def get_images():
clear_folder(datasetPath + "images")
clear_folder(datasetPath + "projections")
try:
uploaded_files = request.files.getlist("file[]")
for idx, file in enumerate(uploaded_files):
file.save(dst=datasetPath + "images/" + file.filename + ".jpg")
camera.main(datasetPath)
pmvs.main(datasetPath)
mesh.main("expansion_pointcloud.ply")
print('DONE')
except:
print(exc_info())
return jsonify({"message": "fail"})
return jsonify({"message": "done"})
def play_move(self):
computer_move = get_computer_move()
human_move = camera.main()
winner = get_match_winner(human_move, computer_move)
if winner == -1:
self.human_wins += 1
elif winner == 1:
self.computer_wins += 1
self.games_played += 1
result = {1: "LOSE", 0: "TIE", -1: "WIN"}[winner]
self.win_lose_text.setText(
f"You played {get_full_move(human_move).upper()} "
f"and the computer played {get_full_move(computer_move).upper()} "
f"which means you {result}!\n\n"
f"Computer wins: {self.computer_wins}\n"
f"Human wins: {self.human_wins}\n"
f"Games played: {self.games_played}")
self.win_lose_text.adjustSize()
def callback():
#camera.main(camera.parse_arguments(['ALL', 'pre-trained/20170512-110547.pb', 'classifier.pkl', '--interval=1', '--minsize=80', self]))
camera.main('ALL', 'pre-trained/20170512-110547.pb',
'classifier.pkl', 3, 80, captureMode, self)
def callback():
camera.main('ALL', 'pre-trained/20170512-110547.pb', 'classifier.pkl', 1, 80, captureMode, self)
import os
import face_recognition
import camera, time
dataset = os.listdir('images')
count = 0
current_image = camera.main()
print("Image obtained...")
print()
#print(current_image)
#current_image=face_recognition.load_image_file('images/'+dataset[7])
encoded_current_image = face_recognition.face_encodings(current_image)
#print(encoded_current_image)
print("Authenticating...")
for image in dataset:
check_image = face_recognition.load_image_file('images/' + image)
faces = face_recognition.face_encodings(check_image)
for face in faces:
encoded_check_image = face
#print(encoded_check_image)
result = face_recognition.compare_faces(encoded_current_image,
encoded_check_image)
#print(result)
if len(result) == 0:
continue
def detect():
return Response(gen2(main()),
mimetype='multipart/x-mixed-replace; boundary=frame')
def video_feed():
return Response(gen(main()),
mimetype='multipart/x-mixed-replace; boundary=frame')
import camera import painter camera.main() painter.main()