update dockerfile

Dockerfile

@@ -13,11 +13,10 @@ RUN pip install --no-cache-dir --upgrade -r requirements.txt
 COPY --chown=user . /app
 CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]
 FROM nvidia/cuda:11.1.1-cudnn8-devel-ubuntu18.04
-# use an older system (18.04) to avoid opencv incompatibility (issue#3524)
 
 ENV DEBIAN_FRONTEND noninteractive
 RUN apt-get update && apt-get install -y \
-	python3-opencv ca-certificates python3-dev git wget sudo ninja-build
+	python3-opencv ca-certificates python3-dev git wget sudo ninja-build 
 RUN ln -sv /usr/bin/python3 /usr/bin/python
 
 # create a non-root user
@@ -34,22 +33,15 @@ RUN wget https://bootstrap.pypa.io/pip/3.6/get-pip.py && \
 
 # install dependencies
 # See https://pytorch.org/ for other options if you use a different version of CUDA
-RUN pip install --user tensorboard cmake onnx   # cmake from apt-get is too old
-RUN pip install --user torch==1.10 torchvision==0.11.1 -f https://download.pytorch.org/whl/cu111/torch_stable.html
+RUN pip install --user tensorboard cmake onnx  
 
 RUN pip install --user 'git+https://github.com/facebookresearch/fvcore'
-# install detectron2
 RUN git clone https://github.com/facebookresearch/detectron2 detectron2_repo
-# set FORCE_CUDA because during `docker build` cuda is not accessible
 ENV FORCE_CUDA="1"
-# This will by default build detectron2 for all common cuda architectures and take a lot more time,
-# because inside `docker build`, there is no way to tell which architecture will be used.
 ARG TORCH_CUDA_ARCH_LIST="Kepler;Kepler+Tesla;Maxwell;Maxwell+Tegra;Pascal;Volta;Turing"
 ENV TORCH_CUDA_ARCH_LIST="${TORCH_CUDA_ARCH_LIST}"
 
 RUN pip install --user -e detectron2_repo
-
-# Set a fixed model cache directory.
 ENV FVCORE_CACHE="/tmp"
 WORKDIR /home/user/detectron2_repo