First I named the one of the output results "cls_prob_test" as tensor_output on line 161 in mtcnn_model.py:
line 161: cls_pro_test = tf.squeeze(conv4_1, axis=0,name = "cls_prob_test")
Then I use codes below to generate PNet.meta:
import tensorflow as tf
import sys
sys.path.append("../")
from train_models.mtcnn_model import P_Net
model_path = '../data/MTCNN_model/PNet_landmark/PNet-18'
graph = tf.Graph()
with graph.as_default():
image_op = tf.placeholder(tf.float32,[200,200,3], name='input')
image_reshape = tf.reshape(image_op, [1, 200, 200, 3])
cls_prob, bbox_pred, _ = P_Net(image_reshape, training=False)
sess = tf.Session(
config=tf.ConfigProto(allow_soft_placement=True, gpu_options=tf.GPUOptions(allow_growth=True)))
saver = tf.train.Saver()
# check whether the dictionary is valid
model_dict = '/'.join(model_path.split('/')[:-1])
ckpt = tf.train.get_checkpoint_state(model_dict)
print(model_path)
readstate = ckpt and ckpt.model_checkpoint_path
assert readstate, "the params dictionary is not valid"
print("restore models' param")
saver.restore(sess, model_path)
saver = tf.train.Saver(tf.global_variables())
saver.save(sess, "output/PNet" )
Finally ,I use mvNCCompile command：
mvNCCompile output/PNet.meta -s 12 -in=input -on=cls_prob_test -is 200 200 -o MTCNN.graph
But report an error:
[Error 5] Toolkit Error: Stage Details Not Supported: Abs
