def video_uniform_sample_n_frames_old(video_path, n_samples, max_dim):
"""
Sample only n frames from the video.
"""
raise Exception('Needs to add argument about resizing type')
cap = FFMPEG_VideoReader(video_path, False)
cap.initialize()
fps = cap.fps
n_frames = cap.nframes
duration = cap.duration
step = duration / (n_samples)
frames = []
for i in range(n_samples):
time_sec = i * step
frame = cap.get_frame(time_sec)
# resize frame to fit in the array, it's going to be used by caffe anyway
frame = image_utils.resize_keep_aspect_ratio_max_dim(frame, max_dim)
# frame encoded as uint and values are from 0-255
# but caffe needs float32 and values from 0-1
frame = frame.astype('float32') / float(255)
frames.append(frame)
# very important, or we'd have memory leakage
cap.__del__()
return frames
def get_regions(video_path, annot, resize_type, verbose=False):
"""
Get the frames whose numbers are given in the "annot" dictionary.. Then, for each frame get the regions as specificed in the "annot" dictionary.
Finally, return these regions.
"""
assert resize_type in ['resize', 'resize_crop', 'resize_crop_scaled']
resize_function = None
if resize_type == 'resize':
resize_function = image_utils.resize_frame
elif resize_type == 'resize_crop':
resize_function = image_utils.resize_crop
elif resize_type == 'resize_crop_scaled':
resize_function = image_utils.resize_crop_scaled
cap = FFMPEG_VideoReader(video_path, False)
cap.initialize()
fps = float(cap.fps)
n_frames = cap.nframes
duration = cap.duration
n_regions = sum([len(v) for k, v in annot.iteritems()])
frame_size = 224
bbox_resize_factor = 2
regions = np.zeros(shape=(n_regions, frame_size, frame_size, 3),
dtype='float32')
region_idx = -1
frame_nums = annot.keys()
for frame_num in frame_nums:
if (region_idx + 1) % 100 == 0 and verbose:
print(' ... reading region %d/%d' % (region_idx + 1, n_regions))
# get the frame
i = frame_num - 1
time_sec = i / fps
frame = cap.get_frame(time_sec)
# get the regions (resized) from the frame
regions_info = annot[frame_num]
for region_info in regions_info:
region_idx += 1
bbox = region_info[1:5]
bbox = np.multiply(bbox, bbox_resize_factor).astype(np.int)
x1, y1, x2, y2 = bbox
region = frame[y1:y2, x1:x2]
# resize frame to fit in the array, it's going to be used by caffe anyway
region = resize_function(region)
# frame encoded as uint and values are from 0-255, but caffe needs float32 and values from 0-1
region = region.astype('float32') / float(255)
regions[region_idx] = region
# very important, or we'd have memory leakage
cap.__del__()
return regions
def video_save_frames_specific_duration(action_num,
video_num,
video_path,
frames_root_pathes,
start_stop_sec,
image_name_format,
verbose=False):
assert len(frames_root_pathes) == len(start_stop_sec)
cap = FFMPEG_VideoReader(video_path, False)
cap.initialize()
fps = float(cap.fps)
duration_sec = cap.duration
img_dim = 224
start_stop_sec = np.array(start_stop_sec)
for i, s_s_sec in enumerate(start_stop_sec):
start_sec, stop_sec = s_s_sec
frame_root_path = frames_root_pathes[i]
# offset of starting/stopping the action
sec_offset = 0.25
start_idx = int((start_sec + sec_offset) * fps)
stop_idx = int((stop_sec + sec_offset) * fps) + 1
if verbose:
print('action, video: %d, %d' % (action_num, video_num))
print('%d/%d' % (start_sec, stop_sec))
print('%d/%d' % (start_idx, stop_idx))
for idx_frame in range(start_idx, stop_idx):
time_sec = idx_frame / fps
if verbose and idx_frame % 100 == 0:
print('... time_sec, frame: %d/%d' % (time_sec, idx_frame))
frame = cap.get_frame(time_sec)
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
frame = image_utils.resize_crop(frame,
target_width=img_dim,
target_height=img_dim)
image_name = image_name_format % (idx_frame, )
frame_path = os.path.join(frame_root_path, image_name)
cv2.imwrite(frame_path, frame)
# very important, or we'd have memory leakage
cap.__del__()
def video_uniform_sampling(spf,
video_path,
resize_type,
is_local,
verbose=False):
assert resize_type in ['resize', 'resize_crop', 'resize_crop_scaled']
resize_function = None
if resize_type == 'resize':
resize_function = image_utils.resize_frame
elif resize_type == 'resize_crop':
resize_function = image_utils.resize_crop
elif resize_type == 'resize_crop_scaled':
resize_function = image_utils.resize_crop_scaled
cap = FFMPEG_VideoReader(video_path, False)
cap.initialize()
fps = cap.fps
n_frames = cap.nframes
duration = cap.duration
n_samples = int(duration / float(spf))
# check if no samples because the video duration is less than spf
# then at least, get 1 frame of the video
if n_samples == 0:
n_samples = 1
frame_size = 224
frames = np.zeros(shape=(n_samples, frame_size, frame_size, 3),
dtype='float32')
for i in range(n_samples):
num = i + 1
if num % 100 == 0 and verbose:
print(' ... reading frame %d/%d' % (num, n_samples))
time_sec = i * spf
frame = cap.get_frame(time_sec)
# resize frame to fit in the array, it's going to be used by caffe anyway
frame = resize_function(frame)
# frame encoded as uint and values are from 0-255
# but caffe needs float32 and values from 0-1
frame = frame.astype('float32') / float(255)
frames[i] = frame
# very important, or we'd have memory leakage
cap.__del__()
return frames, fps, n_frames, duration
