getting-started.html

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    <h1>Getting Started</h1>
    <p>Get up and running with OpenEyes in 5 minutes</p>
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    <h2>Prerequisites</h2>
    <ul>
      <li>NVIDIA Jetson Orin Nano (4GB or 8GB), Raspberry Pi 5, Intel NPU, Hailo, or Qualcomm</li>
      <li>CSI Camera (IMX219), USB Webcam, or RealSense D455</li>
      <li>Ubuntu 22.04 installed</li>
      <li>Internet connection</li>
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    <h2>Clone & Install</h2>
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      <pre><code>git clone https://github.com/mandarwagh9/openeyes.git
cd openeyes
pip install -r requirements.txt</code></pre>
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    <h2>Verify Camera</h2>
    <h3>USB Webcam</h3>
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      <pre><code>ls /dev/video*
python3 -c "import cv2; cap = cv2.VideoCapture(0); print('OK' if cap.isOpened() else 'Error'); cap.release()"</code></pre>
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    <h3>CSI Camera</h3>
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      <pre><code>ls -la /dev/video*
gst-launch-1.0 nvarguscamerasrc sensor-id=0 ! fakesink</code></pre>
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    <h2>Run the Vision System</h2>
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      <pre><code># With debug window
python src/main.py --debug

# Headless
python src/main.py

# With ROS2
python src/main.py --ros2

# With world model (predictive tracking)
python src/main.py --world-model lewm --follow

# With industry template
python src/main.py --template warehouse --debug

# Turbo mode for max FPS
python src/main.py --turbo --world-model lewm

# Process video files
python src/main.py --video input.mp4 --output output.mp4</code></pre>
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    <h2>Jetson Optimization</h2>
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      <pre><code>sudo bash scripts/jetson_perf.sh
# Sets MAXN SUPER mode + jetson_clocks</code></pre>
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    <h2>Next Steps</h2>
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      <li><a href="commands.html">Explore all commands</a></li>
      <li><a href="safety.html">Safety & Reliability Features</a></li>
      <li><a href="ros2.html">Set up ROS2 integration</a></li>
      <li><a href="hardware.html">View hardware specs</a></li>
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    <h2>v2.5.0 — World Models & Predictive Intelligence</h2>
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      <pre><code># LeWM world model (15M params, 100-200 Hz planning)
python src/main.py --world-model lewm --follow

# With predictive safety evaluation
python src/main.py --world-model lewm --safety-predict

# Industry templates (warehouse, manufacturing-qa, agriculture, retail)
python src/main.py --template warehouse
python src/main.py --template manufacturing-qa

# Depth model selection (midas-small, da3-small, da3-base)
python src/main.py --depth-model da3-small</code></pre>
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    <h2>v0.7.0+ New Features</h2>
    <h3>Multi-Modal Sensing</h3>
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      <pre><code># Enable LIDAR processing
python src/main.py --lidar --lidar-topic /scan

# Enable RealSense D455
python src/main.py --realsense

# Multi-camera mode
python src/main.py --multi-camera</code></pre>
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    <h3>VLA & Performance (v0.8.0+)</h3>
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      <pre><code># INT8 quantization (~2x faster)
python src/main.py --int8

# INT8 + DLA (~3x faster)
python src/main.py --int8 --dla

# Maximum FPS
python src/main.py --no-face --no-gesture --no-pose --no-depth --int8 --dla</code></pre>
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    <h3>Safety Features (v1.0.0+)</h3>
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      <pre><code># Enable safety controller
python src/main.py --safety --max-velocity 0.5 --min-distance 0.5

# Enable health monitoring
python src/main.py --health-monitor

# Full production mode
python src/main.py --safety --health-monitor --ota-update</code></pre>
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