def __init__(self):
# Initialize Webcam
self.stream = cv2.VideoCapture(0)
# Starting TensorFlow API with SSD Mobilenet
self.detection = DetectionObj(model='ssd_mobilenet_v1_coco_11_06_2017')
# Start capturing video so the Webca, will tune itself
_, self.frame = self.stream.read()
# Set the stop flag to False
self.stop = False
#
Thread(target=self.refresh, args=()).start()
class WebcamStream:
def __init__(self):
# Initialize Webcam
self.stream = cv2.VideoCapture(0)
# Starting TensorFlow API with SSD Mobilenet
self.detection = DetectionObj(model='ssd_mobilenet_v1_coco_11_06_2017')
# Start capturing video so the Webca, will tune itself
_, self.frame = self.stream.read()
# Set the stop flag to False
self.stop = False
#
Thread(target=self.refresh, args=()).start()
def refresh(self):
# Looping until an explicit stop is sent
# from outside the function
while True:
if self.stop:
return
_, self.frame = self.stream.read()
def get(self):
# returning the annotated image
return self.detection.annotate_photogram(self.frame)
def halt(self):
# setting the halt flag
self.stop = True
from tensorflow_detection import DetectionObj
if __name__ == '__main__':
detection = DetectionObj(model='ssd_mobilenet_v2_coco_11_06_2017')
detection.video_pipeline(video="./sample_videos/ducks.mp4", audio=False)
from tensorflow_detection import DetectionObj
if __name__ == "__main__":
detection = DetectionObj(model='ssd_mobilenet_v1_coco_11_06_2017')
images = [
"./sample_images/intersection.jpg", "./sample_images/busy_street.jpg",
"./sample_images/doge.jpg"
]
detection.file_pipeline(images)
from tensorflow_detection import DetectionObj
if __name__ == '__main__':
detection = DetectionObj(model='ssd_mobilenet_v1_coco_11_06_2017')
detection.webcam_pipeline()