Update Dockerfile

Dockerfile

@@ -3,14 +3,11 @@ FROM pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime
 ENV DEBIAN_FRONTEND=noninteractive
 ENV MKL_THREADING_LAYER=GNU
 
-# Install dependencies, including OpenBLAS
+# Install dependencies
 RUN apt-get update && apt-get install -y \
     git wget libgl1-mesa-glx libglib2.0-0 ffmpeg libx264-dev \
-    build-essential cmake g++ python3-dev
-
-# Install required system dependencies
-RUN apt-get update && apt-get install -y \
-    software-properties-common wget gnupg2 && \
+    build-essential cmake g++ python3-dev software-properties-common \
+    wget gnupg2 libopenblas-dev && \
     rm -rf /var/lib/apt/lists/*
 
 # Add NVIDIA package repositories
@@ -18,12 +15,8 @@ RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86
     dpkg -i cuda-keyring_1.0-1_all.deb && \
     apt-get update
 
-# Install CUDA libraries manually
-RUN apt-get install -y \
-    cuda-command-line-tools-11-7 \
-    libcusolver-dev-11-7 \
-    libcublas-dev \
-    libcudnn8
+# Install CUDA Toolkit (includes libcublas)
+RUN apt-get install -y cuda-toolkit-11-7 libcudnn8
 
 # Create a user
 RUN useradd -m -u 1000 user
@@ -63,8 +56,8 @@ RUN pip install --no-cache-dir urllib3 transformers yacs scipy scikit-image scik
 # Install CMake first
 RUN pip install cmake
 
-# Force dlib to detect CUDA
-RUN pip install dlib --global-option=build_ext --global-option="-DCUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda" -vvv
+# Install dlib with CUDA support (force source compilation)
+RUN pip install --no-cache-dir dlib -vvv --no-binary dlib
 
 # Copy application file
 COPY app.py .