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face_recognition
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Save images with spacebar

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testqueue
Ruben van de Ven 2 years ago
parent e7ff1ac0cb
commit e21376465f
3 changed files with 75 additions and 77 deletions
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  1. 1
      .gitignore
  2. 147
      face_recognition/comparison.py
  3. 4
      mirror.py

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

147
face_recognition/comparison.py
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@ -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():
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():
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):
# 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):
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):
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
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@ -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__':
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)

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