def create_block_frames(trans, path, blocksize=8, debug=False):
""" This function creates a series of frames whereas each frame only contains one field
from the DCT matrix.
"""
B = blocksize
channelrows, channelcols = trans.shape
blocksV = channelrows / B
blocksH = channelcols / B
count = 1
if debug:
B = 2
# create the mask. There is only one white pixel within each block.
# serialize the block using a wave pattern
for (x, y) in wave(B):
blockmask = np.zeros((blocksize, blocksize), np.float32)
blockmask[y][x] = 1.0
mask = np.tile(blockmask, (blocksV, blocksH))
# apply the mask to the image:
trans_masked = np.multiply(trans, mask)
# decode the 'image':
back = np.zeros((channelrows, channelcols), np.uint8)
for row in range(blocksV):
for col in range(blocksH):
dequantblock = trans_masked[row*blocksize:(row+1)*blocksize, col*blocksize:(col+1)*blocksize]
currentblock = np.round(cv2.idct(dequantblock))+128
currentblock[currentblock > 255] = 255
currentblock[currentblock < 0] = 0
back[row*blocksize:(row+1)*blocksize, col*blocksize:(col+1)*blocksize] = currentblock
cv2.cv.SaveImage('%s/dct_%05d.png' % (path, count), cv2.cv.fromarray(back))
count += 1
def create_single_frame(path, number):
""" This creates the animation frames using a single block.
The frames are RGBA pngs.
"""
trans = dct_demo(crop=False, asset='assets/zhaw-gray.png')
blocksize = 64
count = 1
for (x, y) in wave(blocksize)[:number]:
mask = np.zeros((blocksize, blocksize), np.float32)
mask[y][x] = 1.0
trans_masked = np.multiply(trans, mask)
frame = np.round(cv2.idct(trans_masked))+128
frame[frame > 255] = 255
frame[frame < 0] = 0
cv2.cv.SaveImage('%s/dct_%05d.png' % (path, count), cv2.cv.fromarray(frame))
count += 1
