from cvs import *

print ('import tensorflow.....wait...')

import tensorflow as tf

import numpy as np

import time

imageSize = 257

width = imageSize

height = imageSize

def load_model(PATH_TO_CKPT):

detection_graph = tf.Graph()

with detection_graph.as_default():

od_graph_def = tf.GraphDef()

with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid:

serialized_graph = fid.read()

od_graph_def.ParseFromString(serialized_graph)

tf.import_graph_def(od_graph_def, name='')

return detection_graph

def resizeimg(img, width, height):

img = cvs.resize(img, (width,height))

img = img.astype(float)

img = img * (2.0 / 255.0) - 1.0

return img

def main():

cam=cvs.VideoCapture(0)

detection_graph = load_model("frozen_model.pb")

with detection_graph.as_default():

with tf.Session(graph=detection_graph) as sess:

image = detection_graph.get_tensor_by_name('image:0')

heatmaps=detection_graph.get_tensor_by_name('heatmap:0')

offsets=detection_graph.get_tensor_by_name('offset_2:0')

displacementFwd=detection_graph.get_tensor_by_name('displacement_fwd_2:0')

displacementBwd=detection_graph.get_tensor_by_name('displacement_bwd_2:0')

fcount=-1

start = time.time()

while True:

sleep(30)

img = cam.read()

if img is None :

sleep(50)

continue

fcount=fcount+1

# global lbs

lbs = 'Average FPS: '+ str(fcount / (time.time() - start))

cvs.setLbs(lbs)

input_image = resizeimg(img,width,height)

tmpimg = img

tmpimg = cv2.resize(tmpimg, (width,height))

input_image = np.array(input_image,dtype=np.float32)

input_image = input_image.reshape(1,width,height,3)

heatmaps_result,offsets_result,displacementFwd_result,displacementBwd_result = sess.run(

[heatmaps,offsets,displacementFwd,displacementBwd], feed_dict={ image: input_image } )

colors = [[255, 0, 0], [255, 170, 0], [255, 170, 0],[255, 255, 0], [255, 255, 0], [170, 255, 0], [170, 255, 0], [0, 255, 0],

[0, 255, 0], [0, 255, 170], [0, 255, 170], [0, 170, 255], [0, 170, 255], [0, 0, 255], [0, 0, 255],

[255, 0, 255], [255, 0, 255]]

pairs = [[5,6],[5,7],[6,8],[7,9],[8,10],[5,11],[6,12],[11,12],[11,13],[12,14],[13,15],[14,16]]

keypoint = []

ckeypoint = []

heatmaps_result = heatmaps_result[0]

aaaa= np.transpose(heatmaps_result,(2, 0, 1))

offsets_result=offsets_result[0]

bbb= np.transpose(offsets_result,(2, 0, 1))

for k in range(0,17):

heatmaps_result=aaaa[k]

maxheat=np.max(heatmaps_result)

re=np.where(heatmaps_result==maxheat)

ry=re[0][0]

rx=re[1][0]

offsets_resulty=bbb[0+k]

offsets_resultx=bbb[17+k]

ofx=int(offsets_resultx[ry][rx]+0.5)

ofy=int(offsets_resulty[ry][rx]+0.5)

px=(rx)*16+ofx

py=(ry)*16+ofy

if maxheat>0.7 :

cvs.circle(tmpimg, (int(px), int(py)), 3, colors[k], -1)

keypoint.append(int(px))

keypoint.append(int(py))

else :

keypoint.append(-1);

keypoint.append(-1);

ckeypoint.append(keypoint[0])

ckeypoint.append(keypoint[1])

for i in range(1,16,2):

# if keypoint[2*i]>keypoint[2*(i+1)] and keypoint[2*(i+1)]>0 :

# ckeypoint.append(keypoint[2*i+2])

# ckeypoint.append(keypoint[2*i+2+1])

# ckeypoint.append(keypoint[2*i])

# ckeypoint.append(keypoint[2*i+1])

# print ('chang:',i,'to',i+1)

# else :

ckeypoint.append(keypoint[2*i])

ckeypoint.append(keypoint[2*i+1])

ckeypoint.append(keypoint[2*i+2])

ckeypoint.append(keypoint[2*i+2+1])

for pair in pairs:

if ckeypoint[2*pair[0]]>0 and ckeypoint[2*pair[1]]>0 :

cvs.line(tmpimg,(ckeypoint[2*pair[0]],ckeypoint[2*pair[0]+1]),(ckeypoint[2*pair[1]],ckeypoint[2*pair[1]+1]),(0,0,255),1)

cvs.imshow(tmpimg)

print ('frames:',fcount)

class MyApp(App):

def __init__(self, *args):

super(MyApp, self).__init__(*args)

def idle(self):

#idle function called every update cycle

self.lbl.set_text(cvs.getLbs())

pass

def main(self):

#creating a container VBox type, vertical (you can use also HBox or Widget)

main_container = gui.VBox(width=360, height=680, style={'margin':'0px auto'})

self.aidcam = OpencvVideoWidget(self, width=340, height=480)

self.aidcam.style['margin'] = '10px'

self.aidcam.set_identifier("myimage_receiver")

main_container.append(self.aidcam)

#label show fps

self.lbl = gui.Label('This show FPS!', width=360, height=30,left='100px', margin='10px')

main_container.append(self.lbl)

return main_container

if __name__ == "__main__":

initcv(main)

startcv(MyApp)