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‎README.md‎

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@@ -31,8 +31,8 @@ Based on the platform you are using, select the following to get started:
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5. [LLM Finetuning Benchmark](usecases/ai/finetuning-benchmark/README.md)
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6. [LLM RAG Toolkit](usecases/ai/rag-toolkit/README.md)
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7. [AI Video Analytics](usecases/ai/ai-video-analytics/README.md)
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7. [Digital Avatar](usecases/ai/digital-avatar/README.md)
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8. [Digital Avatar](usecases/ai/digital-avatar/README.md)
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9. [Vision Edge AI](usecases/ai/vision-edge-ai/README.md)
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## Disclaimer
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GStreamer* is an open source framework licensed under LGPL. See https://gstreamer.freedesktop.org/documentation/frequently-asked-questions/licensing.html. You are solely responsible for determining if your use of GStreamer requires any additional licenses. Intel is not responsible for obtaining any such licenses, nor liable for any licensing fees due, in connection with your use of GStreamer.
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‎usecases/ai/vision-edge-ai/Dockerfile‎

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# Copyright (C) 2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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FROM ubuntu:24.10
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ARG DEBIAN_FRONTEND=noninteractive
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USER root
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#--------------------------------------------------------------------------------------------------------------------------
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# Essential Tools
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#--------------------------------------------------------------------------------------------------------------------------
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RUN apt update -y && apt install -y \
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software-properties-common \
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build-essential \
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wget \
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gpg \
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curl \
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pciutils \
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git \
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cmake \
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libopencv-dev \
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v4l-utils \
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libusb-1.0-0-dev \
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libssl-dev \
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libgtk-3-dev \
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pkg-config \
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udev \
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libudev-dev \
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libglfw3-dev \
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libgl1-mesa-dev \
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libglu1-mesa-dev \
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python3-pip \
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python3-dev \
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python3-setuptools \
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python3-opencv
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#--------------------------------------------------------------------------------------------------------------------------
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# Graphic & NPU drivers and tools
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#--------------------------------------------------------------------------------------------------------------------------
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# Install Intel GPU Drivers
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RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | \
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gpg --dearmor --output /usr/share/keyrings/intel-graphics.gpg && \
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echo "deb [arch=amd64,i386 signed-by=/usr/share/keyrings/intel-graphics.gpg] \
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https://repositories.intel.com/gpu/ubuntu noble client" \
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> /etc/apt/sources.list.d/intel-gpu-noble.list && \
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apt update -y && apt install -y libze1 intel-level-zero-gpu intel-opencl-icd clinfo
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# Install Intel NPU Drivers
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WORKDIR /tmp
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RUN apt install -y libtbb12
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RUN wget https://github.com/intel/linux-npu-driver/releases/download/v1.10.0/intel-driver-compiler-npu_1.10.0.20241107-11729849322_ubuntu24.04_amd64.deb \
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https://github.com/intel/linux-npu-driver/releases/download/v1.10.0/intel-fw-npu_1.10.0.20241107-11729849322_ubuntu24.04_amd64.deb \
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https://github.com/intel/linux-npu-driver/releases/download/v1.10.0/intel-level-zero-npu_1.10.0.20241107-11729849322_ubuntu24.04_amd64.deb && \
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dpkg -i *.deb && rm -f *.deb
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# Install Intel PCM Tool
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RUN git clone --recursive https://github.com/intel/pcm && \
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cd pcm && mkdir build && cd build && \
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cmake .. && cmake --build . --parallel && make install && \
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rm -rf /tmp/pcm
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#--------------------------------------------------------------------------------------------------------------------------
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# OpenVINO
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#--------------------------------------------------------------------------------------------------------------------------
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WORKDIR /opt/intel
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# Install OpenVINO
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RUN curl -L https://storage.openvinotoolkit.org/repositories/openvino/packages/2024.5/linux/l_openvino_toolkit_ubuntu24_2024.5.0.17288.7975fa5da0c_x86_64.tgz \
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--output openvino.tgz
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RUN tar -xf openvino.tgz
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RUN mv l_openvino_toolkit_ubuntu24_2024.5.0.17288.7975fa5da0c_x86_64 openvino
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RUN cd openvino && sed -i 's/24\.04/24\.10/g' ./install_dependencies/install_openvino_dependencies.sh && \
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bash ./install_dependencies/install_openvino_dependencies.sh -y
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ENV OPENVINO_DIR=/opt/intel/openvino
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RUN pip install --pre -U openvino openvino-dev --extra-index-url https://storage.openvinotoolkit.org/simple/wheels/nightly --break-system-packages
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#--------------------------------------------------------------------------------------------------------------------------
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# librealsense
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#--------------------------------------------------------------------------------------------------------------------------
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WORKDIR /tmp
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RUN git clone https://github.com/IntelRealSense/librealsense
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RUN cd librealsense && mkdir build && cd build && \
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cmake .. -DBUILD_PYTHON_BINDINGS=ON -DPYTHON_EXECUTABLE=$(which python3) && \
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make -j$(nproc) && \
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make install && \
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ldconfig
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#python3 -m pip install --no-cache-dir pyrealsense2 --break-system-packages
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ENV PYTHONPATH=/usr/local/lib/python3.12/dist-packages
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#--------------------------------------------------------------------------------------------------------------------------
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# Required Python Packages
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#--------------------------------------------------------------------------------------------------------------------------
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RUN pip3 install --break-system-packages \
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fire \
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distro \
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zeroconf \
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psutil \
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cython \
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prometheus-client \
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zeroconf
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RUN pip3 install --break-system-packages \
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yt-dlp \
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youtube_dl \
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pafy
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RUN apt remove -y python3-blinker || true
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RUN pip3 install --break-system-packages \
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flask \
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flask_bootstrap
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RUN pip3 install --break-system-packages \
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nncf \
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ultralytics
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#--------------------------------------------------------------------------------------------------------------------------
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# Video Steams Download
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#--------------------------------------------------------------------------------------------------------------------------
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WORKDIR /opt/videos
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RUN wget -O streat.mp4 https://videos.pexels.com/video-files/3759216/3759216-sd_640_360_30fps.mp4
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#RUN wget -O animals.mp4 https://videos.pexels.com/video-files/4938060/4938060-uhd_2732_1440_30fps.mp4
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#--------------------------------------------------------------------------------------------------------------------------
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# Models Preparation
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#--------------------------------------------------------------------------------------------------------------------------
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WORKDIR /opt/models
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COPY ./utils/models.sh /tmp/
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RUN /tmp/models.sh
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RUN rm -rf /tmp/*
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WORKDIR /workspace
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‎usecases/ai/vision-edge-ai/Makefile‎

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# Copyright (C) 2024 Intel Corporation
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# SPDX-License-Identifier: Apache-2.0
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#----------------------------------------------------------------------------------------------------------------------
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# Flags
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#----------------------------------------------------------------------------------------------------------------------
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SHELL := /bin/bash
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CURRENT_DIR := $(shell dirname $(realpath $(lastword $(MAKEFILE_LIST))))
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DOCKER_IMAGE_NAME = vision_edge_ai
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SERVICE_NAME = vision_edge_ai
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# Proxy settings (default to empty if not set)
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PORT ?= 80
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export PORT
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HOST_ADDRESS="0.0.0.0"
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export HOST_ADDRESS
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#----------------------------------------------------------------------------------------------------------------------
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# Docker Settings
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#----------------------------------------------------------------------------------------------------------------------
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export DOCKER_BUILDKIT=1
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DOCKER_COMPOSE_ENV = \
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DOCKER_IMAGE_NAME=$(DOCKER_IMAGE_NAME) \
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HTTP_PROXY=$(HTTP_PROXY) \
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HTTPS_PROXY=$(HTTPS_PROXY) \
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NO_PROXY=$(NO_PROXY) \
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MKL_THREADING_LAYER=gnu \
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CURRENT_DIR=$(CURRENT_DIR) \
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PORT=${PORT} \
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HOST_ADDRESS=$(HOST_ADDRESS)
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#----------------------------------------------------------------------------------------------------------------------
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# Targets
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#----------------------------------------------------------------------------------------------------------------------
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default: run
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.PHONY: build app run bash
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build:
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@$(call msg, Building Docker image ${DOCKER_IMAGE_NAME} ...)
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@$(DOCKER_COMPOSE_ENV) docker-compose build
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@docker-compose run --rm $(SERVICE_NAME) bash -c \
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'cd ./utils/ && python3 setup.py build_ext --quiet --inplace'
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run: stop
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@$(call msg, Running the Vision Edge AI application ...)
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@docker-compose up -d
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stop: build
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@$(call msg, Stopping the Vision Edge AI application ...)
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@docker-compose down --remove-orphans # Ensure old orphaned containers are removed
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install_prerequisites:
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@$(call msg, Installing Prerequisites ...)
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@cd ./tools && bash ./install.sh
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bash:
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@$(call msg, Opening a bash session in the container ...)
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@docker-compose run --rm $(SERVICE_NAME) bash
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#----------------------------------------------------------------------------------------------------------------------
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# Helper Functions
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#----------------------------------------------------------------------------------------------------------------------
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define msg
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tput setaf 2 && \
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for i in $(shell seq 1 120 ); do echo -n "-"; done; echo "" && \
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echo " "$1 && \
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for i in $(shell seq 1 120 ); do echo -n "-"; done; echo "" && \
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tput sgr0
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endef
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‎usecases/ai/vision-edge-ai/README.md‎

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# VisionEdgeAI
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VisionEdgeAI is a Flask web application designed for real-time AI-based vision processing. It enables users to process and analyze video streams efficiently using AI models, all through a simple and interactive web interface. The application is Docker-based and Intel hardware agnostic, ensuring compatibility across various Intel platforms.
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<p align="center">
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<img src="static/images/screenshot_1.png" alt="VisionEdgeAI Screenshot">
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</p>
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---
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## Features:
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- **Web-based UI** for easy interaction.
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- **Real-time AI inference** for vision tasks.
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- **Supports multiple AI models**.
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- **Optimized for CPU, GPU, and NPU acceleration**.
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## Supported Distributions
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This application currently supports the following Ubuntu versions:
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- **Ubuntu 22.04**
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- **Ubuntu 24.04**
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- **Ubuntu 24.10**
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## Installation Instructions
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1. **Clone or Extract the Repository**
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If you haven't already, clone or unzip the VisionEdgeAI project.
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2. **Navigate to the Project Directory**
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```bash
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cd vision-edge-ai
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```
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3. **Install Dependencies**
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Run the following command to install prerequisites (kernel, GPU & NPU drivers, Docker):
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```bash
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make install_prerequisites
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```
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For detailed instructions on setting up dependencies, refer to the [tools/README.md](tools/README.md) file.
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4. **Start the Application**
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To start the application, run:
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```bash
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make
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```
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By default, the application binds to 0.0.0.0, allowing it to be accessible from other machines. To restrict access to the local machine only, you can set the HOST_ADDRESS environment variable. To do this, run
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```bash
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export HOST_ADDRESS="127.0.0.1"
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```
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5. **Stop the Application**
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To stop the application, run:
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```bash
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make stop
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```
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## Usage Instructions
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1. **Open a Web Browser**
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Once the Flask application starts, access it by opening the following URL in your browser:
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```
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http://<server-ip-address>
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```
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Replace `<server-ip-address>` with the IP address of the machine running the application.

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