{
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   "source": [
    "# Loading your First Example\n",
    "\n",
    "\n",
    "## Goals\n",
    "\n",
    "* Understand the system architecture of an x86 Ryzen AI processor\n",
    "\n",
    "* Introduction to the NPU architecture and tiles\n",
    "\n",
    "* Introduction to the Riallto `npu` Python package\n",
    "\n",
    "* Launch an example of a video processing application on the NPU for the first time by calling it from Python"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## References\n",
    "\n",
    "**[Dataflow Architecture](https://en.wikipedia.org/wiki/Dataflow_architecture)**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "---\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "These notebooks will walk you through the key architectural features of the Ryzen AI NPU using a series of video processing examples.\n",
    "\n",
    "\n",
    "<div class=\"alert alert-box alert-success\">\n",
    "This is a reminder that this material can be viewed on the <a href=\"https://www.riallto.ai/\">Riallto webpages</a>. \n",
    "    \n",
    "If you have a Ryzen AI laptop, you should install Riallto and open this material as Jupyter notebooks from within the Riallto framework. You will be able to execute the code in the cells below on the Ryzen AI NPU in your laptop. \n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## System Architecture\n",
    "\n",
    "These examples assume you are using a laptop with a [Ryzen 7040 \"Phoenix\" APU with the Ryzen AI NPU](https://www.amd.com/en/products/processors/consumer/ryzen-ai.html) and an integrated webcam,  or compatible hardware. The typical architecture of the system for the examples is shown below."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center><img src=\"./images/png/ryzen_ai_labels.png\" style=\"max-height: 450px; width:auto; height:auto;\"></center>\n",
    "<center><strong>Ryzen 7040 connected to system memory, webcam and display</strong></center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "The AMD Ryzen 7040 \"Phoenix\" family of laptop and desktop processors has an *AMD Zen 4 **CPU*** (which is an x86 CPU), and *Ryzen AI **NPU*** integrated into the same chip, as indicated in the image.\n",
    "\n",
    "The APU is connected to system memory. System memory is used as the interface between the NPU and the rest of the system. For example, the webcam, controlled by the CPU, will place input data into system memory where the NPU can read it. The NPU will write its results to system memory where it can then be accessed by the CPU and sent to the display. \n",
    "\n",
    "<div class=\"alert alert-box alert-info\">\n",
    "The role of the Ryzen AI NPU is to offload computationally intensive AI workloads from the main x86 CPU or GPU (integrated GPU or discrete GPU) to the NPU. The NPU runs these workloads more power efficiently than the CPU or GPU.\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Video Pipeline\n",
    "\n",
    "The CPU controls the webcam and display that are used as the data source and sink for the application. The CPU will configure the webcam which will write input data to system memory. The NPU will read the webcam data and write its results back to system memory where the CPU can access the results for the display.\n",
    "\n",
    "This diagram shows a simplified representation of the capture-to-display video processing pipeline of your laptop."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center><img src=\"./images/png/pipeline_flow_of_data.png\" style=\"max-height: 150px; width:auto; height:auto;\"></center>\n",
    "<center><strong>Simplified Ryzen AI NPU video processing pipeline</strong></center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "This is the same video pipeline that Microsoft Windows Studio Effects uses for automatic framing, gaze adjustment and background effects."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ryzen AI NPU Architecture\n",
    "\n",
    "The Ryzen AI NPU is any array of compute, memory and interface tiles. There are 20 compute tiles arranged in a 4x5 grid of rows and columns. There are 5 memory tiles and 4 interfaces tiles. Interface tiles connect the NPU to system memory. You will notice an asymmetry in the number of interface tiles and memory tiles.  \n",
    "\n",
    "Tiles are connected to each other through a network of streaming interfaces."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<center><img src=\"./images/png/ryzenai_array_5x4.png\" style=\"max-height: 450px; width:auto; height:auto;\"></center>\n",
    "<center><strong>Ryzen AI NPU organization</strong></center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Compute tiles are where the program or subprograms of a software application are run. Memory and interface tiles move data into and out of the NPU and marshal data movement within the array. Each of the tiles, their features, and interfaces will be introduced in more detail as we progress through these notebooks. \n",
    "\n",
    "---\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Color Threshold Example"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We selected the color threshold as it is the simplest application to start exploring the capabilities of the NPU.\n",
    "\n",
    "The first example we will use is a color thresholding application. The algorithm works on each pixel individually. The threshold function $f(x)$ compares each pixel $x$ against a threshold value, $tv$, where $0 \\leq tv \\leq 255$, such that: \n",
    "\n",
    "$$\n",
    "f(x) = \n",
    "\\begin{cases} \n",
    "0, & \\text{if } x \\leq t \\\\ \n",
    "v, & \\text{if } x > t \n",
    "\\end{cases}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the example, you will be able to set the threshold value $tv$ and see the effect it has on the output video. \n",
    "\n",
    "The threshold algorithm is applied to each of the red, blue and green color channels in the original image separately. Pixel values in each channel that are below the threshold become black. The remaining pixels become red, green or blue respectively.  Note that we assign minimum and maximum color values. The outputs of the three color channels are re-combined to create the final image. \n",
    "\n",
    "The image below shows an example of the operation of the thresholding function. Using the Original image shown on the left, the image is split into its three color channels. Each channel is processed by the threshold function with a given threshold value.  The three channels will be recombined to form the processed output image. The output image will depend on the values of the threshold values used for each channel. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "<center><img src=\"./images/png/toucan_color_threshold.png\"></center>\n",
    "<center><strong>Example of the color threshold algorithm</strong></center>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "----\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Riallto `npu` Python Package and the video library"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To make the NPU more accessible and easier to work with, as part of Riallto we have developed a Python package called `npu`.  In addition to other functionality that we will encounter later that will be used to build custom NPU applications, the Riallto `npu` package provides several useful utilities for checking the status of the NPU. One of these utilities is `nputop` (modelled after the [Linux `top` command](https://man7.org/linux/man-pages/man1/top.1.html)) which shows applications currently running on the NPU. Check the utilization of the NPU by running the following cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
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      "text/plain": [
       "Output()"
      ]
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     "metadata": {},
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    }
   ],
   "source": [
    "from npu import nputop\n",
    "\n",
    "nputop()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The output will report the current state of the NPU in your system. For example, if Microsoft Studio Effects are loaded, you will see this in the `nputop` report.   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Riallto `npu` package, includes a library of video processing example applications in the `videoapps` module in `npu.utils`. Explore the list of available applications by running the following cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['ColorDetectVideoProcessing',\n",
       " 'ColorThresholdVideoProcessing',\n",
       " 'DenoiseDPVideoProcessing',\n",
       " 'DenoiseTPVideoProcessing',\n",
       " 'EdgeDetectVideoProcessing',\n",
       " 'ScaledColorThresholdVideoProcessing',\n",
       " 'VideoApplication']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from npu.utils import videoapps\n",
    "\n",
    "videoapps()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will start by running the *Color Threshold* application (`ColorThresholdVideoProcessing`) and explore more these applications in later notebooks."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "---\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Run the Color Threshold Application\n",
    "\n",
    "The code to run the color threshold example is shown in the next code cell. \n",
    "\n",
    "This will load the application into the Ryzen AI NPU, and start the stream of data from your laptop webcam. The processed video output will be displayed below the code cell.\n",
    "\n",
    "The thresholding example has three widgets. If you run this notebook on a Ryzen AI laptop, you can use each of these widgets to control the threshold value for each of the red, blue and green channels and see the effect on the video stream. Experiment with the three widgets to see how different threshold levels on each channel effects the output.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
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       "Image(value=b'', format='jpeg')"
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       "Button(description='Stop', style=ButtonStyle())"
      ]
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   ],
   "source": [
    "from npu.lib import ColorThresholdVideoProcessing\n",
    "\n",
    "app = ColorThresholdVideoProcessing()\n",
    "app.start()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You should now see the application you just loaded in the `nputop` report:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
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       "model_id": "f64ce4a830604d3bbf6d013ed59897ff",
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      "text/plain": [
       "Output()"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nputop()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "<div class=\"alert alert-box alert-warning\">\n",
    "    After you have explored the application, click the <strong>Stop</strong> button under the video to finish the video stream and release the NPU and webcam.\n",
    "</div>\n",
    "\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Next Steps"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the next notebook we will see how the color threshold application can be mapped to the NPU, and explore the properties of the NPU tiles."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "---\n",
    "\n",
    "<center>\n",
    "Copyright&copy; 2023 AMD, Inc\n",
    "</center>\n",
    "<center>\n",
    "SPDX-License-Identifier: MIT\n",
    "</center>"
   ]
  }
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