def test_video_embedding():
"""use a tempfile, with dummy-data, to ensure that video embedding doesn't crash"""
v = display.Video("http://ignored")
assert not v.embed
html = v._repr_html_()
nt.assert_not_in('src="data:', html)
nt.assert_in('src="http://ignored"', html)
with nt.assert_raises(ValueError):
v = display.Video(b'abc')
with NamedFileInTemporaryDirectory('test.mp4') as f:
f.write(b'abc')
f.close()
v = display.Video(f.name)
assert not v.embed
html = v._repr_html_()
nt.assert_not_in('src="data:', html)
v = display.Video(f.name, embed=True)
html = v._repr_html_()
nt.assert_in('src="data:video/mp4;base64,YWJj"', html)
v = display.Video(f.name, embed=True, mimetype='video/other')
html = v._repr_html_()
nt.assert_in('src="data:video/other;base64,YWJj"', html)
v = display.Video(b'abc', embed=True, mimetype='video/mp4')
html = v._repr_html_()
nt.assert_in('src="data:video/mp4;base64,YWJj"', html)
v = display.Video(u'YWJj', embed=True, mimetype='video/xyz')
html = v._repr_html_()
nt.assert_in('src="data:video/xyz;base64,YWJj"', html)
import numpy as np
import mmcv, cv2
from PIL import Image, ImageDraw
from IPython import display
device = torch.device('cuda:0' if torch.cuda.is_available() else 'cpu')
print('Running on device: {}'.format(device))
mtcnn = MTCNN(keep_all=True, device=device)
video = mmcv.VideoReader('video.mp4')
frames = [
Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)) for frame in video
]
display.Video('video.mp4', width=640)
frames_tracked = []
for i, frame in enumerate(frames):
print('\rTracking frame: {}'.format(i + 1), end='')
# Detect faces
boxes, _ = mtcnn.detect(frame)
# Draw faces
frame_draw = frame.copy()
draw = ImageDraw.Draw(frame_draw)
for box in boxes:
draw.rectangle(box.tolist(), outline=(255, 0, 0), width=6)
# Add to frame list
cap.release()
out.release()
cv2.destroyAllWindows()
# define MTCNN module
mtcnn = MTCNN(keep_all=True, device=device)
mtcnn.to(device)
if __name__ == '__main__':
saveVideo()
video = mmcv.VideoReader(FILE_OUT)
frames = [Image.fromarray(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)) for frame in video]
display.Video(FILE_OUT, width=640)
frames_tracked = []
for i, frame in enumerate(frames):
print('\rTracking frame: {}'.format(i + 1), end='')
# Detect faces
boxes, _ = mtcnn.detect(frame)
# Draw faces
frame_draw = frame.copy()
draw = ImageDraw.Draw(frame_draw)
for box in boxes:
draw.rectangle(box.tolist(), outline=(255, 0, 0), width=6)
frames_tracked.append(frame_draw.resize((640, 360), Image.BILINEAR))
print('\nDone')
