add test code for inference

Author: GE ZHENG

test.py

@@ -0,0 +1,50 @@
+import tensorflow as tf
+import numpy as np
+import os
+from scipy import misc
+from matting_numpy_unpool import generate_trimap
+import argparse
+import sys
+
+g_mean = np.array(([126.88,120.24,112.19])).reshape([1,1,3])
+
+def main(args):
+	
+	gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction = args.gpu_fraction)
+	with tf.Session(config=tf.ConfigProto(gpu_options = gpu_options)) as sess:
+		saver = tf.train.import_meta_graph('./meta_graph/my-model.meta')
+		saver.restore(sess,tf.train.latest_checkpoint('./model'))
+		image_batch = tf.get_collection('image_batch')[0]
+		GT_trimap = tf.get_collection('GT_trimap')[0]
+		pred_mattes = tf.get_collection('pred_mattes')[0]
+
+		rgb = misc.imread(args.rgb)
+		alpha = misc.imread(args.alpha,'L')
+		trimap = generate_trimap(np.expand_dims(np.copy(alpha),2),np.expand_dims(alpha,2))[:,:,0]
+		origin_shape = alpha.shape
+		rgb = np.expand_dims(misc.imresize(rgb.astype(np.uint8),[320,320,3]).astype(np.float32)-g_mean,0)
+		trimap = np.expand_dims(np.expand_dims(misc.imresize(trimap.astype(np.uint8),[320,320],interp = 'nearest').astype(np.float32),2),0)
+
+		feed_dict = {image_batch:rgb,GT_trimap:trimap}
+		pred_alpha = sess.run(pred_mattes,feed_dict = feed_dict)
+		final_alpha = misc.imresize(np.squeeze(pred_alpha),origin_shape)
+		misc.imshow(final_alpha)
+		misc.imsave('./alpha.png',final_alpha)
+
+def parse_arguments(argv):
+	parser = argparse.ArgumentParser()
+
+	parser.add_argument('--alpha', type=str,
+		help='input alpha')
+	parser.add_argument('--rgb', type=str,
+		help='input rgb')
+	parser.add_argument('--trimap_dilation', type=int,
+		help='the kernel size that used to generate trimap from alpha, 20~40 are suggested',default = 30)
+	parser.add_argument('--gpu_fraction', type=float,
+		help='how much gpu is needed, usually 4G is enough',default = 0.4)
+	return parser.parse_args(argv)
+
+
+if __name__ == '__main__':
+    main(parse_arguments(sys.argv[1:]))
+