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TDA4VM: Jacinto TI Edge AI Monthly Webinar (Jul 2021): Embedded deep learning deployment. Demystified.

Part Number: TDA4VM

In this webinar, the third in our monthly series on TI Edge AI technology, you will learn how TI Edge AI processors and software solutions let you maximize AI model performance on specialized deep learning accelerators without having to program the cores. Our solutions let you deploy AI models to your embedded applications with industry-standard APIs (e.g. TensorFlow Lite, ONNX Runtime and TVM). This approach combines the performance advantages of TI Edge AI processors with a programming environment that is simple, flexible, and easy to use.

Webinar topics:

  • Visualizing deep learning models to understand how they operate on an embedded processor
  • Optimization techniques to maximize performance
  • Using industry-standard APIs to compile, deploy, and accelerate your models
  • Hands-on session to explore various deployment techniques
  • TI Model Zoo—60+ pre-compiled models to help you develop faster and more efficiently
  • Performance benchmarking methodologies—what you need to know


Register below for one of the two sessions depending on your timezone.

Session1: Wednesday, July 14, 2021 10:00 am, Central Daylight Time (Chicago, GMT-05:00)
Session2: Wednesday, July 14, 2021 9:00 pm, Central Daylight Time (Chicago, GMT-05:00)


it is recommended to watch the previous webinar to understand the development flow at the link below.

training.ti.com/build-edge-ai-hello-world-application-using-free-online-tools

Please feel free to post any questions below for preparation or if you have any difficulty running the previous webinar code.

  • Thank you all for your interest in the webinar.

    The attached ZIP file has code examples and other required scripts for you to reproduce the results either during the webinar or after at your convenience.

    Directory Contents
    ==================
    - README: this file
    - other files and scripts needed for the program.

    You can bypass any step using this code base. For example, if you do not want to download all the required SW on the PC, you can directly go to step 2 and run the hello world program on the cloud tool directly. Or, you can run it directly on the Edge AI Starter Kit EVM.
    =================================================================================================

    EdgeAI cloud tool: https://dev.ti.com/edgeai/

    Step 1: Develop the hello world example on your computer (PC, MAC or Linux)
    Jupyter Notebook: 1_PC_HelloWebinar.ipynb : runs on the PC


    Step 2: Run the same example on TI's Jacinto hardware in the cloud or on the edgeAI SK tool as-is
    Jupyter Notebook: 2_EdgeAI_ARM_ONLY.ipynb : runs on the Edge AI Cloud tool


    Step 3: Enable deep learning acceleration to make this detection real-time.
    Jupyter Notebook: 3_EdgeAI_Model_Compile_Run.ipynb : runs on the Edge AI Cloud tool for model compilation and inference

    Final Step: Run the same program (inference) on the Edge AI Starter Kit.

    Jupyter Notebook: 4_Infer_SK_EVM_ARM_ONLY.ipynb : runs on the Edge AI starter kit on ARM

    Jupyter Notebook: 4_Infer_SK_EVM_DL_acceleration.ipynb : runs on the Edge AI Cloud tool with deep learning acceleration

    Once you have these code examples running, you can read through the code along with the webinar slides and video to understand what each of the code segment is doing.

    Thank you and let us know if you run into any issues.

    Welcome to the AI world with TI Jacinto solutions!

    Update: 

    Added final step of running inference on Edge AI Starter Kit EVM.

    Also, updated the model to use SSD mobilenet_v2_300

    HelloWorld_PC_Cloud_TDA4VM_SK_EVM_v2.zip