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Working with tf 2.0 #83

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f92172d
Working with tf 2.0
SubhadityaMukherjee Dec 1, 2019
0f4f2c6
bug fixes
SubhadityaMukherjee Dec 1, 2019
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12 changes: 6 additions & 6 deletions utils/process_images.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,7 +37,7 @@
from tqdm import tqdm

# configure command line interface arguments
flags = tf.app.flags
flags = tf.compat.v1.flags
flags.DEFINE_string('model_dir', '/tmp/imagenet', 'The location of downloaded pre-trained Inception model')
flags.DEFINE_string('image_files', '', 'A glob path of images to process')
flags.DEFINE_integer('clusters', 20, 'The number of clusters to display in the image browser')
Expand Down Expand Up @@ -155,15 +155,15 @@ def create_image_vectors(self):
self.create_tf_graph()

print(' * creating image vectors')
with tf.Session() as sess:
with tf.compat.v1.Session() as sess:
for image_index, image in enumerate(tqdm(self.image_files)):
try:
outfile_name = os.path.basename(image) + '.npy'
out_path = join(self.output_dir, 'image_vectors', outfile_name)
if os.path.exists(out_path) and not self.rewrite_image_vectors:
continue
# save the penultimate inception tensor/layer of the current image
with tf.gfile.FastGFile(image, 'rb') as f:
with tf.compat.v2.io.gfile.GFile(image, 'rb') as f:
data = {'DecodeJpeg/contents:0': f.read()}
feature_tensor = sess.graph.get_tensor_by_name('pool_3:0')
feature_vector = np.squeeze( sess.run(feature_tensor, data) )
Expand Down Expand Up @@ -202,8 +202,8 @@ def create_tf_graph(self):
'''
print(' * creating tf graph')
graph_path = join(FLAGS.model_dir, 'classify_image_graph_def.pb')
with tf.gfile.FastGFile(graph_path, 'rb') as f:
graph_def = tf.GraphDef()
with tf.compat.v1.gfile.GFile(graph_path, 'rb') as f:
graph_def = tf.compat.v1.GraphDef()
graph_def.ParseFromString(f.read())
_ = tf.import_graph_def(graph_def, name='')

Expand Down Expand Up @@ -491,4 +491,4 @@ def main(*args, **kwargs):
PixPlot(image_glob)

if __name__ == '__main__':
tf.app.run()
tf.compat.v1.app.run()