def handle_single_images(input_handler: InputHandler, number_of_cameras: int):
Database.initialize()
input_handler_copy = copy.deepcopy(input_handler)
while True:
try:
image_index, image = input_handler_copy.get_frame(0)
identifier = SubjectIdentifier(image_index)
identifier.identify(image)
except IndexError:
break
for i in range(1, number_of_cameras):
input_handler_copy = copy.deepcopy(input_handler)
successes = 0
fails = 0
while True:
try:
image_index, image = input_handler_copy.get_frame(i)
identifier = SubjectIdentifier()
subject = identifier.identify(image)
if subject.name == image_index:
successes += 1
else:
fails += 1
print(image_index, "identified as", subject.name)
except IndexError:
print(successes * 100 / (successes + fails))
break
def handle_single_images(input_handler: InputHandler, number_of_cameras: int):
Database.initialize()
input_handler_copy = copy.deepcopy(input_handler)
while True:
try:
image_index, image = input_handler_copy.get_frame(0)
identifier = SubjectIdentifier(image_index)
identifier.identify(image)
except IndexError:
break
for i in range(1, number_of_cameras):
input_handler_copy = copy.deepcopy(input_handler)
successes = 0
fails = 0
while True:
try:
image_index, image = input_handler_copy.get_frame(i)
identifier = SubjectIdentifier()
subject = identifier.identify(image)
if subject.name == image_index:
successes += 1
else:
fails += 1
print(image_index, 'identified as', subject.name)
except IndexError:
print(successes * 100 / (successes + fails))
break
def run(input_handler: InputHandler, camera_name: str, add_to_db: Optional[str]):
Database.initialize()
im0 = input_handler.get_frame(camera_name).image
im_gray0 = cv2.cvtColor(im0, cv2.COLOR_BGR2GRAY)
im_draw = numpy.copy(im0)
tl, br = util.get_rect(im_draw)
cmt = CMT(im_gray0, tl, br, estimate_rotation=False)
identifier = SubjectIdentifier(add_to_db)
structuring_element = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
while True:
try:
# Read image
im = input_handler.get_frame(camera_name).image
im_gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
im_draw = numpy.copy(im)
cmt.process_frame(im_gray)
# Display results
# Draw updated estimate
if cmt.has_result:
cropped_image = im[cmt.tl[1] : cmt.bl[1], cmt.tl[0] : cmt.tr[0]]
difference = cv2.absdiff(im_gray0, im_gray)
blurred = cv2.medianBlur(difference, 3)
display = cv2.compare(blurred, 6, cv2.CMP_GT)
eroded = cv2.erode(display, structuring_element)
dilated = cv2.dilate(eroded, structuring_element)
cropped_mask = dilated[cmt.tl[1] : cmt.bl[1], cmt.tl[0] : cmt.tr[0]]
cropped_mask[cropped_mask == 255] = 1
horizontal_center = cropped_mask.shape[1] // 2
vertical_center = cropped_mask.shape[0] // 2
cv2.ellipse(
cropped_mask,
(horizontal_center, vertical_center),
(horizontal_center, vertical_center),
0,
0,
360,
3,
-1,
)
cv2.rectangle(im_draw, cmt.tl, cmt.br, (255, 0, 0), 4)
subject = identifier.identify(cropped_image, cropped_mask)
cv2.putText(im_draw, subject.name, cmt.tl, cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2, cv2.LINE_AA)
util.draw_keypoints(cmt.tracked_keypoints, im_draw, (255, 255, 255))
util.draw_keypoints(cmt.votes[:, :2], im_draw)
util.draw_keypoints(cmt.outliers[:, :2], im_draw, (0, 0, 255))
cv2.imshow("main", im_draw)
cv2.waitKey(1)
im_gray0 = im_gray
except IndexError:
Database.save_db()
exit(0)
def run(input_handler: InputHandler, camera_name: str,
add_to_db: Optional[str]):
Database.initialize()
im0 = input_handler.get_frame(camera_name).image
im_gray0 = cv2.cvtColor(im0, cv2.COLOR_BGR2GRAY)
im_draw = numpy.copy(im0)
tl, br = util.get_rect(im_draw)
cmt = CMT(im_gray0, tl, br, estimate_rotation=False)
identifier = SubjectIdentifier(add_to_db)
structuring_element = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
while True:
try:
# Read image
im = input_handler.get_frame(camera_name).image
im_gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
im_draw = numpy.copy(im)
cmt.process_frame(im_gray)
# Display results
# Draw updated estimate
if cmt.has_result:
cropped_image = im[cmt.tl[1]:cmt.bl[1], cmt.tl[0]:cmt.tr[0]]
difference = cv2.absdiff(im_gray0, im_gray)
blurred = cv2.medianBlur(difference, 3)
display = cv2.compare(blurred, 6, cv2.CMP_GT)
eroded = cv2.erode(display, structuring_element)
dilated = cv2.dilate(eroded, structuring_element)
cropped_mask = dilated[cmt.tl[1]:cmt.bl[1],
cmt.tl[0]:cmt.tr[0]]
cropped_mask[cropped_mask == 255] = 1
horizontal_center = cropped_mask.shape[1] // 2
vertical_center = cropped_mask.shape[0] // 2
cv2.ellipse(cropped_mask, (horizontal_center, vertical_center),
(horizontal_center, vertical_center), 0, 0, 360, 3,
-1)
cv2.rectangle(im_draw, cmt.tl, cmt.br, (255, 0, 0), 4)
subject = identifier.identify(cropped_image, cropped_mask)
cv2.putText(im_draw, subject.name, cmt.tl,
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2,
cv2.LINE_AA)
util.draw_keypoints(cmt.tracked_keypoints, im_draw,
(255, 255, 255))
util.draw_keypoints(cmt.votes[:, :2], im_draw)
util.draw_keypoints(cmt.outliers[:, :2], im_draw, (0, 0, 255))
cv2.imshow('main', im_draw)
cv2.waitKey(1)
im_gray0 = im_gray
except IndexError:
Database.save_db()
exit(0)
