OpenPoseImage.py

import cv2
import time
import numpy as np
import argparse
import math

font = cv2.FONT_HERSHEY_SIMPLEX
color = (255, 0, 0)
fontScale = 1
thickness = 2

parser = argparse.ArgumentParser(description='Run keypoint detection')
parser.add_argument("--device", default="cpu", help="Device to inference on")
parser.add_argument("--image_file", default="single.jpeg", help="Input image")

args = parser.parse_args()


MODE = "COCO"

if MODE is "COCO":
    protoFile = "pose/coco/pose_deploy_linevec.prototxt"
    weightsFile = "pose/coco/pose_iter_440000.caffemodel"
    nPoints = 18
    POSE_PAIRS = [ [1,0],[1,2],[1,5],[2,3],[3,4],[5,6],[6,7],[1,8],[8,9],[9,10],[1,11],[11,12],[12,13],[0,14],[0,15],[14,16],[15,17]]

elif MODE is "MPI" :
    protoFile = "pose/mpi/pose_deploy_linevec_faster_4_stages.prototxt"
    weightsFile = "pose/mpi/pose_iter_160000.caffemodel"
    nPoints = 15
    POSE_PAIRS = [[0,1], [1,2], [2,3], [3,4], [1,5], [5,6], [6,7], [1,14], [14,8], [8,9], [9,10], [14,11], [11,12], [12,13] ]


frame = cv2.imread(args.image_file)
frameCopy = np.copy(frame)
frameWidth = frame.shape[1]
frameHeight = frame.shape[0]
threshold = 0.1

net = cv2.dnn.readNetFromCaffe(protoFile, weightsFile)


net.setPreferableBackend(cv2.dnn.DNN_TARGET_CPU)
print("Using CPU device")


t = time.time()
# input image dimensions for the network
inWidth = 368
inHeight = 368
inpBlob = cv2.dnn.blobFromImage(frame, 1.0 / 255, (inWidth, inHeight),
                          (0, 0, 0), swapRB=False, crop=False)

net.setInput(inpBlob)

output = net.forward()
print("time taken by network : {:.3f}".format(time.time() - t))

H = output.shape[2]
W = output.shape[3]

# Empty list to store the detected keypoints
points = []

for i in range(nPoints):
    # confidence map of corresponding body's part.
    probMap = output[0, i, :, :]

    # Find global maxima of the probMap.
    minVal, prob, minLoc, point = cv2.minMaxLoc(probMap)
    
    # Scale the point to fit on the original image
    x = (frameWidth * point[0]) / W
    y = (frameHeight * point[1]) / H

    if prob > threshold : 
        cv2.circle(frameCopy, (int(x), int(y)), 8, (0, 255, 255), thickness=-1, lineType=cv2.FILLED)
        cv2.putText(frameCopy, "{}".format(i), (int(x), int(y)), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2, lineType=cv2.LINE_AA)

        # Add the point to the list if the probability is greater than the threshold
        points.append((int(x), int(y)))
    else :
        points.append(None)

# Draw Skeleton
for pair in POSE_PAIRS:
    partA = pair[0]
    partB = pair[1]

    if points[partA] and points[partB]:
        cv2.line(frame, points[partA], points[partB], (0, 255, 255), 2)
        cv2.circle(frame, points[partA], 8, (0, 0, 255), thickness=-1, lineType=cv2.FILLED)


lh = points[11]
lk = points[12]
la = points[13]
rh = points[8]
rk = points[9]
ra = points[10]

if ((lh is None) or (lk is None) or (la is None)):
    left_angle = "Cannot Determine!"

else:

    if (lk[0]-lh[0]) == 0:
        lh_lk = math.degrees(math.atan(abs(float('inf'))))
        lh_lk = 180 - lh_lk
    else:
        lh_lk = math.degrees(math.atan(abs(float(((-lk[1])-(-lh[1]))/(lk[0]-lh[0])))))
        lh_lk = 180 - lh_lk

    if (la[0]-lk[0]) == 0:
        lk_la = math.degrees(math.atan(abs(float('inf'))))
        lk_la = 180 - lk_la
    else:
        lk_la = math.degrees(math.atan(abs(float(((-la[1])-(-lk[1]))/(la[0]-lk[0])))))
        lk_la = 180 - lk_la

    left_angle = lh_lk + lk_la

if ((rh is None) or (rk is None) or (ra is None)):
    right_angle = "Cannot Determine!"

else:
    if (rk[0]-rh[0]) == 0:
        rh_rk = math.degrees(math.atan(abs(float('inf'))))
        rh_rk = 180 - rh_rk

    else:
        rh_rk = math.degrees(math.atan(abs(float(((-rk[1])-(-rh[1]))/(rk[0]-rh[0])))))
        rh_rk = 180 - rh_rk


    if (ra[0]-rk[0]) == 0:
        rk_ra = math.degrees(math.atan(abs(float('inf'))))
        rk_ra = 180 - rk_ra
    else:
        rk_ra = math.degrees(math.atan(abs(float(((-ra[1])-(-rk[1]))/(ra[0]-rk[0])))))
        rk_ra = 180 - rk_ra

    right_angle = rh_rk + rk_ra

Left_angle_text = ('Left Angle = '+str(left_angle))
right_angle_text = ('Right Angle = '+str(right_angle))

if ((abs(right_angle - 180) > 20) or (abs(left_angle - 180) > 20)):
    result = "Result:- Knock Knees"
else:
    result = "Result:- Normal Knees"


cv2.putText(frame, Left_angle_text, (0, 75), font, fontScale, color, thickness, cv2.LINE_AA)
cv2.putText(frame, right_angle_text, (0, 150), font, fontScale, color, thickness, cv2.LINE_AA)
cv2.putText(frame, result, (0, 300), font, fontScale, color, thickness, cv2.LINE_AA)

cv2.imshow('Output-Keypoints', frameCopy)
cv2.imshow('Output-Skeleton', frame)


cv2.imwrite('Output-Keypoints.jpg', frameCopy)
cv2.imwrite('Output-Skeleton.jpg', frame)

print("Total time taken : {:.3f}".format(time.time() - t))

cv2.waitKey(0)