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Integration_2_1.py
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Integration_2_1.py
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import os
import cv2
from darkflow.net.build import TFNet
#from finding_lane_1 import detect_lanes_img
import numpy as np
#import serial
import time
import json
def draw_boxes_image(colors,results,frame):
#arduino = serial.Serial('COM3',9600)
json_file = []
for (color, result) in zip (colors, results):
#Convert confidence level to int from float
json_temp = dict(result)
json_conf = json_temp['confidence']
json_conf = int(round(json_conf*100))
json_temp['confidence'] = json_conf
#till here
json_file.append(json_temp)
tl = (result['topleft']['x'], result['topleft']['y'])
br = (result['bottomright']['x'], result['bottomright']['y'])
confidence = result['confidence']
label = result['label']
text = '{}: {:.1f}%'.format(label,confidence*100 )
frame = cv2.rectangle(frame, tl, br, color, 5)
frame = cv2.putText(frame, text, tl, cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 0), 2)
'''
if (arduino.isOpen()):
word = label + '\n'
bword = bytes(word,'utf-8')
arduino.write(bword)
'''
cv2.imshow ("predicted",frame)
with open('data.json','w') as outfile:
json.dump(json_file,outfile)
#arduino.close()
'''
def send_to_arduino(word):
arduino = serial.Serial('COM3',9600)
if (arduino.isOpen()):
word = word +'\n'
bword = bytes(word,'utf-8')
arduino.write(bword)
def result_to_word(result):
word = '{}'.format(result['label'])
return word
'''
# M A I N P R O G R A M
options = {
'model': 'cfg/yolo-voc.cfg',
'load': 'bin/yolo-voc.weights',
'threshold': 0.3,
'gpu': 0.5
}
tfnet = TFNet(options)
fileRead = input('Enter Image/Video/Webcam : ')
filename , fileExtension = os.path.splitext(fileRead)
colors = [tuple(255 * np.random.rand(3)) for _ in range(10)]
if (fileExtension == '.jpg') :
frame = cv2.imread (fileRead)
# frame = detect_lanes_img(frame)
results = tfnet.return_predict(frame)
draw_boxes_image(colors,results,frame)
cv2.waitKey(0)
cv2.destroyAllWindows()
elif (fileExtension == '.mp4') :
capture = cv2.VideoCapture(fileRead)
capture.set(cv2.CAP_PROP_FRAME_WIDTH, 1920)
capture.set(cv2.CAP_PROP_FRAME_HEIGHT, 1080)
frame_number = 1
json_file = {}
px_cm_person = 6047
while True:
stime = time.time()
ret, frame = capture.read()
results = tfnet.return_predict(frame)
if ret:
#
#frame = detect_lanes_img(frame)
json_frame = []
frame_str = 'frame {}'.format(frame_number)
for (color, result) in zip (colors, results):
#Convert confidence level to int from float
json_temp = dict(result)
json_conf = json_temp['confidence']
json_conf = int(round(json_conf*100))
json_temp['confidence'] = json_conf
json_frame.append(json_temp)
tl = (result['topleft']['x'], result['topleft']['y'])
br = (result['bottomright']['x'], result['bottomright']['y'])
confidence = result['confidence']
label = result['label']
coorX= result['topleft']['x'] + result['bottomright']['x']/2
coorY= result['topleft']['y'] + result['bottomright']['y']/2
centroids = (coorX,coorY)
if (label == 'person'):
width_person = result['bottomright']['y'] - result['topleft']['y']
dist_person = px_cm_person/width_person
text = '{}: {:.1f}%'.format(label,dist_person )
else :
text = '{}: {:.1f}%'.format(label,confidence*100 )
frame = cv2.rectangle(frame, tl, br, color, 5)
frame = cv2.putText(frame, text, tl, cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 0), 2)
'''
if (arduino.isOpen()):
word = label + '\n'
bword = bytes(word,'utf-8')
arduino.write(bword)
'''
json_file[frame_str] = json_frame
frame_number = frame_number + 1
cv2.imshow ("predicted",frame)
print('FPS {:.1f}'.format(1 / (time.time() - stime)))
if cv2.waitKey(1) & 0xFF == ord('q'):
break
capture.release()
cv2.destroyAllWindows()
with open('data.json','w') as outfile:
json.dump(json_file,outfile)
print('Jumlah Frame :{}'.format(frame_number))
#arduino.close()
elif (fileExtension == '.0' or fileExtension == '.1' ) :
fileExtension = fileExtension[-1]
cam = int (fileExtension)
capture = cv2.VideoCapture(cam)
frame_number = 1
json_file = {}
px_cm_person = 20000
while True:
stime = time.time()
ret, frame = capture.read()
results = tfnet.return_predict(frame)
if ret:
#frame = detect_lanes_img(frame)
json_frame = []
frame_str = 'frame {}'.format(frame_number)
for (color, result) in zip (colors, results):
#Convert confidence level to int from float
json_temp = dict(result)
json_conf = json_temp['confidence']
json_conf = int(round(json_conf*100))
json_temp['confidence'] = json_conf
json_frame.append(json_temp)
tl = (result['topleft']['x'], result['topleft']['y'])
br = (result['bottomright']['x'], result['bottomright']['y'])
confidence = result['confidence']
label = result['label']
coorX= result['topleft']['x'] + result['bottomright']['x']/2
coorY= result['topleft']['y'] + result['bottomright']['y']/2
centroids = (coorX,coorY)
frame = cv2.rectangle(frame, tl, br, color, 5)
if (label == 'person'):
width_person = result['bottomright']['y'] - result['topleft']['y']
dist_person = px_cm_person/width_person
dist_person = format(dist_person, '.2f')
print(dist_person)
text2 = '{}: {}cm'.format(label, dist_person )
print(text2)
frame = cv2.putText(frame, text2, tl, cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 0), 2)
else :
text = '{}: {:.1f}%'.format(label,confidence*100 )
frame = cv2.putText(frame, text, tl, cv2.FONT_HERSHEY_COMPLEX, 1, (0, 0, 0), 2)
'''
if (arduino.isOpen()):
word = label + '\n'
bword = bytes(word,'utf-8')
arduino.write(bword)
'''
json_file[frame_str] = json_frame
frame_number = frame_number + 1
cv2.imshow ("predicted",frame)
print('FPS {:.1f}'.format(1 / (time.time() - stime)))
if cv2.waitKey(1) & 0xFF == ord('q'):
break
capture.release()
cv2.destroyAllWindows()
with open('data.json','w') as outfile:
json.dump(json_file,outfile)
print('Jumlah Frame :{}'.format(frame_number))
#arduino.close()
elif (fileRead == 'exit'):
pass
else:
print('Input Invalid')