def main():
with sample_video() as video:
db = scannerpy.Database()
frames = [0, 100, 200]
[bboxes] = face_detection.detect_faces(db, videos=[video], frames=[frames])
[clothing] = clothing_detection.detect_clothing(db, videos=[video], frames=[frames], bboxes=[bboxes])
print(next(clothing.load())[0])
def main():
with sample_video() as video:
frame_nums = list(range(0, video.num_frames(), 100))
montage_img = video.montage(frame_nums, cols=5)
st.imwrite('sample_montage.jpg', montage_img)
print('Wrote frame montage to {}'.format(
os.path.abspath('sample_montage.jpg')))
def main():
with sample_video() as video:
db = scannerpy.Database()
[shots] = shot_detection.detect_shots(db, videos=[video])
montage_img = video.montage(shots)
imwrite('sample_shots.jpg', montage_img)
print('Wrote shot montage to {}'.format(os.path.abspath('sample_shots.jpg')))
def main():
with sample_video() as video:
db = scannerpy.Database()
frames = list(range(10))
bboxes = face_detection.detect_faces(db,
videos=[video],
frames=[frames])
embeddings = face_embedding.embed_faces(db,
videos=[video],
frames=[frames],
bboxes=bboxes)
print('First embedding: {}'.format(next(embeddings[0].load())))
print('Finished computing embeddings')
def main():
with sample_video() as video:
db = scannerpy.Database()
frames = list(range(50))
bboxes = face_detection.detect_faces(db,
videos=[video],
frames=[frames])
genders = gender_detection.detect_genders(db,
videos=[video],
frames=[frames],
bboxes=bboxes)
print('First gender: {}'.format(next(genders[0].load())))
print('Finished computing genders')
def main():
with sample_video() as video:
db = scannerpy.Database()
frames = [0, 100, 200]
poses = pose_detection.detect_poses(db,
videos=[video],
frames=[frames])
vis.draw_poses(db,
videos=[video],
poses=poses,
frames=[frames],
path='sample_poses.mp4')
print('Wrote video with poses drawn to {}'.format(
os.path.abspath('sample_poses.mp4')))
def main():
with sample_video() as video:
db = scannerpy.Database()
frames = list(range(50))
bboxes = face_detection.detect_faces(db,
videos=[video],
frames=[frames])
vis.draw_bboxes(db,
videos=[video],
frames=[frames],
bboxes=bboxes,
paths=['sample_faces.mp4'])
print('Wrote video with objects drawn to {}'.format(
os.path.abspath('sample_faces.mp4')))
def main():
with sample_video() as video:
db = scannerpy.Database()
frames = list(range(0, 20, 3))
print('Running object detector')
[bboxes] = object_detection.detect_objects(db,
videos=[video],
frames=[frames])
print('Running bbox visualizer')
vis.draw_bboxes(db,
videos=[video],
frames=[frames],
bboxes=[bboxes],
paths=['sample_objects.mp4'])
print('Wrote video with objects drawn to {}'.format(
os.path.abspath('sample_objects.mp4')))
from scannertools import pose_detection, vis, sample_video
import scannerpy
import os
with sample_video() as video:
db = scannerpy.Database()
frames = [0, 100, 200]
poses = pose_detection.detect_poses(db, videos=[video], frames=[frames])
vis.draw_poses(db, videos=[video], poses=poses, frames=[frames], path='sample_poses.mp4')
print('Wrote video with poses drawn to {}'.format(os.path.abspath('sample_poses.mp4')))
from scannertools import sample_video, audio
import scannerpy
import os
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
with sample_video(delete=False) as video:
db = scannerpy.Database()
aud = audio.AudioSource(video)
out = audio.compute_average_volume(db, audio=[aud])
plt.plot(list(out[0].load()))
plt.savefig('volume.png')
def video():
with st.sample_video() as video:
yield video