r
/
face_recognition
1
0
Fork 0
Code Issues Pull Requests Releases 2 Activity
Browse Source

Save images with spacebar

testqueue
Ruben van de Ven 2 years ago
parent
e7ff1ac0cb
commit
e21376465f
3 changed files with 75 additions and 77 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 1
      .gitignore
  2. 147
      face_recognition/comparison.py
  3. 4
      mirror.py

1
.gitignore vendored
Unescape View File

@ -1,2 +1,3 @@ @@ -1,2 +1,3 @@
venv/
*.pyc
saves/

147
face_recognition/comparison.py
Unescape View File

@ -5,6 +5,7 @@ import logging @@ -5,6 +5,7 @@ import logging
import argparse
import numpy as np
import time
import datetime
from PIL import ImageFont, ImageDraw, Image
import os
@ -34,17 +35,22 @@ class Result(): @@ -34,17 +35,22 @@ class Result():
return self
def draw_detections(self):
color = draw_colors[self.algorithm]
cv2_im_rgb = cv2.cvtColor(self.visualisation,cv2.COLOR_BGR2RGB)
# Pass the image to PIL
pil_im = Image.fromarray(cv2_im_rgb)
draw = ImageDraw.Draw(pil_im, 'RGBA')
self.draw_detections_on(draw)
return cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
def draw_detections_on(self, draw: ImageDraw):
'''
Draw on a specified canvas
'''
color = draw_colors[self.algorithm]
for detection in self.detections:
self.draw_detection(draw, detection, color)
self.visualisation = cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
def draw_detection(self, draw: ImageDraw, detection: dict, color: tuple):
width = 2
@ -68,51 +74,8 @@ class Result(): @@ -68,51 +74,8 @@ class Result():
color = tuple(color)
draw.rectangle((detection['startX'], detection['startY'], detection['endX'], detection['endY']), outline=color, width=width)
# cv2.rectangle(rect_img, (0, 0),
# (sub_img.shape[1]-int(width/2), sub_img.shape[0]-int(width/2)),
# color, width)
def draw_detections_cv2(self):
color = draw_colors[self.algorithm]
for detection in self.detections:
self.draw_detection(detection, color)
def draw_detection_cv2(self, detection, color=(0,0,255)):
# First we crop the sub-rect from the image
sub_img = self.visualisation[detection['startY']:detection['endY'], detection['startX']:detection['endX']]
rect_img = sub_img.copy()
width = 2
cv2.rectangle(rect_img, (0, 0),
(sub_img.shape[1]-int(width/2), sub_img.shape[0]-int(width/2)),
color, width)
# white_rect = np.ones(sub_img.shape, dtype=np.uint8) * 255
# filter out weak detections by ensuring the `confidence` is
# greater than the minimum confidence
if detection['confidence'] > self.confidence_threshold:
# draw the bounding box of the face along with the associated
# probability
text = "{:.2f}%".format(detection['confidence'] * 100)
y = detection['startY'] - 10 if detection['startY'] - 10 > 10 else detection['startY'] + 10
# cv2.rectangle(image, (startX, startY), (endX, endY),
# color, 2)
cv2.putText(self.visualisation, text, (detection['startX'], y),
cv2.FONT_HERSHEY_SIMPLEX, 0.45, color, 2, lineType = cv2.LINE_AA)
alpha = 1
else:
# At least 10% opacity
alpha = max(.3, detection['confidence'])
res = cv2.addWeighted(sub_img, 1-alpha, rect_img, alpha, 1.0)
# Putting the image back to its position
self.visualisation[detection['startY']:detection['endY'], detection['startX']:detection['endX']] = res
def resize(self, width, height):
# TODO resize to new target incl all detections
img = self.visualisation
@ -437,16 +400,22 @@ def process3_haar(in_q, out_q, cascade_file): @@ -437,16 +400,22 @@ def process3_haar(in_q, out_q, cascade_file):
# print(img)
out_q.put(result)
def display(image_res, q1, q2, q3, q4, fullscreen = False):
prev_image1 = np.zeros((image_res[1],image_res[0],3), np.uint8)
prev_image2 = np.zeros((image_res[1],image_res[0],3), np.uint8)
prev_image3 = np.zeros((image_res[1],image_res[0],3), np.uint8)
prev_image4 = np.zeros((image_res[1],image_res[0],3), np.uint8)
def display(image_res, q1, q2, q3, q4, fullscreen, output_dir):
logger = logging.getLogger('display')
empty_image = np.zeros((image_res[1],image_res[0],3), np.uint8)
prev_image1 = None
prev_result2 = None
prev_result3 = None
prev_result4 = None
if fullscreen:
cv2.namedWindow("output", cv2.WND_PROP_FULLSCREEN)
cv2.setWindowProperty("output",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)
override_image = None
override_until = None
while True:
logging.debug('r')
try:
@ -454,53 +423,79 @@ def display(image_res, q1, q2, q3, q4, fullscreen = False): @@ -454,53 +423,79 @@ def display(image_res, q1, q2, q3, q4, fullscreen = False):
image1 = cv2.resize(image1, (image_res[0], image_res[1]))
prev_image1 = image1
except Empty as e:
image1 = prev_image1
image1 = prev_image1 if prev_image1 is not None else empty_image
try:
result2 = q2.get_nowait()
result2 = result2.resize(image_res[0], image_res[1])
result2.draw_detections()
image2 = result2.visualisation
# image2 = cv2.resize(image2, (image_res[0], image_res[1]))
prev_image2 = image2
prev_result2 = result2
except Empty as e:
image2 = prev_image2
result2 = prev_result2
finally:
image2 = result2.draw_detections() if result2 is not None else empty_image
try:
result3 = q3.get_nowait()
result3 = result3.resize(image_res[0], image_res[1])
result3.draw_detections()
image3 = result3.visualisation
# image3 = cv2.resize(image3, (image_res[0], image_res[1]))
prev_image3 = image3
prev_result3 = result3
except Empty as e:
image3 = prev_image3
result3 = prev_result3
finally:
image3 = result3.draw_detections() if result3 is not None else empty_image
try:
result4 = q4.get_nowait()
result4 = result4.resize(image_res[0], image_res[1])
result4.draw_detections()
image4 = result4.visualisation
# image4 = cv2.resize(image4, (image_res[0], image_res[1]))
prev_image4 = image4
prev_result4 = result4
except Empty as e:
image4 = prev_image4
result4 = prev_result4
finally:
image4 = result4.draw_detections() if result4 is not None else empty_image
if override_image is not None and override_until > time.time():
cv2.imshow("output", override_image)
else:
override_image = None
img_concate_Verti1 = np.concatenate((image1,image2),axis=0)
img_concate_Verti2 = np.concatenate((image3,image4),axis=0)
grid_img = np.concatenate((img_concate_Verti1,img_concate_Verti2),axis=1)
cv2.imshow("output", grid_img)
img_concate_Verti1 = np.concatenate((image1,image2),axis=0)
img_concate_Verti2 = np.concatenate((image3,image4),axis=0)
grid_img = np.concatenate((img_concate_Verti1,img_concate_Verti2),axis=1)
cv2.imshow("output", grid_img)
# Hit 'q' on the keyboard to quit!
key = cv2.waitKey(1) & 0xFF
if key == ord('q'):
break
if key == ord(' '):
# TODO save frame
pass
def main(camera_id, rotate, fullscreen, cascade_file):
# TODO wait for frame to be processed. Eg. if I move and make a pic, it should use the last frame...
output_res = (image_res[0] *2, image_res[1] * 2)
pil_im = Image.fromarray(cv2.cvtColor(image1, cv2.COLOR_BGR2RGB))
pil_im = pil_im.resize(output_res)
draw = ImageDraw.Draw(pil_im, 'RGBA')
if result2 is not None:
result2.resize(output_res[0], output_res[1]).draw_detections_on(draw)
if result3 is not None:
result3.resize(output_res[0], output_res[1]).draw_detections_on(draw)
if result4 is not None:
result4.resize(output_res[0], output_res[1]).draw_detections_on(draw)
override_image = cv2.cvtColor(np.array(pil_im), cv2.COLOR_RGB2BGR)
override_until = time.time() + 5
logger.info("Show frame until %f", override_until)
# save images:
name = datetime.datetime.now().isoformat(timespec='seconds')
cv2.imwrite(os.path.join(output_dir, f'{name}.png'),override_image)
cv2.imwrite(os.path.join(output_dir, f'{name}-hog.png'),result2.visualisation)
cv2.imwrite(os.path.join(output_dir, f'{name}-dnn.png'),result3.visualisation)
cv2.imwrite(os.path.join(output_dir, f'{name}-haar.png'),result4.visualisation)
def main(camera_id, rotate, fullscreen, cascade_file, output_dir):
image_size = (int(1920/2), int(1080/2))
if not os.path.exists(cascade_file):
raise RuntimeError(f"Cannot load OpenCV haar-cascade file '{cascade_file}'")
if not os.path.isdir(output_dir):
raise RuntimeError(f"Non-existent directory to store files '{output_dir}'")
is_rotated_90 = rotate in [cv2.ROTATE_90_CLOCKWISE, cv2.ROTATE_90_COUNTERCLOCKWISE]
@ -519,7 +514,7 @@ def main(camera_id, rotate, fullscreen, cascade_file): @@ -519,7 +514,7 @@ def main(camera_id, rotate, fullscreen, cascade_file):
q_process3 = Queue(maxsize=1)
p1 = Process(target=record, args=(camera_id, q_webcam1, q_webcam2,q_webcam3,q_webcam4, image_size, rotate))
p2 = Process(target=display, args=(image_size, q_webcam1, q_process1, q_process2, q_process3, fullscreen ))
p2 = Process(target=display, args=(image_size, q_webcam1, q_process1, q_process2, q_process3, fullscreen, output_dir ))
p3 = Process(target=process1_hog, args=(q_webcam2, q_process1,))
p4 = Process(target=process2_dnn, args=(q_webcam3, q_process2,))
p5 = Process(target=process3_haar, args=(q_webcam4, q_process3,cascade_file))

4
mirror.py
Unescape View File

@ -15,6 +15,8 @@ if __name__ == '__main__': @@ -15,6 +15,8 @@ if __name__ == '__main__':
help='Rotate counter clockwise')
parser.add_argument('--cascade', default='haarcascade_frontalface_alt2.xml',
help='Cascade XML file to use (opencv format)')
parser.add_argument('--output', default='saves',
help='Directory to store images (after pressing spacebar)')
args = parser.parse_args()
@ -24,4 +26,4 @@ if __name__ == '__main__': @@ -24,4 +26,4 @@ if __name__ == '__main__':
if args.counter_clockwise:
rotate = cv2.ROTATE_90_COUNTERCLOCKWISE
face_recognition.comparison.main(args.camera, rotate, args.fullscreen, args.cascade)
face_recognition.comparison.main(args.camera, rotate, args.fullscreen, args.cascade, args.output)

Write Preview
Loading…
Cancel
Save