ffmpeg/libavfilter/dnn
Guo, Yejun 71e28c5422 dnn/native: add native support for minimum
it can be tested with model file generated with below python script:
import tensorflow as tf
import numpy as np
import imageio

in_img = imageio.imread('input.jpg')
in_img = in_img.astype(np.float32)/255.0
in_data = in_img[np.newaxis, :]

x = tf.placeholder(tf.float32, shape=[1, None, None, 3], name='dnn_in')
x1 = tf.minimum(0.7, x)
x2 = tf.maximum(x1, 0.4)
y = tf.identity(x2, name='dnn_out')

sess=tf.Session()
sess.run(tf.global_variables_initializer())

graph_def = tf.graph_util.convert_variables_to_constants(sess, sess.graph_def, ['dnn_out'])
tf.train.write_graph(graph_def, '.', 'image_process.pb', as_text=False)

print("image_process.pb generated, please use \
path_to_ffmpeg/tools/python/convert.py to generate image_process.model\n")

output = sess.run(y, feed_dict={x: in_data})
imageio.imsave("out.jpg", np.squeeze(output))

Signed-off-by: Guo, Yejun <yejun.guo@intel.com>
2020-05-08 15:22:27 +08:00
..
Makefile dnn_backend_native_layer_mathbinary: add sub support 2020-04-07 11:04:34 +08:00
dnn_backend_native.c
dnn_backend_native.h dnn_backend_native_layer_mathbinary: add sub support 2020-04-07 11:04:34 +08:00
dnn_backend_native_layer_conv2d.c
dnn_backend_native_layer_conv2d.h
dnn_backend_native_layer_depth2space.c
dnn_backend_native_layer_depth2space.h
dnn_backend_native_layer_mathbinary.c dnn/native: add native support for minimum 2020-05-08 15:22:27 +08:00
dnn_backend_native_layer_mathbinary.h dnn/native: add native support for minimum 2020-05-08 15:22:27 +08:00
dnn_backend_native_layer_maximum.c
dnn_backend_native_layer_maximum.h
dnn_backend_native_layer_pad.c
dnn_backend_native_layer_pad.h
dnn_backend_native_layers.c dnn_backend_native_layer_mathbinary: add sub support 2020-04-07 11:04:34 +08:00
dnn_backend_native_layers.h
dnn_backend_tf.c
dnn_backend_tf.h
dnn_interface.c