send.py

import cv2 as cv
import numpy as np
import argparse

import socket
import time

serverAddress = ('192.168.0.21', 7070)
serverSocket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)


def translate(sensor_val, in_from, in_to, out_from, out_to):
    out_range = out_to - out_from
    in_range = in_to - in_from
    in_val = sensor_val - in_from
    val=(float(in_val)/in_range)*out_range
    out_val = out_from+val
    return out_val

parser = argparse.ArgumentParser()
parser.add_argument('--input', help='Path to image or video. Skip to capture frames from camera')
parser.add_argument('--thr', default=0.1, type=float, help='Threshold value for pose parts heat map')
parser.add_argument('--width', default=368, type=int, help='Resize input to specific width.')
parser.add_argument('--height', default=368, type=int, help='Resize input to specific height.')

args = parser.parse_args()

BODY_PARTS = { "Nose": 0, "Neck": 1, "RShoulder": 2, "RElbow": 3, "RWrist": 4,
               "LShoulder": 5, "LElbow": 6, "LWrist": 7, "RHip": 8, "RKnee": 9,
               "RAnkle": 10, "LHip": 11, "LKnee": 12, "LAnkle": 13, "REye": 14,
               "LEye": 15, "REar": 16, "LEar": 17, "Background": 18 }

POSE_PAIRS = [ ["Neck", "RShoulder"], ["Neck", "LShoulder"], ["RShoulder", "RElbow"],
               ["RElbow", "RWrist"], ["LShoulder", "LElbow"], ["LElbow", "LWrist"],
               ["Neck", "RHip"], ["RHip", "RKnee"], ["RKnee", "RAnkle"], ["Neck", "LHip"],
               ["LHip", "LKnee"], ["LKnee", "LAnkle"], ["Neck", "Nose"], ["Nose", "REye"],
               ["REye", "REar"], ["Nose", "LEye"], ["LEye", "LEar"] ]

inWidth = args.width
inHeight = args.height

net = cv.dnn.readNetFromTensorflow("graph_opt.pb")

cap = cv.VideoCapture(args.input if args.input else 0)

test1=0
eyeWidth=125

def FocalLength(width_in_rf_image):
    focal_length = (width_in_rf_image* 60.0)/ 8.0
    return focal_length
    
def Distance_finder(Focal_Length, real_face_width, face_width_in_frame):
    distance = (real_face_width * Focal_Length)/face_width_in_frame
    return distance

while cv.waitKey(1) < 0:
    hasFrame, frame = cap.read()
    frame = cv.flip(frame, 1)
    if not hasFrame:
        cv.waitKey()
        break

    frameWidth = frame.shape[1]
    frameHeight = frame.shape[0]
    
    net.setInput(cv.dnn.blobFromImage(frame, 1.0, (inWidth, inHeight), (127.5, 127.5, 127.5), swapRB=True, crop=False))
    out = net.forward()
    out = out[:, :19, :, :]  # MobileNet output [1, 57, -1, -1], we only need the first 19 elements

    assert(len(BODY_PARTS) == out.shape[1])

    points = []
    for i in range(len(BODY_PARTS)):
        # Slice heatmap of corresponging body's part.
        heatMap = out[0, i, :, :]

        # Originally, we try to find all the local maximums. To simplify a sample
        # we just find a global one. However only a single pose at the same time
        # could be detected this way.
        _, conf, _, point = cv.minMaxLoc(heatMap)
        x = (frameWidth * point[0]) / out.shape[3]
        y = (frameHeight * point[1]) / out.shape[2]
        if((conf > args.thr)):
            cv.ellipse(frame, (int(x), int(y)), (3, 3), 0, 0, 360, (0, 0, 255), cv.FILLED)
            if(i==1):
                test1 =translate(int(x),100,500,0,8)
                bytes_val = bytes(str(test1), 'utf-8')
                serverSocket.sendto(bytes_val, serverAddress)
        else:
            cv.ellipse(frame, (int(x), int(y)), (3, 3), 0, 0, 360, (255, 0, 0), cv.FILLED)
            #print(str(int(x))+">>"+str(test1))
        points.append((int(x), int(y)) if conf > args.thr else None)
    eyeWidth=points[15][0]-points[14][0]

    """
    for pair in POSE_PAIRS:
        partFrom = pair[0]
        partTo = pair[1]
        assert(partFrom in BODY_PARTS)
        assert(partTo in BODY_PARTS)

        idFrom = BODY_PARTS[partFrom]
        idTo = BODY_PARTS[partTo]

        if points[idFrom] and points[idTo]:
            cv.line(frame, points[idFrom], points[idTo], (0, 255, 0), 3)
            cv.ellipse(frame, points[idFrom], (3, 3), 0, 0, 360, (0, 0, 255), cv.FILLED)
            cv.ellipse(frame, points[idTo], (3, 3), 0, 0, 360, (0, 0, 255), cv.FILLED)
"""
    t, _ = net.getPerfProfile()
    freq = cv.getTickFrequency() / 1000
    cv.putText(frame, '%.2fms' % (t / freq), (10, 20), cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255))
    cv.putText(frame, 'Neck: '+str(test1), (10, 40), cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255))

    
    
    cv.putText(frame, 'Z: '+str(Distance_finder(FocalLength(125), 8, eyeWidth)), (10, 60), cv.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255))
    
    cv.imshow('PoseDetection', frame)