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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

Python 100.00%
scene-graph surgical-data-science vqa-dataset

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ssg-vqa's Issues

not able to run - conda env create -f environment.yml

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

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