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import tensorflow as tf
import numpy as np
from PIL import Image
batch_size = 32
loaded_graph = tf.Graph()
with tf.Session(graph=loaded_graph) as sess:
tf.saved_model.loader.load(sess, [tf.saved_model.tag_constants.TRAINING], "./models/roofs_not_roofs/")
im = np.array(Image.open("./test_pic/b2_DJI_0145_02_05.png"), np.float32)[None,...]/256
x = loaded_graph.get_tensor_by_name('x:0')
y = loaded_graph.get_tensor_by_name('y:0')
print([n.name for n in loaded_graph.as_graph_def().node])
predictor = loaded_graph.get_tensor_by_name('results/pixel_wise_softmax/predicter:0')
keep_prob = loaded_graph.get_tensor_by_name('dropout_probability:0')
print("imshape",im.shape)
y_dummy = np.empty((im.shape[0], im.shape[1], im.shape[2], 2))
res = sess.run(predictor,feed_dict= {x: im,keep_prob: 1.0,y:y_dummy})[0, ..., 1]
print(res.shape) # THIS LINE IS NOT EXECUTED...
ri=Image.fromarray((res*256).astype(np.uint8))
ri.save("pred.png");
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