def annotate_video(video_filepath):
reader = VideofileReader(video_filepath)
frame = FrameIndexSplitter()(reader)
results = Detectron2HumanPose(architecture = 'R50_FPN_3x', device_type = 'cpu')(frame)
keypoints = KeypointsExtractor()(results)
annotated_frame = HumanPoseAnnotator()(frame, keypoints)
writer = VideofileWriter('pose.avi')(annotated_frame)
fl = flow.Flow([reader], [], flow_type = BATCH)
fl.run()
fl.join()
def main():
input_file = get_file(VIDEO_NAME, URL_VIDEO)
output_file = "output.avi"
reader = VideofileReader(input_file)
frame = FrameIndexSplitter()(reader)
detector = TensorflowObjectDetector()(frame)
annotator = BoundingBoxAnnotator()(frame, detector)
writer = VideofileWriter(output_file, fps=30)(annotator)
fl = flow.Flow([reader], [writer], flow_type=BATCH)
fl.run()
fl.join()
def main():
output_file = sys.argv[1]
input_file = get_file(VIDEO_NAME, URL_VIDEO)
reader = VideofileReader(input_file)
frame = FrameIndexSplitter()(reader)
tracks = TracktorFromFrames()(frame)
tracks_to_annotator = TracksToAnnotator()(tracks)
annotator = TrackerAnnotator()(frame, tracks_to_annotator)
writer = VideofileWriter(output_file, fps=30)(annotator)
fl = flow.Flow([reader], [writer], flow_type=BATCH)
fl.run()
fl.join()
def obfuscate_faces(video_filepath):
reader = VideofileReader(video_filepath)
frame = FrameIndexSplitter()(reader)
faces = TensorflowObjectDetector(num_classes=1,
architecture='ssd-mobilenetv2',
dataset='faces',
min_score_threshold=0.2)(frame)
blurred_faces = BoundingboxObfuscator()(frame, faces)
writer = VideofileWriter('blurred_video.mp4', codec='avc1')(blurred_faces)
fl = flow.Flow([reader], [writer], flow_type=BATCH)
fl.run()
fl.join()
def main():
# i.e: 10.23.232.43
stream_address = sys.argv[1]
username = sys.argv[2]
password = sys.argv[3]
output_file = "output.avi"
stream_url = f'rtsp://{username}:{password}@{stream_address}'
reader = VideoUrlReader(stream_url)
frame = FrameIndexSplitter()(reader)
writer = VideofileWriter(output_file, fps=30)(frame)
fl = flow.Flow([reader], [writer], flow_type=REALTIME)
fl.run()
fl.join()
def main():
input_file = get_file(VIDEO_NAME, URL_VIDEO)
output_file = "output.avi"
reader = VideofileReader(input_file)
frame = FrameIndexSplitter()(reader)
detector = TensorflowObjectDetector(num_classes = 2, architecture = 'fasterrcnn-resnet101', dataset = 'kitti')(frame)
# keeps only automobile classes: autos, buses, cycles, etc.
tracker = KalmanFilterBoundingBoxTracker()(detector)
annotator = TrackerAnnotator()(frame, tracker)
writer = VideofileWriter(output_file, fps = 30)(annotator)
fl = flow.Flow([reader], [writer], flow_type = BATCH)
fl.run()
fl.join()
def main():
input_file = get_file(VIDEO_NAME, URL_VIDEO)
output_file = "output.avi"
reader = VideofileReader(input_file)
frame = FrameIndexSplitter()(reader)
detector = TensorflowObjectDetector()(frame)
# keeps only automobile classes: autos, buses, cycles, etc.
filter_ = BoundingBoxesFilter([1, 2, 3, 4, 6, 8, 10, 13])(detector)
tracker = KalmanFilterBoundingBoxTracker()(filter_)
annotator = TrackerAnnotator()(frame, tracker)
writer = VideofileWriter(output_file, fps=30)(annotator)
fl = flow.Flow([reader], [writer], flow_type=BATCH)
fl.run()
fl.join()
def track_humans():
input_file_path = get_file(VIDEO_NAME, URL_VIDEO)
output_file = 'annotated_video.avi'
reader = VideofileReader(input_file_path)
frame = FrameIndexSplitter()(reader)
results = Detectron2HumanPose(architecture='R50_FPN_3x',
device_type='cpu')(frame)
keypoints = KeypointsExtractor()(results)
bounding_boxes = BoundingBoxesExtractor()(results)
anotated_keypoints = HumanPoseAnnotator()(frame, keypoints)
cropped_humans = CropBoundingBoxes()(frame, bounding_boxes)
human_features = HumanEncoder()(cropped_humans)
tracker_input = AppendFeaturesToBoundingBoxes()(bounding_boxes,
human_features)
tracks = DeepSort()(tracker_input)
tracks_anotator_input = ConvertTracksForAnotation()(tracks)
anotated_tracks = TrackerAnnotator()(anotated_keypoints,
tracks_anotator_input)
writer = VideofileWriter(output_file)(anotated_tracks)
fl = flow.Flow([reader], [writer], flow_type=BATCH)
fl.run()
fl.join()
import videoflow
import videoflow.core.flow as flow
from videoflow.core.constants import BATCH
from videoflow.consumers import VideofileWriter
from videoflow.producers import VideofileReader
from videoflow.processors.vision.detectors import TensorflowObjectDetector
from videoflow.processors.vision.annotators import BoundingBoxAnnotator
from videoflow.utils.downloader import get_file
class FrameIndexSplitter(videoflow.core.node.ProcessorNode):
def __init__(self):
super(FrameIndexSplitter, self).__init__()
def process(self, data):
index, frame = data
return frame
input_file = "input.mp4"
output_file = "output.avi"
reader = VideofileReader(input_file)
frame = FrameIndexSplitter()(reader)
detector = TensorflowObjectDetector()(frame)
annotator = BoundingBoxAnnotator()(frame, detector)
writer = VideofileWriter(output_file, fps=30)(annotator)
fl = flow.Flow([reader], [writer], flow_type=BATCH)
fl.run()
fl.join()
