# On versions of L4T prior to 28.1, add 'flip-method=2' into gst_str
gst_str = ('nvcamerasrc ! '
'video/x-raw(memory:NVMM), '
'width=(int)2592, height=(int)1458, '
'format=(string)I420, framerate=(fraction)30/1 ! '
'nvvidconv ! '
'video/x-raw, width=(int){}, height=(int){}, '
'format=(string)BGRx ! '
'videoconvert ! appsink').format(width, height)
return cv2.VideoCapture(gst_str, cv2.CAP_GSTREAMER)
'''
reid_mode = cam_reid.reid_model()
# encode origin image
compare = cam_reid.Compare(model=reid_mode, origin_img="./image/origin")
origin_f, origin_name = compare.encode_origin_image()
def open_cam_onboard(width, height):
gst_elements = str(subprocess.check_output('gst-inspect-1.0'))
if 'nvcamerasrc' in gst_elements:
# On versions of L4T prior to 28.1, add 'flip-method=2' into gst_str
gst_str = ('nvcamerasrc ! '
'video/x-raw(memory:NVMM), '
'width=(int)2592, height=(int)1458, '
'format=(string)I420, framerate=(fraction)30/1 ! '
'nvvidconv ! '
'video/x-raw, width=(int){}, height=(int){}, '
'format=(string)BGRx ! '
'videoconvert ! appsink').format(width, height)
from detection import cam_detection
from reid import cam_reid
import cv2
import time
detect_model = cam_detection.detection_model()
reid_mode = cam_reid.reid_model()
# encode origin image
compare = cam_reid.Compare(
model=reid_mode,
origin_img="/home/hlzhang/project/detection_reid/image/origin")
origin_f, origin_name = compare.encode_origin_image()
def handle_signal_image(img):
# # encode origin image
# compare = cam_reid.Compare(model=reid_mode, origin_img=origin_img)
# origin_f, origin_name = compare.encode_origin_image()
# person detection
img = cv2.resize(img, (640, 480))
idxs, classes, anchors = cam_detection.detection_person(img, detect_model)
bounding_boxs = []
for j in range(idxs[0].shape[0]):
bbox = anchors[idxs[0][j], :]
x1 = int(bbox[0])
y1 = int(bbox[1])
x2 = int(bbox[2])