无法将.pb 图转换为 tflite

Question

I am creating a custom object detection sample for android, I used the ssd_mobilenet_v1_coco pretrained model for transfer learning and got a decent accuracy. I also successfully managed to export the model.ckpt-XXXX to a .pb tflite graph using this line of code in the terminal (ran from the object_detection folder after cloning Tensorflow Object Detection API from github):

python export_tflite_ssd_graph.py --pipeline_config_path=training/ssd_mobilenet_v1_coco.config --trained_checkpoint_prefix=training/model.ckpt-40500--output_directory=tflite --add_postprocessing_op=true

The above created a folder tflite and it contained 2 files:

1. tflite_graph.pb
2. tflite_graph.pbtxt

However, when I want to convert the tflite_graph.pb to detect.tflite I get the following error and the program ends abruptly:

"TOCO failed. See console for info.\n%s\n%s\n" % (stdout, stderr))
tensorflow.lite.python.convert.ConverterError: TOCO failed.

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Check failed: input_array_dims[i] == input_array_proto.shape().dims(i) (300 vs. 128)
Fatal Python error: Aborted
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This is the command I used to convert the .pb to .tflite :

tflite_convert --graph_def_file=tflite/tflite_graph.pb --output_file=tflite/detect.tflite --input_shapes=1,128,128,3 --input_arrays=normalized_input_image_tensor --output_arrays=TFLite_Detection_PostProcess,TFLite_Detection_PostProcess:1,TFLite_Detection_PostProcess:2,TFLite_Detection_PostProcess:3 --allow_custom_ops

The images I used had a size of 128x128 hence why I assumed that would be the input_shapes. I do have Toco installed as well.

Any help or advice will be highly appreciated.

Answer 1

So upon doing additional research, I found out that it was because the config file of the model was looking at images of sizes 300 x 300. So I changed the images dimension in the config file to 128 and it worked.