In this session, Wafa, a robotic teacher and embedded system engineer, explains the process of deploying an object detection model on an ESP32 CAM. The tutorial covers the steps for training a custom model using YOLO v5, collecting and labeling data, utilizing Edge Impulse and RoboFlow for data preparation, training with Google Colab, and converting the model to TensorFlow Lite for microcontroller deployment. Additionally, Wafa discusses setting up the ESP-IDF environment, configuring camera settings, and the importance of ensuring correct model parameters for successful implementation. Watch to learn how to effectively deploy machine learning models on microcontroller devices, with an emphasis on ESP32 CAM.

00:00 Introduction
02:26 Collecting and Labeling Data
05:27 Training the Model with YOLOv5
09:52 Converting and Deploying the Model
14:06 Configuring ESP32 for Deployment
27:26 Final Steps and Troubleshooting
29:52 Q&A and Closing Remarks

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#objectdetection #machinelearning #embeddedsystems #microcontrollers #robotics #edgeai #esp32cam #yolov5 #tensorflow #esp32 #modeldeployment #ai

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