How Can I convert this model to TFLITE about mobile-semantic-segmentation HOT 13 OPEN

Thanks @sercant
But I hav some problem...
in Shell...

Traceback (most recent call last):
  File "tf-convert-tflite.py", line 89, in <module>
    main(**vars(args))
  File "tf-convert-tflite.py", line 47, in main
    tflite_model = converter.convert()
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/lite.py", line 439, in convert
    **converter_kwargs)
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/convert.py", line 309, in toco_convert_impl
    input_data.SerializeToString())
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/convert.py", line 109, in toco_convert_protos
    (stdout, stderr))
RuntimeError: TOCO failed see console for info.
/bin/sh: toco_from_protos: command not found

None

I can't handling this shell error... So How can i do solve this problem?

has anyone solved this error, i'm getting same error for my model

Hey @chin87, I think this is due to a bug in Tensorflow right now. Be sure that toco_from_protos is in your PATH variable.

Also, I have an updated version of the script at my repo if you want to check it out. You will need to modify it to work with this repo though.

from mobile-semantic-segmentation.

@akirasosa please help

from mobile-semantic-segmentation.

Hello @kei9327,

Here is a script that I wrote to convert the model to tf-lite. Also, the model is being tested with the python tf-lite interpreter in the code but you can just comment that part out if you don't need it.

https://gist.github.com/sercant/478cac13391e1b69b2be07654cf3d21e

tf-convert-tflite.py

import argparse

import cv2
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf

from data import standardize

prefix = 'hair_recognition'


def main(pb_file, img_file):
    """
    Predict and visualize by TensorFlow.
    :param pb_file:
    :param img_file:
    :return:
    """
    with tf.gfile.GFile(pb_file, "rb") as f:
        graph_def = tf.GraphDef()
        graph_def.ParseFromString(f.read())

    with tf.Graph().as_default() as graph:
        tf.import_graph_def(graph_def, name=prefix)

    for op in graph.get_operations():
        print(op.name)

    x = graph.get_tensor_by_name('%s/input_1:0' % prefix)
    y = graph.get_tensor_by_name('%s/output_0:0' % prefix)

    loaded_image = cv2.cvtColor(cv2.imread(img_file,-1), cv2.COLOR_BGR2RGB)
    resized_image =cv2.resize(loaded_image, (128, 128))
    input_image = np.expand_dims(np.float32(resized_image[:128, :128]),axis=0)/255.0

    # images = np.load(img_file).astype(float)
    # img_h = images.shape[1]
    # img_w = images.shape[2]

    with tf.Session(graph=graph) as sess:
        # for img in images:
        # batched = img.reshape(-1, img_h, img_w, 3)
        normalized = standardize(input_image)
        
        converter = tf.contrib.lite.TocoConverter.from_session(sess, [x], [y])
        tflite_model = converter.convert()
        open("converted_model.tflite", "wb").write(tflite_model)

        # Load TFLite model and allocate tensors.
        interpreter = tf.contrib.lite.Interpreter(model_content=tflite_model)
        interpreter.allocate_tensors()

        # Get input and output tensors.
        input_details = interpreter.get_input_details()
        output_details = interpreter.get_output_details()

        # Test model on random input data.
        # input_shape = input_details[0]['shape']
        input_data = np.array(normalized, dtype=np.float32)
        interpreter.set_tensor(input_details[0]['index'], input_data)

        interpreter.invoke()
        output_data = interpreter.get_tensor(output_details[0]['index'])
        # print(output_data)
        

        # pred = sess.run(y, feed_dict={
        #     x: normalized
        # })
        plt.imshow(output_data.reshape(128, 128))
        plt.show()


if __name__ == '__main__':
    parser = argparse.ArgumentParser()
    parser.add_argument(
        '--pb_file',
        type=str,
        default='artifacts/model.pb',
    )
    parser.add_argument(
        '--img_file',
        type=str,
        default='data/glasshair.jpg',
        help='image file as numpy format'
    )
    args, _ = parser.parse_known_args()
    main(**vars(args))

from mobile-semantic-segmentation.

Thanks @sercant

But I hav some problem...

in Shell...

Traceback (most recent call last):
  File "tf-convert-tflite.py", line 89, in <module>
    main(**vars(args))
  File "tf-convert-tflite.py", line 47, in main
    tflite_model = converter.convert()
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/lite.py", line 439, in convert
    **converter_kwargs)
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/convert.py", line 309, in toco_convert_impl
    input_data.SerializeToString())
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/convert.py", line 109, in toco_convert_protos
    (stdout, stderr))
RuntimeError: TOCO failed see console for info.
/bin/sh: toco_from_protos: command not found

None

I can't handling this shell error... So How can i do solve this problem?

from mobile-semantic-segmentation.

Hi, I have rewrite code using PyTorch and tf-lite is TODO now.

from mobile-semantic-segmentation.

did you notice better accuracy when using pytorch?

from mobile-semantic-segmentation.

Thanks @sercant

But I hav some problem...

in Shell...

Traceback (most recent call last):
  File "tf-convert-tflite.py", line 89, in <module>
    main(**vars(args))
  File "tf-convert-tflite.py", line 47, in main
    tflite_model = converter.convert()
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/lite.py", line 439, in convert
    **converter_kwargs)
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/convert.py", line 309, in toco_convert_impl
    input_data.SerializeToString())
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/convert.py", line 109, in toco_convert_protos
    (stdout, stderr))
RuntimeError: TOCO failed see console for info.
/bin/sh: toco_from_protos: command not found

None

I can't handling this shell error... So How can i do solve this problem?

Maybe it's because of the python or tensorflow version difference. I am using Python 3.6.5 and Tensorflow 1.12.0.

from mobile-semantic-segmentation.

Thanks @sercant
But I hav some problem...
in Shell...

Traceback (most recent call last):
  File "tf-convert-tflite.py", line 89, in <module>
    main(**vars(args))
  File "tf-convert-tflite.py", line 47, in main
    tflite_model = converter.convert()
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/lite.py", line 439, in convert
    **converter_kwargs)
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/convert.py", line 309, in toco_convert_impl
    input_data.SerializeToString())
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/convert.py", line 109, in toco_convert_protos
    (stdout, stderr))
RuntimeError: TOCO failed see console for info.
/bin/sh: toco_from_protos: command not found

None

I can't handling this shell error... So How can i do solve this problem?

Maybe it's because of the python or tensorflow version difference. I am using Python 3.6.5 and Tensorflow 1.12.0.

If it's not an excuse, Do you have any pretrain data (TFLite)?

from mobile-semantic-segmentation.

Thanks @sercant
But I hav some problem...
in Shell...

Traceback (most recent call last):
  File "tf-convert-tflite.py", line 89, in <module>
    main(**vars(args))
  File "tf-convert-tflite.py", line 47, in main
    tflite_model = converter.convert()
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/lite.py", line 439, in convert
    **converter_kwargs)
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/convert.py", line 309, in toco_convert_impl
    input_data.SerializeToString())
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/convert.py", line 109, in toco_convert_protos
    (stdout, stderr))
RuntimeError: TOCO failed see console for info.
/bin/sh: toco_from_protos: command not found

None

I can't handling this shell error... So How can i do solve this problem?

Maybe it's because of the python or tensorflow version difference. I am using Python 3.6.5 and Tensorflow 1.12.0.

If it's not an excuse, Do you have any pretrain data (TFLite)?

Here is the one I converted using shared pre-trained model.

from mobile-semantic-segmentation.

@sercant how did the model performed on your implementation? I just tried this today and it performed really bad... not only is it slow ~1100ms it also just tries to predict a hair in the middle of the screen everytime.

from mobile-semantic-segmentation.

@sercant how did the model performed on your implementation? I just tried this today and it performed really bad... not only is it slow ~1100ms it also just tries to predict a hair in the middle of the screen everytime.

Yes, it was the same case for me regarding both performance and the behavior. I don't know why it tries to find a hair in the middle of the screen all the time. Maybe the checkpoint provided in #17 was overfitted.

from mobile-semantic-segmentation.

Thanks @sercant

But I hav some problem...

in Shell...

Traceback (most recent call last):
  File "tf-convert-tflite.py", line 89, in <module>
    main(**vars(args))
  File "tf-convert-tflite.py", line 47, in main
    tflite_model = converter.convert()
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/lite.py", line 439, in convert
    **converter_kwargs)
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/convert.py", line 309, in toco_convert_impl
    input_data.SerializeToString())
  File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/tensorflow/contrib/lite/python/convert.py", line 109, in toco_convert_protos
    (stdout, stderr))
RuntimeError: TOCO failed see console for info.
/bin/sh: toco_from_protos: command not found

None

I can't handling this shell error... So How can i do solve this problem?

has anyone solved this error, i'm getting same error for my model

from mobile-semantic-segmentation.

Hi @sercant @akirasosa sorry for bringing up this 2 year old issue. Any news on adding a script to convert to tflite?
@sercant , does your script still works with this repo? Thank you in advance!

from mobile-semantic-segmentation.