finally I made a push

Tkinter/GUI.py

@@ -38,6 +38,7 @@ def videoWindow():
     def on_closing():
         cameraWindow.destroy()
         root.deiconify()
+
     backButton = tk.Button(cameraWindow, text="Previous Page", padx=90, pady=10, fg="white", bg="#2596be", font=('arial', 15), command=on_closing)
     backButton.grid()
 

Tkinter/GUI_Image.py

@@ -30,19 +30,17 @@ def browse():
         filename = filedialog.askopenfilename(title="select File",
                                               filetypes = (("jpeg files","*.jpg"),("all files","*.*"),('png files', '*.png')))
         images.append(filename)
-        canvas = Canvas(newWindow)
-        canvas.config(width=1000, height=500)
-        canvas.pack()
-        img = ImageTk.PhotoImage(Image.open(images[0]))
-
-        # images[0] = cv2.resize(images[0], (200, 200))
-
-        filtering = TkinterCustomButton(master=newWindow,text="Add Filter", corner_radius=5,command=lambda: image_filter(filename, canvas, newWindow),
+        img = Image.open(images[-1])
+        img = img.resize((500, 500))
+        img = ImageTk.PhotoImage(img)
+        img_label = Label(newWindow, image=img)
+        img_label.photo = img
+        img_label.place(x=228, y=40)
+
+        filtering = TkinterCustomButton(master=newWindow,text="Add Filter", corner_radius=5,command=lambda: image_filter(filename, newWindow),
                                         fg_color="#3319CB", hover_color="#005DFE", width=200,cursor="shuttle", text_font=("sans-serif", 20))
-        filtering.pack()
+        filtering.place(x=380, y=550)
 
-        test=canvas.create_image(0, 0, anchor="nw", image=img)
-        test.pack()
 
 
 
@@ -69,12 +67,18 @@ def on_closing():
 
     newWindow.protocol("WM_DELETE_WINDOW", on_closing)
 
-    def render(image_withfilter, canvas):
+    def render(image_withfilter):
         image_withfilter = cv2.cvtColor(image_withfilter, cv2.COLOR_BGR2RGB)
-        photo = ImageTk.PhotoImage(image=Image.fromarray(image_withfilter))
-        canvas.create_image(0, 0, anchor="nw", image=photo).pack()
-
-    def next_fun(path, canvas):
+        img = Image.fromarray(image_withfilter)
+        img = img.resize((500, 500))
+        img = ImageTk.PhotoImage(img)
+        img_label = Label(newWindow, image=img)
+        img_label.photo = img
+        img_label.place(x=228, y=40)
+        # photo = ImageTk.PhotoImage(image=Image.fromarray(image_withfilter))
+        # canvas.create_image(0, 0, anchor="nw", image=photo)
+
+    def next_fun(path):
         global count
 
         images.append(image_filtering_face(
@@ -89,8 +93,8 @@ def next_fun(path, canvas):
         ))
         count += 1
         if count == len(change_filter) - 1:
-            count = -1
-        render(images[-1], canvas)
+            count = 0
+        render(images[-1])
 
     def submit(content,top):
         global entry
@@ -101,19 +105,20 @@ def submit(content,top):
         top.destroy()
     def saving(content, newWindow):
         pass
-    def image_filter(path, canvas, newWindow):
+    def image_filter(path, newWindow):
         images.append(
             image_filtering_face(["../assest/tongue.png"], path, [57], [0.6], [1.2], [-25], [0],
                                  [0]))
         save = TkinterCustomButton(master=newWindow, text="Save", corner_radius=5,
                                    command=lambda: open_popup(images[-1],newWindow), fg_color="#3319CB",
                                    hover_color="#005DFE", width=200, cursor="shuttle", text_font=("sans-serif", 20))
-        save.place(x=50, y=544)
+        save.place(x=50, y=550)
         next = TkinterCustomButton(master=newWindow, text="Next", corner_radius=5,
-                                   command=lambda: next_fun(path, canvas), fg_color="#3319CB",
+                                   command=lambda: next_fun(path), fg_color="#3319CB",
                                    hover_color="#005DFE", width=200, cursor="shuttle", text_font=("sans-serif", 20))
-        next.place(x=710, y=544)
-        render(images[-1], canvas)
+        newWindow.bind("<Right>", lambda x: next_fun(path))
+        next.place(x=710, y=550)
+        render(images[-1])
 
     def open_popup(content,newWindow):
         top = Toplevel(newWindow)
@@ -127,4 +132,3 @@ def open_popup(content,newWindow):
         entry = tk.Entry(top, width=20, bg="white")
         entry.place(x=75, y=10)
         sub_btn.place(x=75, y=50)
-

Tkinter/GUI_Live.py

@@ -18,8 +18,6 @@ def camera(newWindow):
     lmain = Label(app)
     lmain.grid()
 
-
-
     def printInput():
         add_path(inputtxt2.get(1.0, "end-1c"))
 
@@ -115,9 +113,8 @@ def path_name(frame):
                                 command=lambda: print_path2(inputtxt, frame))
         printButton.grid(row=1, column=2)
 
-
-
-
+    newWindow.bind("<Right>", lambda x: nextWindow())
+    newWindow.bind("<Left>", lambda x: nextback())
     video_stream3()
 
 # newWindow.mainloop()

filters_image/image_filtering_face.py

@@ -20,74 +20,52 @@ def image_filtering_face(path_filter,path_img,center,width,height,up,left,counte
     detector = dlib.get_frontal_face_detector()
     faces = detector(image)
     if faces:
-        try:
-            for i in range(len(path_filter)):
-                return filter(image,gray_image,faces,filter_image[i],center[i],width[i],height[i],up[i],left[i])
-        except:
-            image = cv2.imread(path_img)
-            print("except")
-            return image
-
-    # key = cv2.waitKey(0)
-    # if key == ord('n'):
-    #     change_image(counte)
-    # 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])
-
+        # try:
+        for i in range(len(path_filter)):
+            return filter(image,gray_image,faces,filter_image[i],center[i],width[i],height[i],up[i],left[i])
+        # except:
+        #     image = cv2.imread(path_img)
 
+        #     return image
 
 
 def filter(image,gray_frame,faces,filter_image1,center,width,height,up=0,left=0):
     predictor_path = "../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
-        print("filter1")
-        return image
+        try:
+            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
+            print("filter1")
+        except:
+            print("except")
+    return image
         # cv2.imshow("Frame", image)
         # key = cv2.waitKey(0)
 

filters_live/video_filtering_face.py

@@ -7,9 +7,6 @@
 
 import os
 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("../filters_live/shape_predictor_68_face_landmarks.dat")
 counte=0
@@ -19,8 +16,10 @@ def video_filtering_face(path,center,width,height,up,left,path_back,blur,filter_
     for i in path:
         filter_image.append(cv2.imread(i))
     #
-    filter1 = np.zeros((rows, cols), np.uint8)
     _, frame = cap.read()
+    rows, cols, _ = frame.shape
+    filter1 = np.zeros((rows, cols), np.uint8)
+
     filter1.fill(0)
     gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
     faces = detector(frame)
@@ -86,7 +85,7 @@ def change_image(i):
     )
 
 mp_selfie_segmentation = mp.solutions.selfie_segmentation
-fsize = (520, 720)
+fsize = (480, 640)
 def background(frame,path,blur =1):