Machine-Learning-Exercise-Counting-Classification/datasetRecorder_GUI.py at master · vinvinz/Machine-Learning-Exercise-Counting-Classification · GitHub

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import tkinter as tk
from tkinter import *
import customtkinter as ck
from tkinter import ttk, filedialog
from tkinter.filedialog import askopenfile
import os
import threading

import cv2
import mediapipe as mp
import time
import pandas as pd
import numpy as np

from record_dataset import writeCSV, export_landmark

from PIL import Image, ImageTk

mp_drawing = mp.solutions.drawing_utils
mp_drawing_styles = mp.solutions.drawing_styles
mp_pose = mp.solutions.pose
pose = mp_pose.Pose(min_tracking_confidence=0.9, min_detection_confidence=0.9)


class datasetGUI:

    def __init__(self):
        self.root = tk.Tk()
        self.root.geometry("720x540")

        self.csv_filepath = "newdataset.csv"
        self.dataset_label = ""

        self.frame = tk.Frame(height=380, width=720)
        self.frame.place(x=0, y=0)
        self.lmain = tk.Label(self.frame)
        self.lmain.place(x=0, y=0)

        self.utilityComponents()

        self.root.update_idletasks()

        self.root.mainloop()

    def open_file(self):
        file = filedialog.askopenfile(mode='r', filetypes=[('All files', '*.*')])
        if file:
            filepath = os.path.relpath(file.name)
            Label(self.root, text="The File is located at : " + str(filepath), font=('Aerial 11')).place(x=0, y=0)
            self.openVideo(filepath)

    def open_csv(self):
        file = filedialog.askopenfile(mode='r', filetypes=[('All files', '*.*')])
        if file:
            filepath = os.path.relpath(file.name)
            self.csv_filepath = filepath
            Label(self.root, text="File selected : " + str(filepath), font=('Aerial 11')).place(x=220, y=430)

    def record_landmarks(self, result, label, csvFilePath):
        print("Recording Landmarks...")
        try:
            label = float(label)
            export_landmark(result, label, csvFilePath)
        except Exception as e:
            print(e)
            pass


    def utilityComponents(self):
        ttk.Button(self.root, text="Browse", command=self.open_file).place(x=120, y=390)
        label = Label(self.root, text="Open Video File:", font=('Arial 11'))
        label.place(x=0, y=390)

    def pause(self):
        for i in range(1):

            self.root.update_idletasks()

            time.sleep(1)

    def openVideo(self, vidpath):
        cap = cv2.VideoCapture(vidpath)

        label = Label(self.root, text="Choose CSV File:", font=('Arial 11'))
        label.place(x=0, y=430)

        ttk.Button(self.root, text="Pause", command=self.pause).place(x=330, y=470)
        # ttk.Button(self.root, text="Pause", command=self.run_thread).place(x=330, y=500)

        Label(self.root, text="Row Label: ", font=('Arial 11')).place(x=0, y=470)
        self.dataset_label = tk.Entry(self.root, width=10, textvariable = 0)
        self.dataset_label.place(x=100, y=470)


        def detect():
            ret, frame = cap.read()
            image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
            image = cv2.resize(image, (720, 380))
            self.results = pose.process(image)
            mp_drawing.draw_landmarks(image, self.results.pose_landmarks, mp_pose.POSE_CONNECTIONS,
                mp_drawing.DrawingSpec(color=(0,255,255), thickness=0, circle_radius=0),
                mp_drawing.DrawingSpec(color=(255,255,0), thickness=2, circle_radius=1))
            img = image[:, :960, :]
            imgarr = Image.fromarray(img)
            imgtk = ImageTk.PhotoImage(imgarr)
            self.lmain.imgtk = imgtk
            self.lmain.configure(image=imgtk)
            self.lmain.after(10, detect)

        ttk.Button(self.root, text="Record Data", command=lambda: self.record_landmarks(result=self.results, label=self.dataset_label.get(), csvFilePath=self.csv_filepath)).place(x=0, y=490)

        ttk.Button(self.root, text="CSV Location", command=self.open_csv).place(x=130, y=430)

        detect()
        # with mp_pose.Pose(
        #         min_detection_confidence=0.8,
        #         min_tracking_confidence=0.8) as pose:
        #     while cap.isOpened():
        #         success, image = cap.read()
        #         if not success:
        #             print("Ignoring empty camera frame.")
        #             # If loading a video, use 'break' instead of 'continue'.
        #             continue
        #         ret, frame = cap.read()
        #         image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
        #         image = cv2.resize(image, (720, 380))
        #         results = pose.process(image)
        #         mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS,
        #             mp_drawing.DrawingSpec(color=(0,255,255), thickness=0, circle_radius=0),
        #             mp_drawing.DrawingSpec(color=(255,255,0), thickness=2, circle_radius=1))

        #         img = image[:, :720, :]
        #         imgarr = Image.fromarray(img)
        #         imgtk = ImageTk.PhotoImage(imgarr)
        #         self.lmain.imgtk = imgtk
        #         self.lmain.configure(image=imgtk)
        #         self.lmain.after(10, self.openVideo(vidpath=filepath))


datasetGUI()