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mirror of https://git.videolan.org/git/ffmpeg.git synced 2024-07-16 09:21:39 +02:00
ffmpeg/tests/dnn
Mingyu Yin fab00b0ae0 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:output=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:output=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.yin@intel.com>
2020-08-07 10:34:22 +08:00
..
.gitignore dnn-layer-mathunary-test: add unit test for abs 2020-05-28 11:04:21 +08:00
dnn-layer-conv2d-test.c dnn: add tf.nn.conv2d support for native model 2019-10-30 10:31:55 -03:00
dnn-layer-depth2space-test.c avfilter/dnn: unify the layer execution function in native mode 2019-10-15 18:56:25 -03:00
dnn-layer-mathbinary-test.c dnn-layer-mathbinary-test: add unit test for minimum 2020-05-08 15:22:44 +08:00
dnn-layer-mathunary-test.c dnn_backend_native_layer_mathunary: add floor support 2020-08-07 10:34:22 +08:00
dnn-layer-maximum-test.c FATE/dnn: add unit test for layer maximum 2019-09-20 10:57:23 -03:00
dnn-layer-pad-test.c FATE/dnn: fix stack buffer overflow 2019-10-04 09:58:22 -03:00
Makefile dnn-layer-mathunary-test: add unit test for abs 2020-05-28 11:04:21 +08:00