Setting Up Your Qualcomm Development Environment

This guide will walk you through the process of setting up a development environment for computer vision applications on Qualcomm platforms.

System Requirements

Component	Minimum Requirements	Recommended
Operating System	Ubuntu 18.04/20.04, Windows 10	Ubuntu 20.04 LTS
RAM	8GB	16GB or higher
Storage	128GB SSD	256GB SSD or higher
CPU	Intel/AMD x86_64, 4 cores	8+ cores
GPU	NVIDIA GTX 1060 or equivalent	NVIDIA RTX series

Software Installation

1. Install the Qualcomm Neural Processing SDK

# Download the SDK from Qualcomm Developer Network
# Extract and install
tar -xzf qnnsdk-v2.x.x.tar.gz
cd qnnsdk-v2.x.x
./setup.sh

2. Install Required Dependencies

# Ubuntu/Debian
sudo apt update
sudo apt install -y build-essential cmake libopencv-dev python3-dev python3-pip
pip3 install numpy tensorflow torch

# Include Qualcomm-specific packages
pip3 install snpe-sdk

3. Configure Development Tools

# Set up environment variables
echo 'export SNPE_ROOT=/path/to/snpe/installation' >> ~/.bashrc
echo 'export PATH=$PATH:$SNPE_ROOT/bin/x86_64-linux-clang' >> ~/.bashrc
source ~/.bashrc

IDE Setup

We recommend using one of the following IDEs for Qualcomm vision application development:

1. Visual Studio Code

   • Install C/C++ extension
   • Install Python extension
   • Configure include paths for Qualcomm SDK headers

2. Qt Creator

   • Particularly useful for applications with GUI components
   • Configure the kit to use the appropriate compiler

3. Android Studio

   • For Android-based Qualcomm device development
   • Install the NDK for native code development

Verifying Your Installation

Run the following test to verify your installation is working correctly:

cd $SNPE_ROOT/examples/NativeCpp/SampleApp
make
./bin/x86_64-linux-clang/snpe-sample

If the test runs successfully, you should see output demonstrating that the SDK can properly initialize and run a simple inference task.