def FFIC(domain_chunks, range_chunks, inpface):
############################################################################
# encode the range image using svd encoding
############################################################################
# encode image
start = time.time()
codebook = encode_svd(domain_chunks, range_chunks, verbose=False)
svd_encoding_time = time.time() - start
# for svd only we implement compression by
# dropping coefficients in the codebook
codebook[:, COMPRESSION_FACTOR:] = 0
# Use an input face to use as input for the reconstruction
domain_chunks = utils.Partition(inpface, mode=MODE)
# initialize psnr
psnr = np.zeros(10);
# decode image 100 times
start = time.time()
reconstructed_chunks = decode_svd(codebook, domain_chunks)
reconstructed_chunks_1 = copy.deepcopy(reconstructed_chunks)
psnr[0] = PSNR(range_image, reconstructed_chunks.image)
for i in range(9):
rec_dim = rescale(reconstructed_chunks.image, 0.5)
domain_chunks = utils.Partition(rec_dim, mode=MODE)
reconstructed_chunks = decode_svd(codebook, domain_chunks)
psnr[i+1] = PSNR(range_image, reconstructed_chunks.image)
svd_decoding_time = time.time()-start
# plot_image(reconstructed_chunks.image,
# title=f"Reconstructed Image (SVD Encoding) \n {reconstructed_chunks.image.shape[0]}x{reconstructed_chunks.image.shape[0]}, {COMPRESSION_FACTOR}/{BLOCK_SIZE} Compression",
# cmap='gray', y=0.97)
############################################################################
# encoding and decoding time results
############################################################################
print(f"svd mode encoding: {svd_encoding_time}")
print(f"svd mode decoding: {svd_decoding_time}")
############################################################################
# psnr results
############################################################################
# psnr = PSNR(range_image, reconstructed_chunks.image)
print(f"PSNR: {psnr} \t Coefficients Retained: {COMPRESSION_FACTOR}/{BLOCK_SIZE}")
return psnr
aaronface = np.asarray(aaronface.getdata()).reshape(512, 512)
aaronface = rescale(aaronface, 0.25)
else:
facedir = Path(__file__).resolve().parent.parent / "data"
aaronface = Image.open(list(facedir.glob("mandrill.jpg"))[0])
aaronface = np.asarray(aaronface.getdata()).reshape(512, 512)
aaronface = rescale(aaronface, 0.25)
# aaronface = np.asarray(aaronface.getdata()).reshape(64,64)
# aaronface = images.get_image(0, scale_factor=0.125/2)
plot_image(aaronface,
title=f"Domain Image {aaronface.shape[0]}x{aaronface.shape[1]}",
cmap='gray')
domain_chunks = utils.Partition(aaronface, mode=MODE)
reconstructed_chunks = decode_svd(codebook, domain_chunks)
# save_contractiveness_factors(domain_chunks, 1)
for i in range(26):
rec_dim = rescale(reconstructed_chunks.image, 0.5)
domain_chunks = utils.Partition(rec_dim, mode=MODE)
# save_contractiveness_factors(domain_chunks, i)
reconstructed_chunks = decode_svd(codebook, domain_chunks)
if i in [1, 5, 10, 20, 25]:
plot_image(
reconstructed_chunks.image,
title=
f"Reconstructed Image {i} iterations \n{reconstructed_chunks.\
image.shape[0]}x{reconstructed_chunks.image.shape[0]} ({MODE})",
cmap='gray',