# inputs
input_image = r'..\images\opencv.png'
input_video = r'..\videos\ps3-4-a\ps3-4-a.mp4'
output_video = r'..\videos\ps3-4-a\test.mp4'
num_features = 5000
num_matches = 2000
ransac_thresh = 10.0
# median_size = 11
# sobel_size = 3
# edge_thresh = 40
# file io
img = cv2.imread(input_image)
fps = ear.get_fps(input_video)
gen = ear.generate_frames(input_video)
# initialize
a = next(gen)
rows, cols = a.shape[:2]
# bbox = ear.get_initial_bbox(img, a, median_size, sobel_size, edge_thresh)
bbox = np.array([[134.0, 108.0], [447.0, 109.0], [133.0, 250.0],
[446.0, 256.0]])
Ha = ear.get_initial_homography(img, bbox)
with ear.VideoWriter(output_video, fps, (cols, rows)) as writer:
# write initial frame
frame = ear.project_image(img, a, Ha)
writer.write(frame)
def main(params):
# file io
if not os.path.isfile(params['input_video']):
raise FileNotFoundError('no such input video: %s' %
params['input_video'])
img = cv2.imread(params['input_image'])
fps = ear.get_fps(params['input_video'])
gen = ear.generate_frames(params['input_video'])
output_dir = os.path.dirname(params['output_prefix'])
if not os.path.isdir(output_dir):
os.makedirs(output_dir)
_, ext = os.path.splitext(params['input_video'])
output_video = params['output_prefix'] + ext
# initialize
a = next(gen)
rows, cols = a.shape[:2]
bbox = ear.get_initial_bbox(img, a, params['median_size'],
params['sobel_size'], params['edge_thresh'])
Ha = ear.get_initial_homography(img, bbox)
# allocate frame cache
frames = np.empty((params['frame_step'], rows, cols, 3), dtype=np.uint8)
with ear.VideoWriter(output_video, fps, (cols, rows)) as writer:
msg = 'writing to %s...' % output_video
print(msg)
# write initial frame
frame = ear.project_image(img, a, Ha)
writer.write(frame)
for frame_count, b in enumerate(gen, 1):
if params['verbose']:
print('on frame %i' % frame_count)
i = (frame_count - 1) % params['frame_step']
# pocket frame
frames[i] = b
if i != params['frame_step'] - 1:
continue
# update cumulative homography
Hab = ear.get_homography(a,
b,
params['num_features'],
params['num_matches'],
params['ransac_thresh'],
num_anms=params.get('num_anms'))
Hb = ear.update_homography(Ha, Hab)
# compute partial homographies
homographies = ear.interpolate_homographies(Ha,
Hb,
params['frame_step'],
method='direct')
for b, Hb in zip(frames, homographies):
# write frames
frame = ear.project_image(img, b, Hb, copy=True)
writer.write(frame)
# update a
a[:] = b
Ha[:] = Hb
if 'num_frames' in params and frame_count > params['num_frames']:
break
print(msg + 'done!')
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
import context
import ear
if __name__ == '__main__':
fname = r'..\videos\ps3-4-a\ps3-4-a.mp4'
gen = ear.generate_frames(fname)
for frame in gen:
break
ear.easy_imshow(frame, num=1)