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SSG-VQA is a Visual Question Answering (VQA) dataset on laparoscopic videos providing diverse, geometrically grounded, unbiased and surgical action-oriented queries generated using scene graphs.
Home Page: http://camma.u-strasbg.fr/datasets
License: Other
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getting the following error
D:\SSG-VQA>conda env create -f environment.yml
Retrieving notices: ...working... done
Collecting package metadata (repodata.json): done
Solving environment: failed
ResolvePackageNotFound:
libprotobuf==3.20.1=h4ff587b_0
numpy-base==1.23.1=py39ha15fc14_0
openh264==2.1.1=h4ff587b_0
pyjwt==2.4.0=py39h06a4308_0
libnghttp2==1.46.0=hce63b2e_0
tensorboard-plugin-wit==1.8.1=py39h06a4308_0
lame==3.100=h7b6447c_0
tk==8.6.11=h1ccaba5_1
readline==8.1.2=h7f8727e_1
ca-certificates==2022.07.19=h06a4308_0
libiconv==1.16=h7f8727e_2
cryptography==37.0.1=py39h9ce1e76_0
jpeg==9e=h7f8727e_0
brotlipy==0.7.0=py39h27cfd23_1003
re2==2022.04.01=h295c915_0
libssh2==1.10.0=h8f2d780_0
libstdcxx-ng==11.2.0=h1234567_1
nettle==3.7.3=hbbd107a_1
flatbuffers==2.0.0=h2531618_0
cffi==1.15.0=py39hd667e15_1
libwebp-base==1.2.2=h7f8727e_0
mkl-service==2.4.0=py39h7f8727e_0
mkl_fft==1.3.1=py39hd3c417c_0
hdf5==1.10.6=hb1b8bf9_0
libtasn1==4.16.0=h27cfd23_0
setuptools==61.2.0=py39h06a4308_0
ncurses==6.3=h7f8727e_2
_openmp_mutex==4.5=1_gnu
aiohttp==3.8.1=py39h7f8727e_1
intel-openmp==2021.4.0=h06a4308_3561
termcolor==1.1.0=py39h06a4308_1
libgfortran4==7.5.0=ha8ba4b0_17
mkl_random==1.2.2=py39h51133e4_0
torchaudio==0.11.0=py39_cu102
zipp==3.8.0=py39h06a4308_0
wrapt==1.14.1=py39h5eee18b_0
pillow==9.0.1=py39h22f2fdc_0
pip==21.2.4=py39h06a4308_0
yaml==0.2.5=h7b6447c_0
openssl==1.1.1q=h7f8727e_0
python==3.9.12=h12debd9_0
lcms2==2.12=h3be6417_0
tensorflow-base==2.8.2=mkl_py39hf890080_0
giflib==5.2.1=h7b6447c_0
libgomp==11.2.0=h1234567_1
libcurl==7.84.0=h91b91d3_0
cudatoolkit==10.2.89=hfd86e86_1
pysocks==1.7.1=py39h06a4308_0
libgcc-ng==11.2.0=h1234567_1
libunistring==0.9.10=h27cfd23_0
tensorflow-estimator==2.8.0=py39hb070fc8_0
zlib==1.2.12=h7f8727e_2
xz==5.2.5=h7f8727e_1
krb5==1.19.2=hac12032_0
keras==2.8.0=py39h06a4308_0
libedit==3.1.20210910=h7f8727e_0
sqlite==3.39.2=h5082296_0
numpy==1.23.1=py39h6c91a56_0
ffmpeg==4.3=hf484d3e_0
abseil-cpp==20211102.0=hd4dd3e8_0
certifi==2022.6.15=py39h06a4308_0
tensorflow==2.8.2=mkl_py39ha986a27_0
lz4-c==1.9.3=h295c915_1
libpng==1.6.37=hbc83047_0
libev==4.33=h7f8727e_1
libgfortran-ng==7.5.0=ha8ba4b0_17
c-ares==1.18.1=h7f8727e_0
click==8.0.4=py39h06a4308_0
freetype==2.11.0=h70c0345_0
ld_impl_linux-64==2.35.1=h7274673_9
libwebp==1.2.2=h55f646e_0
libidn2==2.3.2=h7f8727e_0
snappy==1.1.9=h295c915_0
gnutls==3.6.15=he1e5248_0
libtiff==4.2.0=h85742a9_0
zstd==1.4.9=haebb681_0
gmp==6.2.1=h2531618_2
libffi==3.3=he6710b0_2
mkl==2021.4.0=h06a4308_640
icu==58.2=he6710b0_3
grpc-cpp==1.46.1=h33aed49_0
bzip2==1.0.8=h7b6447c_0
libuv==1.40.0=h7b6447c_0