Question/Issue:
I’m experimenting with Image Classification on the ESP32‑S3. However, only one specific project fails at startup with an error during AllocateTensors(). The error message suggests it’s running out of memory, but according to the Deployment tab, the RAM usage is about 251 KB, so it seems like there should be enough.
Does anyone know how to investigate this issue or how to fix it?
Logs:
Starting continious inference in 2 seconds...
AllocateTensors() failedERR: Failed to run classifier (-3)
AllocateTensors() failedERR: Failed to run classifier (-3)
AllocateTensors() failedERR: Failed to run classifier (-3)
AllocateTensors() failedERR: Failed to run classifier (-3)
AllocateTensors() failedERR: Failed to run classifier (-3)
AllocateTensors() failedERR: Failed to run classifier (-3)
AllocateTensors() failedERR: Failed to run classifier (-3)
AllocateTensors() failedERR: Failed to run classifier (-3)
AllocateTensors() failedERR: Failed to run classifier (-3)
Project ID:
1004578
Reproducibility:
- [x] Always
- [ ] Sometimes
- [ ] Rarely
Environment:
- Platform: Seeed Studio XIAO ESP32S3 Sense
- Build Environment Details: Arduino IDE 2.3.8, ESP32 BSP 3.3.8
- OS Version: Windows 11
Edge Impulse:
- Impulse: Image data 96x96 - Image - Transfer Learning(Images)
- Image: Grayscale
- Transfer learning: Profile int8 model, MobileNetV2 96x96 0.35(8neurons, 0.1dropout)
- Deployment: Arduino library, TensorFlow Lite, Quantized(int8)
