path image : ')) + # wait until any key is pressed + + if key == ord('q'): + cam.release() + cv2.destroyAllWindows() # wait until any key is pressed + elif key == ord("c"): + img_name = "../saved/opencv_frame.png" + cv2.imwrite(img_name, output_image) + # print("{} written!".format(img_name)) + break + frames = cv2.imread(img_name) + cv2.imshow("Background Change with MP", frames) + key = cv2.waitKey(0) + os.remove("../saved/opencv_frame.png") + if key == ord("s"): + user_name = input("enter name") + imgdir = f"../saved/{user_name}.png" + cv2.imwrite(imgdir, frames) + background('../assest/background/back1.png',blur,img) + if key == ord("e"): + background('../assest/background/back1.png',blur,img) + cam.release() + cv2.destroyAllWindows() + + + diff --git a/background_live/filter_background_live.py b/background_live/filter_background_live.py new file mode 100644 index 0000000..b002c31 --- /dev/null +++ b/background_live/filter_background_live.py @@ -0,0 +1,13 @@ +from background_live import background +from request_image import add_path,check_image +from os.path import exists + +type_filter = int(input('type_filter : ')) +type_blur=int(input('number for blur start from 1 : ')) +if type_filter == 0: + path,img = add_path(input('path image : ')) + background('../assest/background/back1.png', type_blur,img) +if type_filter ==1: + img =check_image() + print(img) + background('../assest/background/back1.png',type_blur,img) diff --git a/background_live/request_image.py b/background_live/request_image.py new file mode 100644 index 0000000..1e548ca --- /dev/null +++ b/background_live/request_image.py @@ -0,0 +1,27 @@ +import requests +from os.path import exists +def add_path(image_path): + r= requests.get(image_path) + img =1 + path_image = f'../assest/background/back{img}.png' + file_exists = exists(path_image) + while file_exists : + img+=1 + path_image = f'../assest/background/back{img}.png' + file_exists = exists(path_image) + + with open(path_image,'wb') as f : + f.write(r.content) + + return path_image,img + +def check_image(): + img = 1 + path_image = f'../assest/background/back{img}.png' + file_exists = exists(path_image) + while file_exists: + img += 1 + path_image = f'../assest/background/back{img}.png' + file_exists = exists(path_image) + return img-1 + diff --git a/filters/__pycache__/dogfilter.cpython-38.pyc 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-1,73 +0,0 @@ -import cv2 -import numpy as np -import dlib -from math import hypot -filter_image = cv2.imread("assest/cat-ears.png") -filter_image3 = cv2.imread("assest/cat-nose.png") -# filter_image4 = cv2.imread("assest\eye1.png") -# filter_image5 = cv2.imread("assest\eye2.png") - - -# Loading Face detector -detector = dlib.get_frontal_face_detector() -predictor = dlib.shape_predictor("assest\shape_predictor_68_face_landmarks.dat") - -def filteringmouse(cap,rows, cols): - 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: - filter(frame,gray_frame,faces,filter_image,27,27,1.7,0.5,120) - filter(frame, gray_frame, faces, filter_image3,28,28,1.1,1,0) - - # filter(frame, gray_frame, faces, filter_image3,27,27,1.5,1,100) - # filter(frame, gray_frame, faces, filter_image4,40,40,0.2,0.4,5) - # filter(frame, gray_frame, faces, filter_image5,46,46,0.2,0.4,5) - - - - except: - _, frame_f = cap.read() - cv2.imshow("Frame", frame_f) - # else: - # _, frame_f = cap.read() - # cv2.imshow("Frame", frame_f) -def filter(frame,gray_frame,faces,filter_image1,X,Y,width,height,above=0,left=0): - for face in faces: - landmarks = predictor(gray_frame, face) - - # filter coordinates - # top_filter = (landmarks.part(27).x+10, landmarks.part(24).y+10) - center_filter = (landmarks.part(X).x-left, landmarks.part(Y).y-above) - left_filter = (landmarks.part(4).x, landmarks.part(4).y) - right_filter = (landmarks.part(14).x, landmarks.part(14).y) - - filter_width = int(hypot(left_filter[0] - right_filter[0], - left_filter[1] - right_filter[1]) * width) - filter_height = int(filter_width * height) - - # 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)) - - # 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) - - 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) - - frame[top_left[1]: top_left[1] + filter_height, - top_left[0]: top_left[0] + filter_width,:] = final_filter - - cv2.imshow("Frame", frame) \ No newline at end of file diff --git a/filters/dogfilter.py b/filters/dogfilter.py deleted file mode 100644 index 964de52..0000000 --- a/filters/dogfilter.py +++ /dev/null @@ -1,58 +0,0 @@ -import cv2 -import numpy as np -import dlib -from math import hypot -filter_image = cv2.imread("assest\dogfilter.png") -# Loading Face detector -detector = dlib.get_frontal_face_detector() -predictor = dlib.shape_predictor("assest\shape_predictor_68_face_landmarks.dat") - -def filteringdog(cap,rows, cols): - 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 face in faces: - landmarks = predictor(gray_frame, face) - - # filter coordinates - # top_filter = (landmarks.part(27).x, landmarks.part(24).y) - center_filter = (landmarks.part(27).x, landmarks.part(27).y) - left_filter = (landmarks.part(2).x, landmarks.part(2).y) - right_filter = (landmarks.part(14).x, landmarks.part(14).y) - - filter_width = int(hypot(left_filter[0] - right_filter[0], - left_filter[1] - right_filter[1]) * 1.3) - filter_height = int(filter_width *1.5) - - # 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)) - - # Adding the new filter - # coloring - filtery = cv2.resize(filter_image, (filter_width, filter_height)) - filtery_gray = cv2.cvtColor(filtery, cv2.COLOR_BGR2GRAY) - _, filter1 = cv2.threshold(filtery_gray, 25, 255, cv2.THRESH_BINARY_INV) - - 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) - - frame[top_left[1]: top_left[1] + filter_height, - top_left[0]: top_left[0] + filter_width] = final_filter - - cv2.imshow("Frame", frame) - except: - _, frame_f = cap.read() - cv2.imshow("Frame", frame_f) - # else: - # _, frame_f = cap.read() - # cv2.imshow("Frame", frame_f) diff --git a/filters/face_filter_crown.py b/filters/face_filter_crown.py deleted file mode 100644 index d2ca543..0000000 --- a/filters/face_filter_crown.py +++ /dev/null @@ -1,52 +0,0 @@ -# import cv2 -# import numpy as np -# import dlib -# from math import hypot -# filter_image = cv2.imread("../assest/flower-crown-png-42606.png") -# -# # Loading Face detector -# detector = dlib.get_frontal_face_detector() -# predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat") -# -# cap = cv2.VideoCapture(0) -# -# while True : -# _, frame = cap.read() -# gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) -# faces = detector(frame) -# for face in faces : -# landmarks = predictor(gray_frame, face) -# top_glasses = (landmarks.part(24).x , landmarks.part(24).y) -# left_glasses = (landmarks.part(0).x , landmarks.part(0).y) -# right_glasses = (landmarks.part(16).x , landmarks.part(16).y) -# center_glasses = (landmarks.part(27).x , landmarks.part(27).y) -# -# glasses_width = int (hypot(left_glasses[0] -right_glasses[0], -# left_glasses[1] - right_glasses[1])) -# -# glasses_height = int(glasses_width * 0.6) -# -# # positios -# upper_left = (int(center_glasses[0] - glasses_width/2 ), -# int(center_glasses[1] - glasses_height/2)) -# lower_right = (int(center_glasses[0] + glasses_width / 2), -# int(center_glasses[1] + glasses_height / 2)) -# -# # Adding the glasses in the correct position -# glasses = cv2.resize(filter_image,(glasses_width , glasses_height)) -# gray_glasses = cv2.cvtColor(glasses, cv2.COLOR_BGR2GRAY) -# -# -# _, glasses_mask = cv2.threshold(gray_glasses,120, 225, cv2.THRESH_BINARY_INV) -# glasses_area = frame[upper_left[1] : upper_left[1]+glasses_height , upper_left[0]:upper_left[0]+glasses_width] -# glasses_ares_no_glasses = cv2.bitwise_and(glasses_area , glasses_area,mask= glasses_mask) -# final_glasses = cv2.add(glasses_ares_no_glasses, glasses) -# frame[upper_left[1]: upper_left[1] + glasses_height, upper_left[0]:upper_left[0] + glasses_width] = final_glasses -# -# cv2.imshow("Frame",frame) -# -# -# -# key = cv2.waitKey(1) -# if key ==27 : -# break \ No newline at end of file diff --git a/filters/filter1.py b/filters/filter1.py deleted file mode 100644 index 0946dc0..0000000 --- a/filters/filter1.py +++ /dev/null @@ -1,59 +0,0 @@ -import cv2 -import numpy as np -import dlib -from math import hypot - -filter_image = cv2.imread("assest\image1.png") -# Loading Face detector -detector = dlib.get_frontal_face_detector() -predictor = dlib.shape_predictor("assest\shape_predictor_68_face_landmarks.dat") - -def filtering(cap,rows, cols): - 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 face in faces: - landmarks = predictor(gray_frame, face) - - # filter coordinates - # top_filter = (landmarks.part(27).x, landmarks.part(24).y) - center_filter = (landmarks.part(32).x, landmarks.part(24).y) - left_filter = (landmarks.part(3).x, landmarks.part(2).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]) * 1.7) - filter_height = int(filter_width *1.1) - - # 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)) - - # Adding the new filter - # coloring - filtery = cv2.resize(filter_image, (filter_width, filter_height)) - filtery_gray = cv2.cvtColor(filtery, cv2.COLOR_BGR2GRAY) - _, filter1 = cv2.threshold(filtery_gray, 25, 255, cv2.THRESH_BINARY_INV) - - 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) - - frame[top_left[1]: top_left[1] + filter_height, - top_left[0]: top_left[0] + filter_width] = final_filter - - cv2.imshow("Frame", frame) - except: - _, frame_f = cap.read() - cv2.imshow("Frame", frame_f) - else: - _, frame_f = cap.read() - cv2.imshow("Frame", frame_f) diff --git a/filters/head_crown.py b/filters/head_crown.py deleted file mode 100644 index 4bf6fa2..0000000 --- a/filters/head_crown.py +++ /dev/null @@ -1,62 +0,0 @@ -import cv2 -import numpy as np -import dlib -from math import hypot -filter_image = cv2.imread("assest/flower-crown-png-42606.png") - -# Loading Face detector -detector = dlib.get_frontal_face_detector() -predictor = dlib.shape_predictor("assest\shape_predictor_68_face_landmarks.dat") - -def filteringmouse(cap,rows, cols): - 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: - filter(frame,gray_frame,faces,filter_image,27,27,1.2,0.6,20) - # filter(frame, gray_frame, faces, filter_image3,27,27,1.5,2,25) - except: - _, frame_f = cap.read() - cv2.imshow("Frame", frame_f) - # else: - # _, frame_f = cap.read() - # cv2.imshow("Frame", frame_f) -def filter(frame,gray_frame,faces,filter_image1,X,Y,width,height,above=0,left=0): - for face in faces: - landmarks = predictor(gray_frame, face) - - # filter coordinates - # top_filter = (landmarks.part(27).x+10, landmarks.part(24).y+10) - center_filter = (landmarks.part(X).x-left, landmarks.part(Y).y-above) - left_filter = (landmarks.part(4).x, landmarks.part(4).y) - right_filter = (landmarks.part(14).x, landmarks.part(14).y) - - filter_width = int(hypot(left_filter[0] - right_filter[0], - left_filter[1] - right_filter[1]) * width) - filter_height = int(filter_width * height) - - # New filter position - top_left = (int(center_filter[0] - filter_width / 2), - int(center_filter[1] - filter_height )) - bottom_right = (int(center_filter[0] + filter_width / 2), - int(center_filter[1] + filter_height / 2)) - - # 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) - - 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) - - frame[top_left[1]: top_left[1] + filter_height, - top_left[0]: top_left[0] + filter_width,:] = final_filter - - cv2.imshow("Frame", frame) \ No newline at end of file diff --git a/filters/mustache_filter_2.py b/filters/mustache_filter_2.py deleted file mode 100644 index 130ea16..0000000 --- a/filters/mustache_filter_2.py +++ /dev/null @@ -1,62 +0,0 @@ -import cv2 -import numpy as np -import dlib -from math import hypot -filter_image = cv2.imread("assest/10-2-moustache-free-png-image.png") - -# Loading Face detector -detector = dlib.get_frontal_face_detector() -predictor = dlib.shape_predictor("assest\shape_predictor_68_face_landmarks.dat") - -def filteringmouse(cap,rows, cols): - 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: - filter(frame,gray_frame,faces,filter_image,51,51,1,0.5,1,-3) - # filter(frame, gray_frame, faces, filter_image3,27,27,1.5,2,25) - except: - _, frame_f = cap.read() - cv2.imshow("Frame", frame_f) - # else: - # _, frame_f = cap.read() - # cv2.imshow("Frame", frame_f) -def filter(frame,gray_frame,faces,filter_image1,X,Y,width,height,above=0,left=0): - for face in faces: - landmarks = predictor(gray_frame, face) - - # filter coordinates - # top_filter = (landmarks.part(27).x+10, landmarks.part(24).y+10) - center_filter = (landmarks.part(X).x-left, landmarks.part(Y).y-above) - left_filter = (landmarks.part(4).x, landmarks.part(4).y) - right_filter = (landmarks.part(12).x, landmarks.part(12).y) - - filter_width = int(hypot(left_filter[0] - right_filter[0], - left_filter[1] - right_filter[1]) * width) - filter_height = int(filter_width * height) - - # 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)) - - # 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, 225, cv2.THRESH_BINARY_INV) - - 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) - - frame[top_left[1]: top_left[1] + filter_height, - top_left[0]: top_left[0] + filter_width,:] = final_filter - - cv2.imshow("Frame", frame) \ No newline at end of file diff --git a/filters_image/image_filtering_face.py b/filters_image/image_filtering_face.py new file mode 100644 index 0000000..85353b8 --- /dev/null +++ b/filters_image/image_filtering_face.py @@ -0,0 +1,104 @@ +import cv2 +import numpy as np +import dlib +from math import hypot +from filters_live.change_filter import change_filter +import os + +# Loading Face detector + +def image_filtering_face(path_filter,path_image,center,width,height,up,left,counte=0): + # path = r"../assest/moustache2.png" + filter_image = [] + for i in path_filter: + filter_image.append(cv2.imread(i)) + image = cv2.imread(path_image) + rows, cols, _ = image.shape + filter1 = np.zeros((rows, cols), np.uint8) + filter1.fill(0) + gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) + detector = dlib.get_frontal_face_detector() + faces = detector(image) + if faces: + try: + for i in range(len(path_filter)): + filter(image,gray_image,faces,filter_image[i],center[i],width[i],height[i],up[i],left[i]) + except: + image = cv2.imread(path_image) + cv2.imshow("Frame", image) + else: + image = cv2.imread(path_image) + cv2.imshow("Frame", image) + key = cv2.waitKey(0) + if key == ord('n'): + change_image(counte,path_image) + elif key == ord('q'): + cv2.destroyAllWindows() + # elif key == ord("c"): + # img_name = "../saved/opencv_frame.png" + # cv2.imwrite(img_name, image) + # print("{} written!".format(img_name)) + # + # image = cv2.imread(img_name) + # cv2.imshow("Frame", image) + # key = cv2.waitKey(0) + # os.remove("../saved/opencv_frame.png") + if key == ord("s"): + user_name = input("enter name") + imgdir = f"../saved/{user_name}.png" + cv2.imwrite(imgdir, image) + image_filtering_face(["../assest/tongue.png"],"../assest/face.jpg",[57],[0.6],[1.2],[-25],[0]) + if key == ord("e"): + image_filtering_face(["../assest/tongue.png"],"../assest/face.jpg",[57],[0.6],[1.2],[-25],[0]) + + + +def filter(image,gray_frame,faces,filter_image1,center,width,height,up=0,left=0): + predictor_path = r"../assest/shape_predictor_68_face_landmarks.dat" + predictor = dlib.shape_predictor(predictor_path) + + for face in faces: + landmarks = predictor(gray_frame, face) + + 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) + + filter_width = int(hypot(left_filter[0] - right_filter[0], + left_filter[1] - right_filter[1]) * width) + filter_height = int(filter_width * height) + + # 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)) + + # Adding the new filter + 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) + + filter_area = image[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) + + image[top_left[1]: top_left[1] + filter_height, + top_left[0]: top_left[0] + filter_width,:] = final_filter + + cv2.imshow("Frame", image) + +def change_image(i,path_image): + image_filtering_face( + change_filter[i]['filter'], + path_image, + change_filter[i]['center'], + change_filter[i]['width'], + change_filter[i]['height'], + change_filter[i]['up'], + change_filter[i]['left'], + change_filter[i]['counte'] + ) +if __name__ == "__main__": + image_filtering_face(["../assest/tongue.png"],"../assest/face.jpg",[57],[0.6],[1.2],[-25],[0]) \ No newline at end of file diff --git a/filters_live/change_filter.py b/filters_live/change_filter.py new file mode 100644 index 0000000..2285361 --- /dev/null +++ b/filters_live/change_filter.py @@ -0,0 +1,69 @@ +## jaso file for adding + +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/beard.png"], + 'center': [8], + 'width': [1.1], + 'height': [1.5], + 'up': [0], + 'left': [0], + 'counte': 8}, + {'filter': ["../assest/tongue.png"], + 'center': [57], + 'width': [0.6], + 'height': [1.2], + 'up': [-25], + 'left': [0], + 'counte': 0}, + + + ] + diff --git a/filters/glasses_black.py b/filters_live/glasses_black.py similarity index 100% rename from filters/glasses_black.py rename to filters_live/glasses_black.py diff --git a/filters/gost.py b/filters_live/gost.py similarity index 89% rename from filters/gost.py rename to filters_live/gost.py index 02e84a6..ac67b37 100644 --- a/filters/gost.py +++ b/filters_live/gost.py @@ -2,7 +2,7 @@ import numpy as np import dlib from math import hypot -filter_image = cv2.imread("assest/10-2-moustache-free-png-image.png") +filter_image = cv2.imread("assest/moustache2.png") # Loading Face detector detector = dlib.get_frontal_face_detector() diff --git a/filters/mustache_filter.py b/filters_live/mustache_filter.py similarity index 100% rename from filters/mustache_filter.py rename to filters_live/mustache_filter.py diff --git a/filters/shape_predictor_68_face_landmarks.dat b/filters_live/shape_predictor_68_face_landmarks.dat similarity index 100% rename from filters/shape_predictor_68_face_landmarks.dat rename to filters_live/shape_predictor_68_face_landmarks.dat diff --git a/filters_live/video_filtering_face.py b/filters_live/video_filtering_face.py new file mode 100644 index 0000000..979e2a9 --- /dev/null +++ b/filters_live/video_filtering_face.py @@ -0,0 +1,115 @@ +import cv2 +import numpy as np +import dlib +from math import hypot +from change_filter import change_filter +import os +# 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)) + + + 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 = cap.read() + cv2.imshow("Frame", frame) + else: + _, frame = cap.read() + cv2.imshow("Frame", frame) + key = cv2.waitKey(1) + if key == ord('n'): + # print('first : ' ,i) + change_image(counte) + # print('second : ', i) + elif key == ord('q'): + cap.release() + cv2.destroyAllWindows() + elif key ==ord("c"): + img_name = "../saved/opencv_frame.png" + cv2.imwrite(img_name, frame) + # print("{} written!".format(img_name)) + break + frames = cv2.imread(img_name) + cv2.imshow("Frame", frames) + key = cv2.waitKey(0) + os.remove("../saved/opencv_frame.png") + if key ==ord("s"): + user_name = input("enter name") + imgdir = f"../saved/{user_name}.png" + cv2.imwrite(imgdir, frames) + video_filtering_face(["../assest/tongue.png"], [57], [0.6], [1.2], [-25], [0]) + if key == ord("e"): + video_filtering_face(["../assest/tongue.png"], [57], [0.6], [1.2], [-25], [0]) + + + +def filter(frame,gray_frame,faces,filter_image1,center,width,height,up=0,left=0): + for face in faces: + landmarks = predictor(gray_frame, face) + + # 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) + + filter_width = int(hypot(left_filter[0] - right_filter[0], + left_filter[1] - right_filter[1]) * width) + filter_height = int(filter_width * height) + + # 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)) + + # 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) + + 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) + + 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'] + ) +if __name__ == "__main__": + video_filtering_face(["../assest/tongue.png"],[57],[0.6],[1.2],[-25],[0]) \ No newline at end of file diff --git a/main.py b/main.py index 8fa7f38..e69de29 100644 --- a/main.py +++ b/main.py @@ -1,17 +0,0 @@ -import cv2 -import numpy as np - -import dlib -from filters.filter1 import filtering -from filters.dogfilter import filteringdog -# Loading Camera and Nose image and Creating mask -cap = cv2.VideoCapture(0) -_, frame = cap.read() -# print(frame) -rows, cols, _ = frame.shape -filter1 = np.zeros((rows, cols), np.uint8) -while True: - filteringdog(cap,rows, cols) - key = cv2.waitKey(1) - if key == 27: - break diff --git a/saved/ yaseenmalkalbacgrond.png b/saved/ yaseenmalkalbacgrond.png new file mode 100644 index 0000000..cbbc30f Binary files /dev/null and b/saved/ yaseenmalkalbacgrond.png differ diff --git a/saved/ yousef.png b/saved/ yousef.png new file mode 100644 index 0000000..a797270 Binary files /dev/null and b/saved/ yousef.png differ diff --git a/saved/11.png b/saved/11.png new file mode 100644 index 0000000..35d2d4b Binary files /dev/null and b/saved/11.png differ diff --git a/saved/hiss.png b/saved/hiss.png new file mode 100644 index 0000000..adc0492 Binary files /dev/null and b/saved/hiss.png differ diff --git a/saved/opencv_frame32.png b/saved/opencv_frame32.png new file mode 100644 index 0000000..9e90a3f Binary files /dev/null and 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