def produce_data_samp(raw_input_queue, detection_queue, time_control_queue, filename, resolution):
if filename == "no_filename":
cap = cv2.VideoCapture(0)
else:
cap = cv2.VideoCapture(filename)
cap.set(3, resolution[0])
cap.set(4, resolution[1])
while True:
process_start = time.time()
# Read the frame
valid, img = cap.read()
if not valid:
print("ERROR: Image Error on VideoCapture\n")
log(time.asctime(), "produce_data_samp;", "No image input")
break
time_control_queue.put(time.time())
raw_input_queue.put(img)
detection_queue.put(img)
log(time.asctime(), "produce_data_samp;", "Raw image has been captured and stored")
# time.sleep(0.01)
# Stop if escape key is pressed
k = cv2.waitKey(1) & 0xff
if k == 27:
break
process_duration = time.time() - process_start
log_process_duration("produce_data_samp", process_duration)
# Release the VideoCapture object
cap.release()
def modify_alt(processed_image_pipe_out, faces_pipe_out,
time_control_pipe_out):
# create window
cv2.namedWindow('image_display', cv2.WINDOW_AUTOSIZE)
start_time = time.time()
mode = 1
number_of_seconds = 1
counter = 0
frame_number = 0
fps = "FPS: "
while True:
process_start = time.time()
image = processed_image_pipe_out.recv()
faces = faces_pipe_out.recv()
for (x, y, w, h) in faces:
if mode < 0:
cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)
else:
image = blur_fragment(image, x, y, w, h)
counter += 1
if (time.time() - start_time) > number_of_seconds:
fps = "FPS: "
fps += str(round(counter / (time.time() - start_time)))
counter = 0
start_time = time.time()
cv2.putText(image, fps, (0, 30), cv2.FONT_HERSHEY_SIMPLEX, 1,
(255, 255, 255), 2)
cv2.imshow('image_display', image)
time_since_captured = time_control_pipe_out.recv()
difference = time.time() - time_since_captured
frame_number += 1
log_delay(frame_number, difference)
log(time.asctime(), "modify_alt;", "Effect applied and image shown")
k = cv2.waitKey(1) & 0xff
if k == 27:
cv2.destroyAllWindows()
break
elif k == 32:
mode *= -1
process_duration = time.time() - process_start
log_process_duration("modify_alt", process_duration)
time_control_pipe_out.close()
processed_image_pipe_out.close()
faces_pipe_out.close()
def detect_faces_std(in_queue, out_queue, faces_queue):
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
while True:
process_start = time.time()
image = in_queue.get()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray, 1.1, 4)
faces_queue.put(faces)
out_queue.put(image)
log(time.asctime(), "detect_faces_std;",
"Face detection on frame completed")
k = cv2.waitKey(1) & 0xff
if k == 27:
break
process_duration = time.time() - process_start
log_process_duration("detect_faces_std", process_duration)
def detect_faces_samp(queue, faces_queue, sampling_step):
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
counter = 0
while True:
process_start = time.time()
image = queue.get()
if counter == 0:
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray, 1.1, 4)
log(time.asctime(), "detect_faces_samp;",
"Face detection on frame completed")
faces_queue.put(faces)
counter += 1
counter %= sampling_step
k = cv2.waitKey(1) & 0xff
if k == 27:
break
process_duration = time.time() - process_start
log_process_duration("detect_faces_samp", process_duration)
def detect_faces_alt(raw_image_pipe_out, processed_image_pipe_in,
faces_pipe_in):
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
while True:
process_start = time.time()
image = raw_image_pipe_out.recv()
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray, 1.1, 4)
faces_pipe_in.send(faces)
processed_image_pipe_in.send(image)
log(time.asctime(), "detect_faces_alt;",
"Face detection on frame completed")
k = cv2.waitKey(1) & 0xff
if k == 27:
break
process_duration = time.time() - process_start
log_process_duration("detect_faces_alt", process_duration)
raw_image_pipe_out.close()
processed_image_pipe_in.close()
faces_pipe_in.close()