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update to run on TF2.11.* #182

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2 changes: 1 addition & 1 deletion config_fern.txt
View file
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
expname = fern_test
basedir = ./logs
datadir = ./data/nerf_llff_data/fern
datadir = /home/khoa/workspace/Data_set/NeRF_Data/nerf_llff_data/fern
dataset_type = llff

factor = 8
Expand Down
241 changes: 228 additions & 13 deletions environment.yml
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Original file line number Diff line number Diff line change
@@ -1,15 +1,230 @@
# To run: conda env create -f environment.yml
name: nerf
name: nerf_tf
channels:
- conda-forge
- conda-forge
- defaults
dependencies:
- python=3.7
- pip
- cudatoolkit=10.0
- tensorflow-gpu==1.15
- numpy
- matplotlib
- imageio
- imageio-ffmpeg
- configargparse
- imagemagick
- _libgcc_mutex=0.1=conda_forge
- _openmp_mutex=4.5=2_gnu
- alsa-lib=1.2.8=h166bdaf_0
- aom=3.5.0=h27087fc_0
- atk-1.0=2.38.0=hd4edc92_1
- attr=2.5.1=h166bdaf_1
- brotli=1.0.9=h166bdaf_8
- brotli-bin=1.0.9=h166bdaf_8
- bzip2=1.0.8=h7f98852_4
- ca-certificates=2022.12.7=ha878542_0
- cairo=1.16.0=ha61ee94_1014
- certifi=2022.12.7=pyhd8ed1ab_0
- configargparse=1.5.3=pyhd8ed1ab_0
- contourpy=1.0.7=py39h4b4f3f3_0
- cudatoolkit=11.2.2=hbe64b41_11
- cudnn=8.1.0.77=h90431f1_0
- cycler=0.11.0=pyhd8ed1ab_0
- dbus=1.13.6=h5008d03_3
- expat=2.5.0=h27087fc_0
- ffmpeg=5.1.2=gpl_h8dda1f0_106
- fftw=3.3.10=nompi_hf0379b8_106
- font-ttf-dejavu-sans-mono=2.37=hab24e00_0
- font-ttf-inconsolata=3.000=h77eed37_0
- font-ttf-source-code-pro=2.038=h77eed37_0
- font-ttf-ubuntu=0.83=hab24e00_0
- fontconfig=2.14.2=h14ed4e7_0
- fonts-conda-ecosystem=1=0
- fonts-conda-forge=1=0
- fonttools=4.39.2=py39h72bdee0_0
- freetype=2.12.1=hca18f0e_1
- fribidi=1.0.10=h36c2ea0_0
- gdk-pixbuf=2.42.10=h05c8ddd_0
- gettext=0.21.1=h27087fc_0
- ghostscript=9.54.0=h27087fc_2
- giflib=5.2.1=h0b41bf4_3
- glib=2.74.1=h6239696_1
- glib-tools=2.74.1=h6239696_1
- gmp=6.2.1=h58526e2_0
- gnutls=3.7.8=hf3e180e_0
- graphite2=1.3.13=h58526e2_1001
- graphviz=6.0.2=h99bc08f_0
- gst-plugins-base=1.22.0=h4243ec0_2
- gstreamer=1.22.0=h25f0c4b_2
- gstreamer-orc=0.4.33=h166bdaf_0
- gtk2=2.24.33=h90689f9_2
- gts=0.7.6=h64030ff_2
- harfbuzz=6.0.0=h8e241bc_0
- icu=70.1=h27087fc_0
- imageio=2.26.0=pyh24c5eb1_0
- imageio-ffmpeg=0.4.8=pyhd8ed1ab_0
- imagemagick=7.1.1_3=pl5321h0dc3a92_0
- importlib-resources=5.12.0=pyhd8ed1ab_0
- importlib_resources=5.12.0=pyhd8ed1ab_0
- jack=1.9.22=h11f4161_0
- jbig=2.1=h7f98852_2003
- jpeg=9e=h0b41bf4_3
- keyutils=1.6.1=h166bdaf_0
- kiwisolver=1.4.4=py39hf939315_1
- krb5=1.20.1=h81ceb04_0
- lame=3.100=h166bdaf_1003
- lcms2=2.15=hfd0df8a_0
- ld_impl_linux-64=2.40=h41732ed_0
- lerc=4.0.0=h27087fc_0
- libblas=3.9.0=16_linux64_openblas
- libbrotlicommon=1.0.9=h166bdaf_8
- libbrotlidec=1.0.9=h166bdaf_8
- libbrotlienc=1.0.9=h166bdaf_8
- libcap=2.66=ha37c62d_0
- libcblas=3.9.0=16_linux64_openblas
- libclang13=15.0.7=default_h3e3d535_1
- libcups=2.3.3=h36d4200_3
- libdb=6.2.32=h9c3ff4c_0
- libdeflate=1.17=h0b41bf4_0
- libdrm=2.4.114=h166bdaf_0
- libedit=3.1.20191231=he28a2e2_2
- libevent=2.1.10=h28343ad_4
- libffi=3.4.2=h7f98852_5
- libflac=1.4.2=h27087fc_0
- libgcc-ng=12.2.0=h65d4601_19
- libgcrypt=1.10.1=h166bdaf_0
- libgd=2.3.3=h5aea950_4
- libgfortran-ng=12.2.0=h69a702a_19
- libgfortran5=12.2.0=h337968e_19
- libglib=2.74.1=h606061b_1
- libgomp=12.2.0=h65d4601_19
- libgpg-error=1.46=h620e276_0
- libiconv=1.17=h166bdaf_0
- libidn2=2.3.4=h166bdaf_0
- liblapack=3.9.0=16_linux64_openblas
- libllvm15=15.0.7=hadd5161_1
- libnsl=2.0.0=h7f98852_0
- libogg=1.3.4=h7f98852_1
- libopenblas=0.3.21=pthreads_h78a6416_3
- libopus=1.3.1=h7f98852_1
- libpciaccess=0.17=h166bdaf_0
- libpng=1.6.39=h753d276_0
- libpq=15.2=hb675445_0
- librsvg=2.54.4=h7abd40a_0
- libsndfile=1.2.0=hb75c966_0
- libsqlite=3.40.0=h753d276_0
- libstdcxx-ng=12.2.0=h46fd767_19
- libsystemd0=252=h2a991cd_0
- libtasn1=4.19.0=h166bdaf_0
- libtiff=4.5.0=h6adf6a1_2
- libtool=2.4.7=h27087fc_0
- libudev1=253=h0b41bf4_0
- libunistring=0.9.10=h7f98852_0
- libuuid=2.32.1=h7f98852_1000
- libva=2.17.0=h0b41bf4_0
- libvorbis=1.3.7=h9c3ff4c_0
- libvpx=1.11.0=h9c3ff4c_3
- libwebp=1.2.4=h1daa5a0_1
- libwebp-base=1.2.4=h166bdaf_0
- libxcb=1.13=h7f98852_1004
- libxkbcommon=1.5.0=h79f4944_1
- libxml2=2.10.3=hca2bb57_3
- libzlib=1.2.13=h166bdaf_4
- lz4-c=1.9.4=hcb278e6_0
- matplotlib=3.7.1=py39hf3d152e_0
- matplotlib-base=3.7.1=py39he190548_0
- mpg123=1.31.2=hcb278e6_0
- munkres=1.1.4=pyh9f0ad1d_0
- mysql-common=8.0.32=ha901b37_0
- mysql-libs=8.0.32=hd7da12d_0
- ncurses=6.3=h27087fc_1
- nettle=3.8.1=hc379101_1
- nspr=4.35=h27087fc_0
- nss=3.89=he45b914_0
- numpy=1.24.2=py39h7360e5f_0
- openh264=2.3.1=hcb278e6_2
- openjpeg=2.5.0=hfec8fc6_2
- openssl=3.1.0=h0b41bf4_0
- p11-kit=0.24.1=hc5aa10d_0
- packaging=23.0=pyhd8ed1ab_0
- pango=1.50.14=hd33c08f_0
- pcre2=10.40=hc3806b6_0
- perl=5.32.1=2_h7f98852_perl5
- pillow=9.4.0=py39h2320bf1_1
- pip=23.0.1=pyhd8ed1ab_0
- pixman=0.40.0=h36c2ea0_0
- pkg-config=0.29.2=h36c2ea0_1008
- ply=3.11=py_1
- pthread-stubs=0.4=h36c2ea0_1001
- pulseaudio=16.1=ha8d29e2_1
- pyparsing=3.0.9=pyhd8ed1ab_0
- pyqt=5.15.7=py39h5c7b992_3
- pyqt5-sip=12.11.0=py39h227be39_3
- python=3.9.16=h2782a2a_0_cpython
- python-dateutil=2.8.2=pyhd8ed1ab_0
- python_abi=3.9=3_cp39
- qt-main=5.15.8=h5d23da1_6
- readline=8.1.2=h0f457ee_0
- setuptools=67.6.0=pyhd8ed1ab_0
- sip=6.7.7=py39h227be39_0
- six=1.16.0=pyh6c4a22f_0
- svt-av1=1.4.1=hcb278e6_0
- tk=8.6.12=h27826a3_0
- toml=0.10.2=pyhd8ed1ab_0
- tornado=6.2=py39hb9d737c_1
- tzdata=2022g=h191b570_0
- unicodedata2=15.0.0=py39hb9d737c_0
- wheel=0.40.0=pyhd8ed1ab_0
- x264=1!164.3095=h166bdaf_2
- x265=3.5=h924138e_3
- xcb-util=0.4.0=h166bdaf_0
- xcb-util-image=0.4.0=h166bdaf_0
- xcb-util-keysyms=0.4.0=h166bdaf_0
- xcb-util-renderutil=0.3.9=h166bdaf_0
- xcb-util-wm=0.4.1=h166bdaf_0
- xkeyboard-config=2.38=h0b41bf4_0
- xorg-fixesproto=5.0=h7f98852_1002
- xorg-kbproto=1.0.7=h7f98852_1002
- xorg-libice=1.0.10=h7f98852_0
- xorg-libsm=1.2.3=hd9c2040_1000
- xorg-libx11=1.8.4=h0b41bf4_0
- xorg-libxau=1.0.9=h7f98852_0
- xorg-libxdmcp=1.1.3=h7f98852_0
- xorg-libxext=1.3.4=h0b41bf4_2
- xorg-libxfixes=5.0.3=h7f98852_1004
- xorg-libxrender=0.9.10=h7f98852_1003
- xorg-libxt=1.2.1=h7f98852_2
- xorg-renderproto=0.11.1=h7f98852_1002
- xorg-xextproto=7.3.0=h0b41bf4_1003
- xorg-xproto=7.0.31=h7f98852_1007
- xz=5.2.6=h166bdaf_0
- zipp=3.15.0=pyhd8ed1ab_0
- zlib=1.2.13=h166bdaf_4
- zstd=1.5.2=h3eb15da_6
- pip:
- absl-py==1.4.0
- astunparse==1.6.3
- cachetools==5.3.0
- charset-normalizer==3.1.0
- flatbuffers==23.3.3
- gast==0.4.0
- google-auth==2.16.2
- google-auth-oauthlib==0.4.6
- google-pasta==0.2.0
- grpcio==1.51.3
- h5py==3.8.0
- idna==3.4
- importlib-metadata==6.1.0
- keras==2.11.0
- libclang==15.0.6.1
- markdown==3.4.1
- markupsafe==2.1.2
- oauthlib==3.2.2
- opt-einsum==3.3.0
- protobuf==3.19.6
- pyasn1==0.4.8
- pyasn1-modules==0.2.8
- requests==2.28.2
- requests-oauthlib==1.3.1
- rsa==4.9
- tensorboard==2.11.2
- tensorboard-data-server==0.6.1
- tensorboard-plugin-wit==1.8.1
- tensorflow==2.11.0
- tensorflow-estimator==2.11.0
- tensorflow-io-gcs-filesystem==0.31.0
- termcolor==2.2.0
- typing-extensions==4.5.0
- urllib3==1.26.15
- werkzeug==2.2.3
- wrapt==1.15.0
64 changes: 35 additions & 29 deletions run_nerf.py
View file
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Original file line number Diff line number Diff line change
Expand Up @@ -13,7 +13,6 @@
from load_deepvoxels import load_dv_data
from load_blender import load_blender_data


tf.compat.v1.enable_eager_execution()


Expand Down Expand Up @@ -667,6 +666,9 @@ def train():
with open(f, 'w') as file:
file.write(open(args.config, 'r').read())

testimgdir = os.path.join(basedir, expname, 'tboard_val_imgs')
os.makedirs(testimgdir, exist_ok=True)

# Create nerf model
render_kwargs_train, render_kwargs_test, start, grad_vars, models = create_nerf(
args)
Expand Down Expand Up @@ -706,7 +708,7 @@ def train():
if args.lrate_decay > 0:
lrate = tf.keras.optimizers.schedules.ExponentialDecay(lrate,
decay_steps=args.lrate_decay * 1000, decay_rate=0.1)
optimizer = tf.keras.optimizers.Adam(lrate)
optimizer = tf.keras.optimizers.legacy.Adam(lrate)
models['optimizer'] = optimizer

global_step = tf.compat.v1.train.get_or_create_global_step()
Expand Down Expand Up @@ -750,9 +752,9 @@ def train():
print('VAL views are', i_val)

# Summary writers
writer = tf.contrib.summary.create_file_writer(
writer = tf.summary.create_file_writer(
os.path.join(basedir, 'summaries', expname))
writer.set_as_default()
# writer.set_as_default()

for i in range(start, N_iters):
time0 = time.time()
Expand Down Expand Up @@ -835,7 +837,8 @@ def train():
def save_weights(net, prefix, i):
path = os.path.join(
basedir, expname, '{}_{:06d}.npy'.format(prefix, i))
np.save(path, net.get_weights())
# np.save(path, net.get_weights())
np.save(path, np.asanyarray(net.get_weights(), object))
print('saved weights at', path)

if i % args.i_weights == 0:
Expand Down Expand Up @@ -875,12 +878,13 @@ def save_weights(net, prefix, i):

print(expname, i, psnr.numpy(), loss.numpy(), global_step.numpy())
print('iter time {:.05f}'.format(dt))
with tf.contrib.summary.record_summaries_every_n_global_steps(args.i_print):
tf.contrib.summary.scalar('loss', loss)
tf.contrib.summary.scalar('psnr', psnr)
tf.contrib.summary.histogram('tran', trans)
# with tf.summary.record_summaries_every_n_global_steps(args.i_print):
with writer.as_default():
tf.summary.scalar('loss', loss, step=i)
tf.summary.scalar('psnr', psnr, step=i)
tf.summary.histogram('tran', trans, step=i)
if args.N_importance > 0:
tf.contrib.summary.scalar('psnr0', psnr0)
tf.summary.scalar('psnr0', psnr0, step=i)

if i % args.i_img == 0:

Expand All @@ -895,31 +899,33 @@ def save_weights(net, prefix, i):
psnr = mse2psnr(img2mse(rgb, target))

# Save out the validation image for Tensorboard-free monitoring
testimgdir = os.path.join(basedir, expname, 'tboard_val_imgs')
if i==0:
os.makedirs(testimgdir, exist_ok=True)
imageio.imwrite(os.path.join(testimgdir, '{:06d}.png'.format(i)), to8b(rgb))

with tf.contrib.summary.record_summaries_every_n_global_steps(args.i_img):
# testimgdir = os.path.join(basedir, expname, 'tboard_val_imgs')
# if i==0:
# os.makedirs(testimgdir, exist_ok=True)
imageio.imwrite(os.path.join(testimgdir, '{:06d}.png'.format(i)), to8b(rgb))

tf.contrib.summary.image('rgb', to8b(rgb)[tf.newaxis])
tf.contrib.summary.image(
'disp', disp[tf.newaxis, ..., tf.newaxis])
tf.contrib.summary.image(
'acc', acc[tf.newaxis, ..., tf.newaxis])
# with tf.summary.record_summaries_every_n_global_steps(args.i_img):
with writer.as_default():
tf.summary.image('rgb', to8b(rgb)[tf.newaxis], step=i)
tf.summary.image(
'disp', disp[tf.newaxis, ..., tf.newaxis], step=i)
tf.summary.image(
'acc', acc[tf.newaxis, ..., tf.newaxis], step=i)

tf.contrib.summary.scalar('psnr_holdout', psnr)
tf.contrib.summary.image('rgb_holdout', target[tf.newaxis])
tf.summary.scalar('psnr_holdout', psnr, step=i)
tf.summary.image('rgb_holdout', target[tf.newaxis], step=i)

if args.N_importance > 0:

with tf.contrib.summary.record_summaries_every_n_global_steps(args.i_img):
tf.contrib.summary.image(
'rgb0', to8b(extras['rgb0'])[tf.newaxis])
tf.contrib.summary.image(
'disp0', extras['disp0'][tf.newaxis, ..., tf.newaxis])
tf.contrib.summary.image(
'z_std', extras['z_std'][tf.newaxis, ..., tf.newaxis])
# with tf.summary.record_summaries_every_n_global_steps(args.i_img):
with writer.as_default():
tf.summary.image(
'rgb0', to8b(extras['rgb0'])[tf.newaxis], step=i)
tf.summary.image(
'disp0', extras['disp0'][tf.newaxis, ..., tf.newaxis], step=i)
tf.summary.image(
'z_std', extras['z_std'][tf.newaxis, ..., tf.newaxis], step=i)

global_step.assign_add(1)

Expand Down
2 changes: 1 addition & 1 deletion run_nerf_helpers.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@
def img2mse(x, y): return tf.reduce_mean(tf.square(x - y))


def mse2psnr(x): return -10.*tf.log(x)/tf.log(10.)
def mse2psnr(x): return -10.*tf.math.log(x)/tf.math.log(10.)


def to8b(x): return (255*np.clip(x, 0, 1)).astype(np.uint8)
Expand Down