def split_func(split_id):
# -------- choose a whole part ------------------ #
each_split_sample_num = samples.shape[0] // split_num
my_samples = samples[split_id * each_split_sample_num: (split_id + 1) * each_split_sample_num]
my_labels = labels[split_id * each_split_sample_num: (split_id + 1) * each_split_sample_num]
utility.save_to_file(save_prefix + str(split_id) + ".file", my_samples, my_labels)
def generate_datas(args):
counts = args.iter_num // 10
total_samples, total_labels = None, None
for _ in range(counts):
random_samples, random_labels = utility.generate_random_samples(
num_of_samples=args.global_batch_size * 10,
vocabulary_size=args.vocabulary_size,
slot_num=args.slot_num,
max_nnz=args.nnz_per_slot,
use_sparse_mask=False)
if total_samples is None:
total_samples = random_samples
total_labels = random_labels
else:
total_samples = np.concatenate([total_samples, random_samples],
axis=0)
total_labels = np.concatenate([total_labels, random_labels],
axis=0)
utility.save_to_file(args.filename, total_samples, total_labels)
'block_coords': (block_x, block_y),
'key': zigzag[i],
'val': transform[zigzag[i]]
})
return result
if __name__ == '__main__':
if len(sys.argv) == 1:
root_dir = util.safeGetDirectory()
all_files = [f for f in listdir(root_dir) if path.isfile(path.join(root_dir, f))]
input_file = util.getVideoFile(all_files)
n = util.getConstant('n')
filename = path.join(root_dir, input_file)
elif len(sys.argv) == 3:
filename = path.realpath(sys.argv[2])
n = int(sys.argv[1])
else:
print 'Usage: python block_dct.py 6 ../path/to/file.mp4'
exit()
# Read the video data
video = cv2.VideoCapture(filename)
frame_data = util.getContent(video)
# Calculate the significant components
significant_components = FindDiscreteCosineTransform(frame_data, n)
# Write the data to the file
output_filename = filename.replace('.mp4', '_blockdct_' + str(n) + '.bct')
util.save_to_file(significant_components, output_filename)
'''
if __name__ == '__main__':
if len(sys.argv) == 1:
root_dir = util.safeGetDirectory()
all_files = [f for f in listdir(root_dir) if path.isfile(path.join(root_dir, f))]
input_file = util.getVideoFile(all_files)
n = util.getConstant('n')
filename = path.join(root_dir, input_file)
elif len(sys.argv) == 3:
filename = path.realpath(sys.argv[2])
n = int(sys.argv[1])
else:
print 'Usage: python block_quantize.py 6 ../path/to/file.mp4'
exit()
# Read video data
video = cv2.VideoCapture(filename)
frame_data = util.getContent(video)
# Quantize the blocks of the video
quantized_values, frame_block_list = quantize(frame_data, n)
# Write the data to the file
output_filename = filename.replace('.mp4', '_hist_' + str(n) + '.hst')
util.save_to_file(quantized_values, output_filename)
# Display histogram of quantized regions
image_filename = output_filename.replace('.hst', '.png')
display_histogram(quantized_values, n, image_filename=image_filename)
'''
Main Method
Given a video file `video_filename.mp4` and an `m` value, will output a text file video_filename_blockdwt_n.bwt in the same directory.
Pass the parameters in via command line parameters.
'''
if __name__ == '__main__':
if len(sys.argv) == 1:
root_dir = util.safeGetDirectory()
all_files = [f for f in listdir(root_dir) if path.isfile(path.join(root_dir, f))]
input_file = util.getVideoFile(all_files)
m = util.getConstant('m')
filename = path.join(root_dir, input_file)
elif len(sys.argv) == 3:
filename = path.realpath(sys.argv[2])
m = int(sys.argv[1])
else:
print 'Usage: python frame_dwt.py 6 ../path/to/file.mp4'
exit()
# Read the video data
video = cv2.VideoCapture(filename)
frame_data = util.getContent(video)
# Calculate the wavelet components of each frameblock
significant_wavelets = video_framedwt(frame_data, m)
# Write the data to the file
output_filename = filename.replace('.mp4', '_framedwt_' + str(m) + '.fwt')
util.save_to_file(significant_wavelets, output_filename)
