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DIIDevHeads IoT Integration Server
•Created by Boss lady on 9/27/2024 in #iot-cloud
How do I optimize and deploy a deep learning model on an ESP32?
@Boss lady To deploy your deep learning model for image recognition on the
ESP32, you need to optimize it to address memory constraints. The MemoryError occurs because the model is too large for the ESP32’s available memory. To resolve this, you can:
- Quantize the Model: Convert the model to an 8-bit format using TensorFlow Lite’s post-training quantization, which significantly reduces the model size and memory usage.
- Simplify the Model: Reduce the complexity by using fewer layers, neurons, or switching to more efficient architectures like MobileNet or TinyML models.
- Use Additional Optimizations: Techniques like pruning or weight clustering can further shrink the model.
Once optimized, test the model on the ESP32 to ensure it fits and runs inference efficiently.4 replies