Is it possible to run ssd_mobilenet_v1_fpn on Android for inference?

Question

I'm making an object detection app for Android, I got good performance while training with ssd_mobilenet_v1_fpn model.

I exported frozen inference graph, converted to tflite and quantized it to improve performance. But when i try it on TensorFlow Lite Object Detection Android Demo the app crashes.

The app works perfectly with the default model (ssd_mobilenet_v1) but unfortunately isn't good for small objects detection and classification.

Here my quantized ssd_mobilenet_v1_fpn model:

Google Drive: https://drive.google.com/file/d/1rfc64nUJzHQjxigD6hZ6FqxyGhLRbyB1/view?usp=sharing

OneDrive: https://univpr-my.sharepoint.com/:u:/g/personal/vito_filomeno_studenti_unipr_it/EXtl9aitsUZBg6w3awcLbfcBGBgrSV4kqBdSlS3LJOXKkg?e=kHEcy2

Here the unquantized model:

Googe Drive: https://drive.google.com/file/d/11c_PdgobP0jvzTnssOkmcjp19DZoBAAQ/view?usp=sharing

OneDrive: https://univpr-my.sharepoint.com/:u:/g/personal/vito_filomeno_studenti_unipr_it/EcVpJ44Daf5OgpVTYG1eD38B6P1mbnospRb8wXU_WQRh0g?e=cIgpQ2

For quantization i used this command line:

bazel run -c opt tensorflow/lite/toco:toco -- \ --input_file=tflite_graph.pb \ --output_file=detect_quant.tflite \ --input_shapes=1,640,480,3 \ --input_arrays=normalized_input_image_tensor \ --output_arrays=TFLite_Detection_PostProcess,TFLite_Detection_PostProcess:1,TFLite_Detection_PostProcess:2,TFLite_Detection_PostProcess:3 \ --inference_type=QUANTIZED_UINT8 \ --mean_values=128 \ --std_values=128 \ --change_concat_input_ranges=false \ --allow_custom_ops --default_ranges_min=0 --default_ranges_max=6

I also tried tflite converter python api, but it doesn't work for this model.

Here the android logcat errors: Errors

2020-09-16 18:54:06.363 29747-29747/org.tensorflow.lite.examples.detection E/Minikin: Could not get cmap table size!

2020-09-16 18:54:06.364 29747-29767/org.tensorflow.lite.examples.detection E/MemoryLeakMonitorManager: MemoryLeakMonitor.jar is not exist!

2020-09-16 18:54:06.871 29747-29747/org.tensorflow.lite.examples.detection E/BufferQueueProducer: [] Can not get hwsched service

2020-09-16 18:54:21.033 29747-29786/org.tensorflow.lite.examples.detection A/libc: Fatal signal 6 (SIGABRT), code -6 in tid 29786 (inference)

Has anyone managed to use an fpn model on android? or a model other than ssd_mobilenet_v1?

Answer 1

I couldn't find a way to run this model on Android, it probably isn't possible or my phone isn't powerful enough.

However I solved my problem by using two different networks, MobilenetV1 for object detection (detect only one class "object"), and one for classification (takes object's bounding boxes and classifies them). It's not the most elegant solution but at least it works.