PersonalAI/personalai_dash.py at main · devhttps/PersonalAI · GitHub

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import cv2
import streamlit as st
import numpy as np
import mediapipe as mp
from mediapipe.tasks import python
from mediapipe.framework.formats import landmark_pb2
import queue
import pandas as pd
from personal_ai import *
from time import time, sleep

st.set_page_config(
    layout="wide"
)
# personalAI = PersonalAI("IMG_2149.mov")
personalAI = PersonalAI("IMG_2149.mov")
personalAI.run()

st.sidebar.title("AI Personal Trainer")
display_charts = st.sidebar.checkbox('Display charts', value=True)
reset = st.sidebar.button("Reset")

col1, col2 = st.columns(2)
# run = st.sidebar.checkbox('Ligar Webcam')
# landmarks = st.sidebar.checkbox('Mapeamento facial')

frame, landmarks, ts = personalAI.image_q.get()
df_nodes_x = pd.DataFrame()
df_nodes_y = pd.DataFrame()

placeholder = st.empty()
c = 0
status = "relaxed"
useful_points = [11, 12, 24, 23, 14, 13]

count = 0

while True:
    frame, landmarks, ts = personalAI.image_q.get()
    if ts == "done": break

    if len(landmarks.pose_landmarks) > 0:
        frame, elbow_angle = personalAI.draw_angle(frame, landmarks, 12, 14, 16)
        frame, hip_angle = personalAI.draw_angle(frame, landmarks, 11, 23, 25)

        df_y = pd.DataFrame([i.y for i in [i for i in landmarks.pose_landmarks[0]]]).rename(columns={0: ts}).transpose()
        df_nodes_y = pd.concat([df_nodes_y, df_y])

        # Pushup Logic
        if elbow_angle > 150 and hip_angle > 170:
            status = "ready"
            dir = "down"

        if status == "ready":
            if dir == "down" and elbow_angle < 60:
                dir = "up"
                count += 0.5
            if dir == "up" and elbow_angle > 100:
                dir = "down"
                count += 0.5

        # frame = cv2.putText(frame, status, (70, 70),
        #                 cv2.FONT_HERSHEY_PLAIN, 5, (20,20,20), 3)
        # frame = cv2.putText(frame, str(int(count)), (frame.shape[1]-100, 100),
        #                 cv2.FONT_HERSHEY_PLAIN, 8, (20,20,20), 3)

        with placeholder.container():
            col1, col2 = st.columns([0.4, 0.6])
            status_m = f":red[{status}]" if status == "relaxed" else f":green[{status}]"
            col2.markdown("### **Status:** " + status_m)
            col2.markdown(f"### Count: {int(count)}")

            col2.divider()
            col1.image(frame)

            if c % 2 == 0 and display_charts:
                col2.line_chart(df_nodes_y[useful_points])
            c += 1