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authorMingyu Yin <mingyu.yin@intel.com>2020-08-06 14:47:16 +0800
committerGuo, Yejun <yejun.guo@intel.com>2020-08-07 10:34:22 +0800
commitfab00b0ae077207a9aa1fa2cea34beb6ed860452 (patch)
tree603c3f39e7b63905fe6b55ab9b9f4abba6b9ad42 /tests/dnn
parent7031a7beae5af7648c885e05435f179beb00d4d2 (diff)
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>
Diffstat (limited to 'tests/dnn')
-rw-r--r--tests/dnn/dnn-layer-mathunary-test.c4
1 files changed, 4 insertions, 0 deletions
diff --git a/tests/dnn/dnn-layer-mathunary-test.c b/tests/dnn/dnn-layer-mathunary-test.c
index 7da3a206ed..0bfcdcbd85 100644
--- a/tests/dnn/dnn-layer-mathunary-test.c
+++ b/tests/dnn/dnn-layer-mathunary-test.c
@@ -58,6 +58,8 @@ static float get_expected(float f, DNNMathUnaryOperation op)
return atanh(f);
case DMUO_CEIL:
return ceil(f);
+ case DMUO_FLOOR:
+ return floor(f);
default:
av_assert0(!"not supported yet");
return 0.f;
@@ -132,5 +134,7 @@ int main(int agrc, char **argv)
return 1;
if (test(DMUO_CEIL))
return 1;
+ if (test(DMUO_FLOOR))
+ return 1;
return 0;
}