> -----Original Message-----
> From: ffmpeg-devel <ffmpeg-devel-boun...@ffmpeg.org> On Behalf Of Mingyu
> Yin
> Sent: 2020年8月6日 14:47
> To: ffmpeg-devel@ffmpeg.org
> Subject: [FFmpeg-devel] [PATCH] dnn_backend_native_layer_mathunary: add
> floor support
>
> It can be tested with the model generated with below python script:
>
> import tensorflow as tf
> import os
> import numpy as np
> import imageio
> from tensorflow.python.framework import graph_util name = 'floor'
>
> pb_file_path = os.getcwd()
> if not os.path.exists(pb_file_path+'/{}_savemodel/'.format(name)):
> os.mkdir(pb_file_path+'/{}_savemodel/'.format(name))
>
> with tf.Session(graph=tf.Graph()) as sess:
> in_img = imageio.imread('detection.jpg')
> in_img = in_img.astype(np.float32)
> in_data = in_img[np.newaxis, :]
> input_x = tf.placeholder(tf.float32, shape=[1, None, None, 3],
> name='dnn_in')
> y_ = tf.math.floor(input_x*255)/255
> y = tf.identity(y_, name='dnn_out')
> sess.run(tf.global_variables_initializer())
> constant_graph = graph_util.convert_variables_to_constants(sess,
> sess.graph_def, ['dnn_out'])
>
> with
> tf.gfile.FastGFile(pb_file_path+'/{}_savemodel/model.pb'.format(name),
> mode='wb') as f:
> f.write(constant_graph.SerializeToString())
>
> print("model.pb generated, please in ffmpeg path use\n \n \
> python tools/python/convert.py {}_savemodel/model.pb
> --outdir={}_savemodel/ \n \nto generate model.model\n".format(name,name))
>
> output = sess.run(y, feed_dict={ input_x: in_data})
> imageio.imsave("out.jpg", np.squeeze(output))
>
> print("To verify, please ffmpeg path use\n \n \
> ./ffmpeg -i detection.jpg -vf
> format=rgb24,dnn_processing=model={}_savemodel/model.pb:input=dnn_in:ou
> tput=dnn_out:dnn_backend=tensorflow -f framemd5
> {}_savemodel/tensorflow_out.md5\n \
> or\n \
> ./ffmpeg -i detection.jpg -vf
> format=rgb24,dnn_processing=model={}_savemodel/model.pb:input=dnn_in:ou
> tput=dnn_out:dnn_backend=tensorflow {}_savemodel/out_tensorflow.jpg\n
> \nto generate output result of tensorflow model\n".format(name, name, name,
> name))
>
> print("To verify, please ffmpeg path use\n \n \
> ./ffmpeg -i detection.jpg -vf
> format=rgb24,dnn_processing=model={}_savemodel/model.model:input=dnn_in
> :output=dnn_out:dnn_backend=native -f framemd5
> {}_savemodel/native_out.md5\n \
> or \n \
> ./ffmpeg -i detection.jpg -vf
> format=rgb24,dnn_processing=model={}_savemodel/model.model:input=dnn_in
> :output=dnn_out:dnn_backend=native {}_savemodel/out_native.jpg\n \nto
> generate output result of native model\n".format(name, name, name, name))
>
> Signed-off-by: Mingyu Yin <mingyu....@intel.com>
> ---
> libavfilter/dnn/dnn_backend_native_layer_mathunary.c | 4 ++++
> libavfilter/dnn/dnn_backend_native_layer_mathunary.h | 1 +
> tests/dnn/dnn-layer-mathunary-test.c | 4 ++++
> tools/python/convert_from_tensorflow.py | 2 +-
> tools/python/convert_header.py | 2 +-
> 5 files changed, 11 insertions(+), 2 deletions(-)
LGTM, will push soon, thanks.
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