i have a trained tensorflow model , for the training i select ssdmobilenetfpnlite(640x640) after that i convert my model to tflite. while inferencing i got only 3-4 fps how i increase that fps more than 25
Hi @Amit_Kumar_Tiwaree ,
Here are a few possibilities that you can increase Frames per second(fps) while inferencing:
From TFLIte point of view:
- Optimize the TFLite model to int8 quantization(improves the speed by 3x+) Ref.
- If your target device has hardware acceleration, use it to run your model. The supported delegates for hardware acceleration are: NNAPI on Android, GPU delegates on iOS and Android, and Edge TPU on Coral devices.
From Base model point of view: - Use the model optimization techniques like Pruning and knowledge distillation.
- If acceptable to the accuracy barometer, try to reduce the input image resolution to 320x320. It will significantly improve fps especially on low-end devices.
Thank You